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Knowledge Evolution Research on Enterprise Human Resources Management Based on Knowledge Mapping

In this paper, the knowledge mapping based enterprise knowledge system is analyzed objectively, and some problems and deficiencies in the current enterprise knowledge system are studied and found. Meanwhile, we make most use of more effective human resources implementation plan and human resources management to achieve optimization and improvement on the current enterprise knowledge system. Thus, we come up with KM-HS knowledge evolution models of enterprises based on human resources in order to provide construction of enterprise knowledge system with detailed methods. On this basis, the paper emphasizes on knowledge acquisition, mapping construction, knowledge mapping benchmark analysis and human resources implementation plan to offer methods and references for enterprises relying on human resources management knowledge evolution of knowledge mapping.


Introduction
Knowledge mapping is a kind of technical method that uses a graphic model to describe the connection relationship between knowledge and everything modelling in the world. A knowledge mapping consists of nodes and edges, which can be regarded as an entity or an abstract concept, and edges represent attributes of entities or relationships between entities.The complex relationships between things and concepts can be identified, discovered and inferred from the data by using the knowledge mapping. However, the construction of enterprise knowledge system is the development progress of enterprise internal knowledge from scratch to existence, from weak to strong, from mutual encouragement to close integration, from disorder to order, which is essentially the evolution and development process of enterprise knowledge.
At present, the enterprise mostly utilizes the data base to store data and information in the progress of human resources knowledge management. In the meantime, the enterprise sorts out data and information by tree structure and search for and apply knowledge via some certain tools with searching functions. At this point, we can generally search for some knowledge we needed, but some searching problems have existed such as unsystematic searching engine, unprocessed searching engine and moment by moment system update. Therefore, we are supposed to research deeply on methods and tools for human resources knowledge management. In the course of the research, the knowledge mapping will be applied and gradually innovated so as to play more important role in the practice.

Research on Evolution Manner
In the era of knowledge-driven economy, the update of knowledge and technology changes with each passing day, which means its update, evolution and iteration has conducted at a very fