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Universität Augsburg. Institut für Informatik D Augsburg. Learning Scrutable User Models: Inducing Conceptual Descriptions. Martin E.
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1 Universität Augsburg Learning Scrutable User Models: Inducing Conceptual Descriptions Martin E. Müller Report März 2002 Institut für Informatik D Augsburg
2 Copyright c Martin E. Müller Institut für Informatik Universität Augsburg D Augsburg, Germany all rights reserved
3 Abstract The problem of filtering relevant information from the huge amount of available data is tackled by using models of the user s interest in order to discriminate interesting information from un interesting data. As a consequence, Machine Learning for User Modeling (Ml4Um) has become a key technique in recent adaptive systems. This article presents the novel approach of conceptual user models which are easy to understand and which allow for the system to explain its actions to the user. We show that Ilp can be applied for the task of inducing user models from even sparse feedback by mutual sample enlargement. Results are evaluated independently of domain knowledge within a clear machine learning problem definition. The whole concept presented is realized in a meta web search engine, OySTER. (To appear in: Künstliche Intelligenz, 4/2002.) 1
4 Learning Scrutable User Models: Inducing Conceptual Descriptions Martin E. Müller Abstract. The problem of filtering relevant information from the huge amount of available data is tackled by using models of the user s interest in order to discriminate interesting information from un interesting data. As a consequence, Machine Learning for User Modeling (Ml4Um) has become a key technique in recent adaptive systems. This article presents the novel approach of conceptual user models which are easy to understand and which allow for the system to explain its actions to the user. We show that Ilp can be applied for the task of inducing user models from even sparse feedback by mutual sample enlargement. Results are evaluated independently of domain knowledge within a clear machine learning problem definition. The whole concept presented is realized in a meta web search engine, OySTER. 1 Conceptual User Models In Ml4Um user models are often represented by n ary vectors. In the course of content based document recommendation, the vectors represent significance of key phrases for the user s interest which is defined as the frequency (TfIdf and similar) of those phrases in the documents the user has rated ( relevance feedback ) as interesting in the past. In order to decide whether to recommend a document or not, the document (i.e. the corresponding vector) is compared to the user model vector, see [2, 1, 9], [5] and [6]. Though the vectors represent a user s interest, they do not explicitely describe a user s interest: A sequence of word frequencies is not a user model that can be explained to the user in an intutive way. Thus, our motivation was to find a transparent formalism which is accessible to every user and which allows for an easy translation into the user s language. Such a language could be the language of concept hierarchies. The choice of such an approach is supported by the fact, that humans in general (including unexperienced users in the web) are capable of describing and finding objects using concept hierarchies such as library taxonomies, classification systems or web directories. As a result, we obtain a user adaptive system, which is capable of describing internal user models and which can explain recommendations to the user, thereby increasing user acceptance because the user is able to map elements of taxonomies onto meaningful concepts. The crucial difference is, that the user 2 Conceptual descriptions Within OySTER we use two taxonomies of classes: One for document types (T ) and one for document content (categories, C). A pictorial view on the question of whether a certain document is interesting for a user u with respect to the underlying user model M u, is shown in figure Document categories and types The OySTER taxonomy C covers research related document in the field of artificial intelligence and neighboring communities. It is handishly coded, taking into account our experience with already existing taxonomies such as the universal decimal classification (Udc), the dmoz ontology and personal experience with classifying news articles, [3]. The resulting ontology consists of 69 classes with a maximum depth of 5. 1 Documents a and b are assigned a unique class. Document c belongs to at least two known classes. Thus, the user is interested in document b (about machine learning) and not in document a, because it is about DOS. 2
5 Figure 1: Using C for both document classification and user models Accordingly, the hierarchy of document types can roughly be divided into homepages, research articles and lecture material. Document or text types are discussed within computational linguistics but are rather unknown in the domain of text classification for user centered document retrieval. 2 The hierarchy of document types contains 35 classes with a maximum tree depth of 4. The classifiers C for the document content taxonomy C were developed in course of the Bikini project, [3]. Representing documents. Using our classifiers C and T documents d are represented by their classification: T C(d) = T (d), C (d) = t : c = t :: p, c 1 :: p 1, c 2 :: p 2,..., c n :: p n where t is the document s type and p the confidence of the classification and c i are categories with decreasing values of confidence p i. Modeling the taxonomies and inheritance of concepts by entailment means that the intuitive subsumption relation is a is realized as logical implication. Accordingly, the taxonomy is represented as a set of Horn clauses as shown below. The predicate genpenalty is used as a generalization bias: cat_..._cs(x,d) :- cat_..._cs_programming(x,c), genpenalty(c,d). cat_..._cs_programming(x,d) :- cat_..._cs_programming_languages(x,c), genpenalty(c,d). 2 Although text types like newspaper article, obituary or poem are widely accepted, the new document types that emerged with the Www have not been discussed to a satisfying extent so far. Researchers agree that there are text types like homepage but it is still argued whether those types are already known types which have been adapted to new media or whether they are genuine types. 3
6 cat_..._cs_programming_languages(x,d) :- cat_..._cs_programming_languages_procedural(x,), genpenalty(c,d). Document types T are represented in a similar way. Background knowledge is represented as a set of facts (here, classifaction data for the Url 5121): type_..._researchpaper(5121,68). cat_..._ai_machine_learning_symbolic(5121,92). cat_..._ai_nat_lang_proc_generation(5121,78). cat_..._ai_machine_learning_subsymbolic(5121,20). Figure 2: One aspect of a user model as shown in the OySTER search engine 2.2 Describing interest by concepts Since a user is not interested in single, very specific topics only, a user model may consist of several aspects which describe different, specific parts of a user s interest. Aspects can be compared to specific topics of interest, or, e.g. to folders for news items or s (c.f. [1, 12]). 3 The aspect shown in figure 2 is interpreted as: A document d is considered relevant with respect to the aspect Conceptual User Models if it classifies as: 1. a publication about knowledge representation 2. a publication about symbolic machine learning 3. a publication about user modeling with according confidence values. Representing a user model by a set of Horn clauses is very straightforward. The example from above yields: p interest u(a, D): type...publication(d, T 1 ), cat...knowledge representation(d, C 1 ), type...publication(d, T 2 ), cat...symbolic machine learning(d, C 2 ), type...publication(d, T 3 ), cat...user modeling(d, C 3 ), (C 1 25), (C 2 35), (C 3 40), (1) 3 Furthermore, we also explicitely model what the user is not interested in (i.e. his dis interest). 4
7 3 Inducing user models In the last section we have shown how conceptual user models can be represented as Horn clauses. Our aim is to induce such user models by taking into account user feedback that has been given with respect to documents. Therefore, the learning target is a Prolog clause which gives rise to the application of inductive logic programming methods, Ilp; see [8]. Although Ilp has the advantage of inducing lucid hypotheses, it is still an underestimated machine learning approach in the context of user modeling. Nevertheless, there are several recent advances, e.g. [4]. The hypotheses are generated by the Ilp learner Progol, [7], which is based on the inverse entailment method. Our approach and the following evaluation is based on several assumptions and focuses on a special aspect within the whole approach of user adaptive web search: (1) Knowledge about documents and knowledge about users are strictly discriminated. We argue, that user models shall contain information about the users interest but no domain knowldege. 4 (2) Feedback is strictly discriminated from labels: Feedback ( relevance feedback ) is given with respect to documents, but interest is represented by concepts. As a consequence, labels are generated by interpreting feedback as relevance feedback with respect to categories. The way of interpretation allows us to generate samll precise or larger but noisier samples (3) Following the argument in (1), our approach is based on the assumption, that no prior knowledge is available. This means, that our user modeling problem can be described by the aim to learn user models from scratch with only a few examples. 3.1 Representing user models Thinking towards a working user model induction process and thus having in mind a feasible learning problem, one needs to refine the rough idea of modeling a user s interest a bit further. One of the most prominent problems within user model induction is sparse negative feedback. This leads to several problems; the most intriguing problem is that one would need to employ a learning algorithm which works for little data and/or for positive data only, [11]. Thus, we introduced the novel approach of explicitly modeling a user s disinterest 5 : In figure fig:ontosk differently shaded nodes represent concepts that are of interest or which are known not to be of interest. One also could interpret non interestingness in this figure as explicit disinterest. This leads to the following definition: [User model M u ] A user model M u is a tuple M u +, Mu, where M u + models the user s interest and Mu models the user s disinterest. Aspects a are subsets of M u : M u (a) = M u + (a), Mu (a). Interest of u with respect to aspect a is represented by the binary predicate p interest u (a, ); disinterest by the according binary predicate n interest u (a, ). The following clause is an element of M u + (a) M u + : p interest u(a, D) : type t 1 (D, T 1 ),..., type t nt (D, T nt ), cat c 1 (D, C 1 ),..., cat c nc (D, C nc ), thresh(c 1, ϑ 1 ),..., thresh(c n, ϑ n ). (2) where u is the user id, a the aspect id and D is instantiated with the id d of the document currently under consideration. Document types (t i ) and categories (c j ) are assigned confidence values tc i and cc j, respectively. Finally, thresholds require confidence values to be greater than a certain boundary ϑ k. Explicitly modeling of the user s disinterest is a rather novel approach in user modeling ([12] use three different kinds of feature vectors to describe long and short term interest where the short term is described by both explicit interest and disinterest). 4 Incorporating system dependent domain knowledge will most likely improve the quality of results, but makes evaluation of the learned user model impossible. 5 We chose this word in analogy to dis like. 5
8 3.2 Feedback and samples In our approach, we assume that feedback F u given by a user u will be used to construct a labeled sample f u using a function Γ. We want to approximate the target function i u (the characteristic function of the user s interest I u on the hypothesis space) by a user model M u. Feedback. The feedback given by user u is a relation F u between documents d and feedback values. Relevance of documents with respect to aspect is not neccessarily disjoint, because same document can be interesting to several aspects. For our formalization, we need to assume that feedback is disjoint. This assumption is required for using feedback given with respect to aspect aas a basis for larger samples which includes examples for a as examples for a and vice versa. For our evalution, however, we used feedback data which deliberatly violates this assumption (relevance as indicated by feedback may overlap for different aspects) in order to achieve results that withstand real world data. Accordingly, the sample f u has to provide more information than contained in F u. This leads to the following definition: [User modeling sample, f u ] A sample that is used for a learning problem in user modeling consists of a sequence of labeled pieces of evidence [ ] {+, } f u = d i, a i, v i (3) i I where d i are documents of the domain, values v i {, } are example labels, a i are valid aspects in M u and the superscript denotes the target M + u or M u. Note, that according to definition 5, f u actually includes label data that will be used for different learning targets, namely M + u (a i ) and M u (a i ). To clarify the contents and information provided by feedback and different samples we have depicted an example in figure fig:feedbackaspect. 6 (1) (2) d d d d d d a a d 1 d 2 d 3 a a (5) a a d 1 d 2 d 3 d d d (3) (4) Figure 3: Feedback F u,a and a sample f u The domain contains three documents d 1, d 2, d 3. The learning target is split into two aspects a, a. Part (1) shows feedback as given by the user: A plus sign (+) represent a positive label while a minus sign (-) represents negative feedback. Obviously, document d 1 is interesting with respect to a, but not with respect to aspect a. Document d 2 on the other hand, is not interesting with respect to a ; its relevance to a is unknown. The third document is interesting for a, but relevance 6 Feedback for document d 1 shows that aspects are disjoint (see end of paragraph def:user-models-dis). 6
9 with respect to a is unknown. For some documents there is only positive (d 3 ) or only negative evidence (d 2 ). From this feedback data we want to derive a sample as shown in definition 3.2. In a first step, (2), the given feedback is mapped one to one onto labeled examples. Upward pointing bars indicate feedback with respect to M u +, while downward pointing arrows indicate relevance for disinterest. As an example, consider document d 3 : Since it was rated interesting with respect to a, we have positive evidence for M u + (a). But this also means, that d 3 represents negative evidence for Mu (a ). One might claim, that from the feedback gathered we might conclude that d 3 is a negative example for M u + (a ) as well: The same holds for d 1 and Mu (a). This is shown in part (3). Thinking a step further, one might even guess, that d 2 might be of interest with respect to a since it is not of interest with respect to a. The same argument applies to d 1 and a, see part (4). Of course, this is a very vague guess which may rather cause noisy samples instead of large, reliable samples. Putting it all together we yield a sample as shown in part (5). Note, that in this figure, we have not depicted whether feedback for some d with respect to a is interpreted as evidence for M u + or Mu. Generating samples. As already stated, we assume that a document d which is interesting for u with respect to an interest aspect a is most likely non interesting for another aspect a. Since relevance of d shall only be provable by means of M u + (a) a hypothesis for M u + (a ) should exclude d. Table fig:generatesamplesfromfeedback shows different ways to interpret relevance feedback using Γ functions as a sample f u (see last section and figure fig:feedbackaspect). Taking into account F u,a f u d, A, v d, a, i u (d) Γ A v i u (d) t + a M + u a M u + a M + u a M u 1 a M + u 2 a M u 3 a M u 4 a M + u Table 1: Generating samples from feedback relevance feedback with respect to other aspects a, f u can be enlarged by decreasingly reliable information as provided by Γ 1,..., Γ 4. Γ 1 simply states the fact, that aspects are exclusive. Γ 2 takes positive evidence for interest in a as positive evidence for disinterest in a. This inference is not as reliable as Γ 1. Therefore, Γ 2 should only be considered in cases, where there is very little labeled data available for M u. Γ 3 states that an uninteresting (with respect to a ) document d is not necessarily uninteresting for aspect a. Thus, it is (weak) negative evidence for M u (a), too. However, such documents d can be interesting for M + u (a). This is stated by Γ 4, but is not reliable at all and prone to generate noise (thus, it is only defined for reasons of symmetry). 4 Results It is clear, that specific interests provide a better base for inducing user models than shattered or vague feedback. 7
10 Accordingly, we carried out an evaluation of several different user characteristics. We simulated four different user characteristics with different specificity of interest. For each user, 50 aspects were generated. By combining aspects we were able to evaluate the learning of single aspects of different specificity as well as the accuracy gain of Γ application for multiple aspects. The specificity of interest was used to generate more or less noisy feedback samples on simulated Urls with respect to a distance measure on the taxonomy. The Urls themselves were simulated by generating classification data. To ensure validity of our generated Urls, we defined a diversity measure of Url classifications as the sum of category distances. On real documents, the average diversity was 17.27; the Urls generated in our test set were chosen such that the overall average diversity is slightly worse (18.78). 4.1 Learning single aspects The left graph in figure 4 shows that accuracy increases both in specificity and sample size. 7 A 100 User 111 User 222 User 333 User Accuracy Sample Size Examples 50 Examples 25 Examples 10 Examples 5 Examples 80 Accuracy Aspect Id Figure 4: Learning p interest for specific interests more detailed evaluation of the accuracy for learning p interest for user 444 only is shown in the right graph in figure 4 (the graphs on the left hand side are average values derived from such data files). 4.2 Learning multiple aspects It has been shown that accuracy for small samples is rather poor; one cannot feel overly impressed by an initial accuracy of 54%. However, learning from five examples only is a very hard problem. This motivates using mutual feedback from other aspects in order to enlarge the sample. In the 7 Most specific interest in user 444, decreasing specificity for users
11 following evaluation, interest aspect 8 was chosen as aspect a whose feedback data is used by Γ in order to gain more examples for learning aspects a = [1,..., 50]. The evaluation was carried out for users with 50 aspects each, thus modeling 200 different aspects of different specificity. For each user, initial samples of length 5, 10, 25, 50 and 75 were generated (with an uniform distribution of positive and negative examples). Γ 1 and Γ 4 enlarged all samples by 15 examples that were generated from feedback given with respect to aspect a =8. The average accuracy gain in relation to figure 4 is described in table 2. The last line shows results for a worst case evalutation which was performed on deliberately noisy domain data. It shows, that Γ performes best if used on samples of length 25. On shorter samples (length 5 and 10), Γ performs slightly worse (in number and average accuracy gain) than in the reference case. For longer samples, both number of and average accuracy gain are significantly smaller than in the reference case. As a consequence, documents with multiple topics (i.e. a strong diversity), generate noisy learning and evaluation samples. A solution to this problem is to take into account only the most reliable document classification. Therefore, the outcome of this evaluation can be regarded as a baseline of minimal performance which is guaranteed by our approach: Accuracy gain is still obtained in several cases and, neglecting cases where Γ actually delivers worse results 8, follows the general rules of improving learning results. Sample size User % 5.6 % 0% % 6.4 % 0% % 5.0 % 0% % 6.6 % 0% % 3.8 % 2.5 % Table 2: Average positive accuracy gain 4.3 Discussion From the results, we draw two major conclusions: Only small samples should be enlarged. With growing sample size, the impact of Γ functions decreases. Due to the fact that the accuracy of plainly derived hypotheses increases for larger samples, application of Γ functions does not contribute to the result. In such cases, enlarged samples noisify the input. As results for sample length 50 show, accuracy on Γ samples actually drops significantly below plain learning accuracy. Specificity of interest. Over specific interest as simulated by user 444 leads to highly accurate hypotheses. This explains a relatively poor accuracy gain using Γ functions for user 444. The best average accuracy gain (5.8%) on samples of length 5 was obtained for the specific (but not over specific) user 111. More than 20% of all aspects could be learned with a higher accuracy using Γ functions. For a sample size of 10 examples, similar results can be derived. It is noteworthy, that Γ helps to increase accuracy for 9 of 50 aspects for user 111 while it helps for only 3 aspects for user 444. It has to be emphasized, that we deliberately violated our assumption of disjointness of aspects in this evaluation (the extreme case is the result for learning aspect 8) in order to show that our approach even works in domains which do not meet the theoretical requirements. A better method to cope with similar aspects would have been to choose only those aspects a, a,... 8 Such cases can be prevented by testing sample accuracy of hypothesis for plain samples and Γ enhanced samples. If sample accuracy for enhanced samples drops below accuracy on the initial sample, hypotheses are discarded. 9
12 for each learning task M u (a), where a, a,... significantly differ from a (this can be modeled by means of the distance measure δ on C). Summary of results. It has been shown, that sample enlargement pays off for small samples only. Plain learning average accuracy results of between 50 to 52% do not sound very promising. One must bear in mind though, that samples of length 5 pose a very hard learning problem. When taking this into account one can conclude that an accuracy gain of 10% (in relation to accuracy levels by plain learning) can be yielded in up to 20% of all cases.especially in cases where there is very little feedback available (namely 5 or 10 examples) an accuracy gain of 5% should be viewed as a major improvement. 5 Conclusion In this article, we have shown, that user models representing a user s interest can be represented as conceptual descriptions. Conceptual user models can be translated into Prolog clauses such that the problem of learning user models becomes a problem of inducing logic programs. We presented a method for coping with sparse feedback and small samples. Together, this forms the novel idea of inducing conceptual user models using the rather uncommon method of ILP. One major advantage of the approach is that scrutability and explainability are guaranteed as a side effect of the chosen method: User models are sets of Prolog clauses which can be easily explained to the user because each body literal corresponds to a class of the taxonomy C. Furthermore, recommendation of results to the user can be explained as well: (dis ) interestingness of a document is determined by carrying out Prolog proofs. Results show relevance of documents with respect to aspects. As a side effect, results are disambiguated: A query for compression yields results which are evaluated with respect to classes information theory, file systems and diving and according aspects. The proofs themselves can be verbalized as well, also taking into account inheritance between classes of the taxonomy. Since the problem of learning a user model can be properly dissected from its surroundings, we evaluated the approach without veiling the facts by way of additional background knowledge. As a consequence, the results obtained can easily be outstripped by approaches which either take into account more information (domain knowldege word occurrences) or impose severe restrictions on the domain (like independence of features). Nevertheless, there remain many open research questions. In this article, we did not explain the underlying (assymetric) distance measure we defined on the taxonomy. It remains to be evaluated, how different distance measure affect the learning results. Another interesting research question is, how so-called redundant hypotheses could be used to infer more accurate hypotheses: During the induction process many hypotheses are generated (consisting of up to 15 literals) which only cover single examples. Regarding compression measures for hypotheses, those clauses are discarded. Still, they carry valuable information: One could imagine, that we collect all literals from all redundant clauses and then construct a new clause using an information gain driven method (see Foil, [10]). References [1] Balabanovic, M. An interface for learning multi-topic user profiles from implicit feedback. In AAAI-98 Workshop on Recommender Systems (Madison, Wisconsin, July 1998). [2] Billsus, D., and Pazzani, M. A hybrid user model for news story classification. Springer, 1999, pp
13 [3] Eilert, S., Mentrup, A., Müller, M. E., Rolf, R., Rollinger, C.-R., Sievertsen, F., and Trenkamp, F. Bikini: User adaptive news classification in the world wide web. In Workshop Machine Learning for User Modeling, 8th Intl. Conf. on User Modeling (2001). [4] Jacobs, N., and Blockeel, H. The learning shell: Automated macro construction. In Proc. 8th Intl. Conf. User Modeling (2001), M. Bauer, P. Gmytrasiewicz, and J. Vassileva, Eds., Springer. [5] Joachims, T., Freitag, D., and Mitchell, T. Webwatcher: A tour guide for the world wide web. In Proceedings of IJCAI 97 (August 1997). [6] Lieberman, H. Letizia: An agent that assists web browsing. In Proc. of the IJCAI 95 (1995), pp [7] Muggleton, S. Inverse entailment and Progol. New Generation Computing, 13 (1995), [8] Muggleton, S., and Raedt, L. D. Inductive logic programming: Theory and methods. Machine Learning 19, 20 (1994), [9] Pazzani, M., Muramatsu, J., and Billsus, D. Syskill & Webert: Identifying interesting Web Sites. In Proc. of the National Conference on Artificial Intelligence (Portland, OR, 1996). [10] Quinlan, J. R. Learning logical definitions from relations. Machine Learning 5, 3 (1990), [11] Schwab, I., Koychev, I., and Kobsa, A. Learning about users from observation. In Adaptive User Interfaces (Menlo Park, California, March 2000), S. Rogers and W. Iba, Eds., no. SS in Technical Report, AAAI Press, pp [12] Widyantoro, D. H., Yin, J., Nasr, M. S. E., Yang, L., Zacchi, A., and Yen, J. Alipes: A swift messenger in cyberspace. In Proc. AAAI Spring Symposium on Intelligent Agents in Cyberspace (Palo Alto, March 1999). 11
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text:
first team / OGCN - OL D -3
Nice preview
Published on the 03 August 2011 à 10:00 by R.B
Despite a dozen departures, the team from the Cote d'Azur has reinforced this season ... They have also changed president... They should avoid the worries of a relegation battle...
15th in 2009-2010, and 17th last season just two points clear of the relegation zone and saving themselves on the final day of the season, the last two years have not been easy for Nice. Fortunately Civelli and his partners made a good run at home by taking 32 of a possible 46 points, or an equivalent of 9th place. Away from home, they finished in 19th place!
Nice are now setting off with other aspirations. Jean-Pierre Rivière became president by putting his hand deep in his pockets. Many faces will no longer be seen out on the pitch, such as Letizi, Ben Saada, Bamogo, Ljuboja, Paisley ...
Arrivals include, the Argentine defender Monzon, the midfielder Meriem, defender K. Gomis ... not to mention the return of loan striker Poté. Not to mention even the return of Faé and Hellebuyck, absent a large part of last season due to injury or health problems. The Marseille player Abriel is announced at Nice as well... while an offensive reinforcement is desired. Let's hope for Nice that they manage to keep the remarkable Anthony Mounier, the best passer of the club with 11 assists and so important with his activity. Mouloungui was the team's top scorer 8 goals.
Eric Roy's men have undergone two training camps during their pre-season preparation, in Catalonia and one another in the Haute-Savoie. They have played four friendly games: a draw against Istres 2-2 (Mounier and Tulasne), success against Guinea 1-0 (Mouloungui) and Udinese 1-0 (Hellebuyck) and a 2-0 defeat against Evian.
For the match against OL, Civelli is suspended.
Note that Nice are unbeaten at home against OL since February 7, 2009, with a 2-2 draw, a 1-0 victory in the Coupe de France and a 3-1 success in the league.

subset: commoncrawl


text:
(P)1996 Inner Visions Worldwide Networks, Inc. All rights reserved.
Acts of Faith is an important spiritual resource for African-Americans and other people of all colors." (Linda Villarosa, Senior Editor,
Essence magazine)
" Acts of Faith is a dazzling collection of meditative statements. It should be a standard work for a long time. Iyanla Vanzant has found a way to help us keep body and soul whole." (Molefi Kete Asante, Professor and Chair, Department of African-American Studies, Temple University)
"ShellBell - London. Loved it!"
I listened to this book on the train as I went to work. Iyanla's voice is so comforting! Her words are powerful, they reached the core of my soul. Although, the deepness and truth of what she was saying made me feel uncomfortable at times. The explanations she gives and the way she reads - soothes. Once the book came to an end, I was sad! LOL! My only negative is: Too short! A beautiful book to inspire and encourage.👌🏾👍 The music and drums webeautiful!😍
"Very Enlightening"
Very Enlightening, Motivational and elegantly presented. With Spiritual guidance that was easy to understand and to utilize.
"Inspirational and concise"
Yes, in order to get a perspective from other, "people of color".
Listening to the advice, "I'm outta here" in relation to bad situations.
I liked the narrators encouraging tone of voice.
I found the topics to be a bit advanced and I would have benefited from more detailed explanations.
"I can replace this over and over again"
I completely enjoy this book. It inspires me, I've listened to it repeatedly. I feel encouraged
"phenominal message"
I really needed to to hear this message and intend to pass it on to my family!
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text:
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BioShock Infinite takes place in 1912, in an American city in the sky.
Yes, in the sky.
Quite a change from the previous two BioShock games, which were in the underwater city named "Rapture." The city of Columbia, however, has sunshine. And clearly, the sky.
Composer Garry Schyman and Creative Director of Irrational Games, Ken Levine, knew the score needed to sound different.
Garry accomplished the changes by using a much smaller ensemble — basically, a small string section and some percussion.
The year 1912 was an interesting time in American classical music, most notably because there wasn't much yet. Many American composers of the time still sounded quite European, although Charles Ives certainly stood out.
Garry considered Ives's influence, but rather turned to other American icons in Stephen Foster, and American folk music in general.
He asked the string players to keep a "fiddle" sound in mind (fiddlers tend to play with less vibrato than traditional classical violinists), and to occasionally play aggressively.
There are so many incredible pieces on this soundtrack, I'm having a hard time deciding which to include here. Let's start with "Elizabeth's Theme":
And, I might as well throw in Booker's theme too, which is called "AD".
Stop me before I give away the entire soundtrack.
Which is difficult, since there is always quite a bit of licensed music in BioShock games. One of my favorite occurrences came during the credits:
Other licensed music includes Chopin's Nocturne in E-flat, Op. 9 No. 2, Scott Joplin's Solace (which is what plays each time the game is loading a new scene) and Mozart's Requiem. Full music list here.
You can hear Garry talk about scoring a 1912 American city in the clouds on the new episode of Top Score from Classical MPR. Episodes are also available on iTunes.


text:
JUNEAU (AP) -- A proposed hydroelectric project for Juneau may get a boost from the governor's proposal to make the state Department of Natural Resources the lead agency for permitting of development projects.
Project developers had feared they would not win the support of the state Department of Fish and Game because the Lake Dorothy hydroelectric project would divert water from streams inhabited by eastern brook trout, a nonnative fish.
Federal agencies have suggested they will not object to building the project in the trout's habitat, said Corry Hildenbrand, president of Lake Dorothy Hydro Inc.
However, relevant state agencies have about a month to suggest terms and conditions of a potential license to the Federal Energy Regulatory Commission.
Fish and Game's Habitat Division has indicated it may stipulate that enough water be left in streams to sustain the trout population, which was introduced in the 1920s or '30s, Hildenbrand said.
''That would make the project uneconomical to the Juneau community,'' he said.
The project, privately financed by Lake Dorothy Hydro Inc., would cost $35 million or more and at the earliest come on line in 2007, Hildenbrand said. Lake Dorothy Hydro is a subsidiary of Alaska Energy Resources Inc., as is Alaska Electric Light and Power, Juneau's electric utility.
The project would tap Lake Dorothy and Bart Lake, which are about 16 miles south of downtown Juneau, to bring 63 ''firm'' gigawatt hours of power to the city annually. Classifying a power output as firm indicates the plant would provide that much power during the driest year on record. The plant's projected firm power output would be a sizable addition to Juneau's energy sources, which generate about 324 firm gigawatt hours per year.
Hildenbrand said the project is essential to ensure continuous clean energy for Juneau, which relies on hydropower from four plants: the AEL&P-owned Salmon Creek, Annex Creek and Gold Creek projects, and the state-owned Snettisham project.
''We're running out of firm hydroelectric energy in Juneau,'' he said. ''If we don't build this project, we'll have to be generating power with fossil fuels.''
Hildenbrand said he has asked Fish and Game to review the policy that requires it to protect nonnative fish as well as native fish.
Clayton Hocks, a fisheries biologist with the Habitat Division, said the fish are not doing any harm and the agency would not change that policy.
''These aren't invasive species. ... This is a self-sustaining population that has been there for quite a while,'' Hocks said. ''We haven't waived (the policy) in the past, but we'll consider all the options and weigh the alternatives.''
He said it was not clear what conditions Fish and Game would stipulate, but that the Federal Energy Regulatory Commission has the ultimate authority.
In his State of the State address last week, Gov. Frank Murkowski said he would give DNR authority over the Habitat Division's permitting function.
''On many occasions, the Habitat Division has been the sole agency opposing and delaying legitimate projects important to the state,'' Murkowski said, citing the Lake Dorothy project.
Hocks disputed that.
''We have not delayed the review at all. It's FERC's review,'' he said.
Murkowski spokesman John Manly said Lake Dorothy is just one of a series of projects the division has held up.
''These are legitimate projects ... and if Habitat is holding up a project to protect a nonnative species that was introduced there, that doesn't seem to me a legitimate thing to do,'' Manly said.
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ALON BLAST UPDATE: Workers released from hospital, operations on at refinery
Published 7:00 pm, Monday, October 26, 2009
Three workers who were injured when an explosion occurred at Alon's Big Spring refinery Monday night have been released from the hospital Tuesday morning, officials said.
The refinery also was operating at its usual planned rates Tuesday and the incident had no effect on production, according to Alon spokesman Blake Lewis.
Paramedics had transported two individuals to Scenic Mountain Medical Center in Big Spring when an explosion in one of the refinery's boilers occurred Monday night, according to Big Spring officials. Another employee was airlifted to an Odessa hosptial, according to Big Spring Fire Department officials. All three were treated and released.
Alon's Company Chief Operating Officer Joseph Israel confirmed "an incident" involving a boiler occurred around 8:45 p.m. Monday.
The incident is under internal company investigation, according to Lewis.


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DECATUR, Tenn. - The Meigs County basketball Tigers needed only one free throw to seal the program's first trip to the state tournament in 27 years.
It took a while, but they finally -- collectively -- got two. And those made the difference in a 71-69 Class A sectional win over South Greene.
The Tigers watched a seven-point lead with 3:49 remaining disappear because of the hot shooting of Nick Fillers and their own inability to hit free throws. The visiting Rebels pulled even in the final minute before Meigs got a free throw apiece from Cam Harris and Bryson Baker.
The hosts sweated out a Jonathan Zavelata 3-point attempt that rattled out at the buzzer, sealing Meigs' first state appearance since 1987.
Their next opponent will be determined by a blind draw Sunday afternoon in Murfreesboro.
"We've worked so hard all year, and it feels great to see all the hard work going towards this to pay off," senior Levi Woods said. "Early on, I let the emotion get to me and I had to settle myself down and pace myself, but we're going to enjoy tonight and then go make a run at a state championship.
"I love Meigs County; I'd do anything for these people here; I love this town. We're going back to the state tournament, and we're making history."
The Tigers (30-4) were led by 23 points from the Mr. Basketball finalist, who needed only 11 to become the school's all-time leading scorer. He eclipsed that mark on a layup with 2:48 remaining in the first quarter and now has 2,374 points.
When he broke the career record, his team was riding the emotions of a packed house and leading 18-5, but the Rebels rallied back with five first-half 3-pointers and briefly took a lead before a 12-2 run by the Tigers gave them a 38-31 advantage going into halftime.
The Tigers built a six-point lead in the second half and seemed to be in control until the final minutes, when they missed five consecutive free throws before Harris hit the second of two. They then added the insurance shot by Baker, and Woods grabbed Zavelata's miss to end the game.
"You hate to see that, having the home crowd behind you in your gym," Meigs coach Sammy Perkinson said of the missed free throws. "Zy [Moore] is a good free-throw shooter, Bryson's a good free-throw shooter, and Levi, but we just missed them and opened the door for South Greene. But we won and we're tickled to death.
"We wasted some energy because the crowd was so into it early. We came out and went so hard and fed off their energy, that it took the energy out of us and they came back. But we held on and we're glad to be going to Murfreesboro; now we just have to work on some free throws."
Matthew Meadows had 18 points on the interior for Meigs, while Baker added nine. Fillers had 27 to lead South Greene (16-18), while Daniel Lowery added 19.
"We had a shot to win," South Greene coach Terry Hoese said. "We came out and played our butts off against a great team; I know why their record is what it is. They've got a great bunch of kids down there and I can't take anything away from there, but I think everybody in here gained respect for us. The kids played hard; we got down a couple times big, but we never gave up -- it's how we've been all year -- and what else can you ask for? We had a shot at the end to win it.
Contact Gene Henley at firstname.lastname@example.com or 423-757-6311. Follow him at twitter.com/genehenleytfp.


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Dairy Queen bringing back fan favorite Blizzard
Published 12:28 pm, Thursday, August 20, 2015
Dairy Queen announced on Thursday it will bring back the Pumpkin Pie Blizzard on Aug. 31.
The company said the treat is so popular that it will be featured as the Blizzard of the Month flavor for two consecutive months.
The Pumpkin Pie Blizzard is a combination of pumpkin pie pieces blended into vanilla soft serve and crowned with whipped topping and nutmeg.
"Pumpkin is the flavor of the fall season, and we were one of the first who began serving up our Pumpkin Pie Blizzard Treat in 1991 long before it became a mainstream cultural phenomenon," said Barry Westrum, executive vice president of Marketing for American Dairy Queen Corporation, in a prepared statement. "Part of the allure is that it's a limited-time-only flavor. Our Pumpkin Pie Blizzard Treat is probably the most unique, one-of-a-kind seasonal offering that fans will find. It's one of the Blizzard Treats that has become part of our brand DNA."


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Lucas Glover held on to win the US Open today, two shots ahead of Phil Mickelson, David Duval and Ricky Barnes. The 29-year-old endured a nervy final round, making four bogeys but, crucially, birdied the par-four 16th to move clear.
Ricky Barnes, who had held the lead since the second day, had a miserable day and shot six-over par - but still finished joint second. Glover, who turned professional in 2001, had only one win on the PGA Tour, in Oklahoma, before this tournament.
Ross Fisher, who at times during the final day looked capable of challenging for the title, tailed off towards the end, bogeying two of the last four holes to finish fifth. Tiger Woods shot one-under par today but was never in contention. He finished tied for sixth with Soren Hansen and Hunter Mahan.
Rori McIlroy shot one of the best rounds of the day, an impressive 68 - only Ian Poulter was better with a three-under 67 - to finish joint 10th.


text: When using vacu-tainers to bleed rabbit ear arteries, we use heparin to increase blood flow and avoid clotting in the syringe. The collected blood does not form a clot; the cellular debris is centrifuged out and serum is diluted and generally used for western blotting. Overall, we haven't had much success generating antibodies. Our boss has raised antibodies in the past, collecting serum thru cardiac puncture, allowing the blood to clot and then removing the clot. He has suggested that clotting is important for getting clean antibodies. Can anyone shed some light on this debate? Is clotting necessary? Does it remove whole blood fractions that might interfere with western blotting? Thanks, paul bucciaglia


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Animal Save Movement Pakistan celebrated Anti Fur Day
--FUR is not FUN , FUR is DEATH--
Multan, 23 November 2012
Mr. Khalid Mahmood Qurashi, President of Animal Save Movement Pakistan, said: "Whenever animals are killed or hunted for their FUR or MEAT their ecosystem gets disturbed. And because of that, the ecosystem of humans is also disturbed. So we are trying to stop the hunting of animals because by killing animals, I think we are going against nature.
Animals deserve our kindness and love. They are not ours to eat, wear, experiment on or use for entertainment and transportation.
Animal Save Movement Pakistan protests strongly against this tyranny and the debacle act of killing any animal for FUR.
Don't use fur, don't support stores that sell FUR and don't contribute as a FUN to celebrities that wear fur.
FUR is not FUN , FUR is DEATH...."
Link: Do the Animals Only in the West Have Rights?
Date: 2012-11-26


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Summer's Bounty Gazpacho
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Author Notes: Gazpacho is a Spanish soup, served chilled - it's a great summertime dish, made with fresh raw vegetables.
It's really simple, toss everything in a food processor, add a little olive oil and BAM! - It's party time!
A great little number for entertaining, you can make it in advance of your soiree - actually, I prefer to serve it after a day or two when the flavours have really developed – it gets better every day, gazpacho soup will last in the fridge, in an airtight container, for a week.
If there's any gazpacho leftover, you can use it as a pasta sauce, stirred into scrambled eggs, as a tomato base on pizza, a salsa with corn chips or as a base for stews and curries. Versatile!
If you don't have gluten free bread you can use almond meal instead, and for those who are not coeliac, use your stale bread or a good sourdough.
Serve it in a bowl drizzled with olive oil, or into a tall glass and serve it neat.
You could get really crazy and serve it with prawns or crayfish tails - I served mine with chorizo, jalapeno and I made some goats cheese balls and rolled them in fresh basil as an accompaniment. —Cle-ann
Serves 4
- 500 grams ripe tomatoes
- 2 garlic cloves
- 1/2 red onion
- 1 small cucumber
- 1 green capsicum
- 1 red capsicum
- 2-3 slices gluten free bread (or wheat bread)
- 3 tablespoons sherry vinegar
- 1/4 cup extra virgin olive oil
- 1/2 cup water
- Salt and freshly ground pepper
- Chorizo
- Jalapeno
- Fresh basil
- Extra virgin olive oil
- Avocado
- Goats cheese
- Prawns (shrimp)
- Crayfish (lobster)
- Pop everything in a food processor and process until smooooth. Add more water if it's too think.
- Cover and refrigerate for at least 2 hours before serving or leave it in the fridge overnight.
- Serve cold with whatever garnishes you like!
More Great Recipes:


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Perhaps nothing defines a classic as much as the Mint Julep. First appearing in print in 1803, three years prior to the first defintion of a cocktail, the julep is complex and versatile, yet so simple at its core. While juleps rained supreme in the 18th and early 19th centuries, they soon gave way to the family of drinks known as "smashes". Faster to prepare and consume, smashes meshed well with the increasing pace of American life.
While early juleps were likely mixed with cognac, the accepted spirit nowadays is bourbon. For the preparation of a proper julep, a few things are needed. Firstly, a traditional silver or pewter julep cup is essential, allowing frost to form on the outside of the cup and keeping the drink icy cold. Secondly, crushed ice is a must. I make my crushed ice by placing it into a canvas lewis bag and crushing it with a mallet. Thirdly, lots of nice fresh mint is needed both as an ingredient and as a very functional garnish.
So let's begin. A traditional julep is made with just four simple ingredients, Spirit, sugar/syrup, ice, and mint. I switch mine up just a bit and use a sweet liqueur in place of the sugar, which adds a little bit of extra flavor to the drink. We start by gently muddling roughly a dozen mint leaves in the bottom of the cup. The goal here is to gently express the mint oils and coat the glass, not to shred the leaves to a pulp. I usually add the liqueur (Apricot in this case) at this time as I like to get the flavors incorporated. Next we will fill our cup with the crushed ice, and pour in our Bourbon. A quick stir is really all that is needed, just enough to get the cup to start frosting on the exterior. Then we will pile more crushed ice on top to give it that adult snow cone look. Then we will garnish with several large sprigs of mint, the more the better in my opinion, and place our straw nice and close, so that in sipping the beverage your nose is treated to the wonderful aromatics of the mint. And there you have it, a perfect summer sipper for those long hot afternoons. Cheers!
The Mint Julep
2 oz Bourbon
1/2 oz Orchard Apricot Liqueur


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I am from Henderson, NV and I've been a Club Horse member for 6 years, 7 months and 13 days
Nicknames: Moose
Age: 23 years old
Gender: Gelding
Breed: Thoroughbred
Height: 17 hands
Color: White with gray mmane
Type of Riding: English, bareback, western.
My Horse's Achievements: Monte won tons of shows. He even won my heart.
My Horse's Favorite Treat: Apples, mint horse nuggets
My Horse's Favorite Things To Do: Be turned out so he can run and discover
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I started working @ the barn where he was being neglected. so I started working with him, and fell in love.
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Accounts Payable Frequently Asked Questions
Q: If I sent in five requests for payments or invoices on the same day, why were they not processed at the same time?
Requests for payments are reviewed and processed based upon payment due dates which will vary with each request. Delays may be caused by the need for additional or corrected information for certain requests.
Q: Why is address a required field on the check request?
Multiple addresses are stored in the Workday system. We need to have the address so that the payment is sent to the correct place.
Q: Why is a New Vendor form required for every new vendor?
The IRS Rules require that we file a Form 1099-Misc Statement for some recipients of miscellaneous income. The New Vendor form helps us determine if a 1099-Misc from needs to be sent to the vendor at year end.
Q: How long does it take to process a check request?
During peak periods it can take up to 7 to 10 business days to process the request.
Q: How do I get a rush check?
Please call Dotti Koulalis to request a rush check. If the request is for a new supplier we must have the New Vendor form before we cut the check. This could add a day to the process. Please see Rush Check policy for more details.
Q: Why do we need to submit an itemized receipt for meals along with the credit card receipt?
The itemized receipt will list beverages. Alcohol charges must be identified and
coded to a/c 7848.
coded to a/c 7848.
Q: How do I get reimbursed for out-of-pocket expenses?
The Check Request must have original receipts, a complete FOPAL, and an authorized signature. For all reimbursements, submit a completed Check Request filling in all the necessary information (the form on-line indicates this information in RED), attached original receipts, complete the FOPAL to be charged and approved by an authorized signer.
Q: Why is it necessary to submit original receipts?
Original receipts are necessary to avoid double payment.
Q: Is a New Vendor form needed for every entity that is not on the system?
Even when we are paying the vendor only one time, it is necessary to have their documentation in our vendor file. When the College Pro-Card is used a new vendor form is NOT needed.
Q: How do I know if a vendor is on the system?
The BANNER form you want to check is FAIVNDH. Search in the vendor ID for the entity. Remember businesses use the entire name in the space for the last name. Individuals are searched with last, first and middle names. The Budget Office Web page has instruction on how to search a vendor.
Q: How do I get reimbursed for Conferences I attended and paid admission?
Complete a Check Request Form filling in all the necessary information (the on-line form indicates this in RED) attached original receipts, complete the FOAPAL (accounting codes) to be charged and approved by an authorized signer.
Q: How do I get reimbursed for Airline tickets I purchased?
If you want to be reimbursed for airfare before the trip you will need to complete a Request for Advance Form attached original receipts, complete the FOAPAL (accounting codes) to be charged and approved by an authorized signer. You will also need to sign the form indicating that you will complete and submit a Travel Expense form within 60 Days of the completed trip.
Q: Can I use a Check Request along with an Invoice?
This is not necessary. All you need to do is put your FOAPAL (accounting codes) on the invoice and get an authorized signer to approve the expenditure.
Q: How do I handle Vendor Credits?
A credit memo is handled as an Invoice. All you need to do is put your FOAPAL on the credit memo and get an authorized signer to approve the expenditure.
Q: Why is it necessary to complete the Authorized Signature every year when there are no changes in the department?
The College must have proper internal controls over financial transactions. Annual updates of authorized signers are an excellent form of internal control.
Q: Why is a separate Authorized Signature form necessary for each of my Orgs/Funds/Grants?
Individual forms are necessary because the organization and processing of this form is sorted by org number.
Q: Who is the Primary Authorized Official on the Authorized Signature form?
The Primary Authorized Official is considered by the Budget Office to be the financial manager ultimately responsible for ensuring that all financial transactions do not exceed the authorized budget.


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FIFA World Cup: It's all about 'Messidependencia' and 'Neymania'
Tostao, the Brazilian legend, advised the Selecao the other day, "Your plan A should be to pass the ball to Neymar. And the Plan B is, pass it to Neymar again!"
Tostao, the Brazilian legend, advised the Selecao the other day, "Your plan A should be to pass the ball to Neymar. And the Plan B is, pass it to Neymar again!"
No Argentine legend has come up with a similar idea for his side. But the players themselves appeared to be aware of their Plan C: pass the ball to Lionel Messi!
Neymar celebrates his goal against Chile. PIC/PTI
"Messidependencia" and "Neymania" have been the words for Argentina and Brazil in the 2014 World Cup.
So far, Neymar has scored four of Brazil's eight goals. Matches decided via tie-breakers are treated as draws by FIFA.
Even the goals are not included in the scorers' account. As a result, the coolest of penalties taken by Neymar against Chile has not been included. Following the all-important and decisive fifth penalty by Neymar, Brazilain head coach Felipao Scolari admitted in the post-match press conference, "He is 22 only, but plays with the maturity of a 35-year old footballer. He is amazing and has been ready since he was 18."
LM 10 rules
LM 10, as Messi is fondly called by his fans, has scored four and played a major part in Angel di Maria's last gasp winner in the first knockout round against Switzerland on Tuesday. If we add the own goal netted by Kolasniac of Bosnia which resulted from a free kick taken by Messi, he has had a hand in six of his team's seven goals.
Over-reliance on a single player could never be explained so easily by any other statistic!
His coach Alejandro Sabella, had no doubt about the 'dependence' issue either. "He is the best footballer of this generation. When you have Lio Messi in the side, you are bound to rely on him. Lio is to us what Diego (Maradona) was to the 1986 Argentina team."


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Léopold Gourmel Extra Age des Epices 20 Carats is a Tres Vieux Cognac, very old. You might want to have this cognac after a good meal, with a good Burgundy wine. This Cognac matures very slowly in oak barrels, a slow pace is important for this product. After 25 years of ageing a cask stops brining more aromas to the cognac - but after 20 years a Cognac reaches a certain peak. This Extra Cognac is pure vintage, no additives, aged in untoasted barrels; and certainly not chill-filtered.
Warning: Last items in stock!
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Tasting notes: Colour: Dark and golden. On the nose really round, some sweet honey hints, here and there leather. In the mouth rather powerful, slow opening - then spicy with pepper notes and coriander. The finish is dominated by ginger and butterscotch.
This cognac house has always relied on natural processes. From growing the grapes to picking, maturing, distilling, aging and bottling them, Gourmel cognac is free of any chemicals, pesticides or additives to enhance color in respect of nature and the final product. The philosophy of the company is to concentrate on quality not quantity, which means that one year the outcome may be higher than in others. This is further shown by the radical decision to produce only pure vintage cognacs, so there is no blending of different years in order to create VS, VSOP or XO cognacs for instance. To go with this authentic approach, the design of Gourmel is simple and modern.


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Golf Lessons with Tru-Trac Technology
TruTrac integrates two very different tracking technologies into one powerful system, giving you the information you need to dramatically improve your game. Ball flight characteristics are accurately calculated utilizing sonic triangulation positioning technologies in conjunction with optical analysis of the club path and club face angle.
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Enjoy the full menu of Food and Spirits from the Library Pub Sports Bar & Grill served to you in your own private room while you golf or hunt! You have your own call button in each room for wait staff to serve you.
Laser Shooting
Shooting Simulators,target practice, virtual hunting, and speed shooting are just a few of the available options with Play Golf 365's Laser Shot Shooting Simulators.
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As a golfer, one can only dream of playing the course at St. Andrews in Scotland or Pebble Beach in California. Don't dream it. Live it! At Play Golf 365, we offer the most unique and precise indoor golf experience at an affordable price. Using cutting edge technology, golfers are able to utilize their own clubs and golf balls (or you can borrow one of our golf sets) while enjoying food and spirits from the Library Pub Sports Bar & Grill. Weather is no issue. Enjoy playing some of the most famous courses from around the world all year long! Play Golf 365 is your headquarters to play indoor virtual golf any day of the year in West Bloomfield, Michigan (near Commerce).
Our technology is state-of-the-art. The experience is dead-on real! Check out our facility and see for yourself. We're proud to offer Tru-Trac golf swing technology that will analyze your golf swing and improve your game. You can even take lessons from one of our golf pros. Or just enjoy a relaxing day of golf with your foursome. We specialize in the most immersive indoor golf experience in Michigan by offering incredible golf courses, private suits with all the sites and sounds of real golf, and delicious food and spirits from the Library Pub Bar and Grill served to you in your private room.
At Play Golf 365, anybody any age can play. We've had kids as young as 5 years old enjoy the experience to teenagers and young adults. Our primary clientele is anywhere from 18 to 85. People always say that golf is a great unifier. It appeals to men and women of all cultures, kids, adults, and the elderly, and everybody can play together and be competitive. You can't say that about basketball, football, or almost any other sport. At Play Golf 365, we've hosted tournaments with parents and grandparents playing against kids during the dead of Winter.
Play Golf 365 is four-season golf at its best. We're ready for you every day of the year. The meaning of indoor virtual golf has been redefined in West Bloomfield. Play Golf 365, your play golf all year destination.
We opened up Play Golf 365 because we love the game of golf and want to play all year long. We want to be able to experience Pebble Beach when it is 12 degrees outside with a foot of snow at our doorstep. If you love the game of golf, we encourage you to come and try Play Golf 365 for an amazing golf experience!
TruGolf TechnologyAt Play Golf 365 we offer the most prestigious golf course library in the Detroit Metro area with 87+ courses currently available. According to Golf Digest, 18 of our courses are ranked in the "Top 100 Courses in America," 23 are ranked in the "Top 100 Courses in the World," and 32 hold televised events. Take our Video Tour.
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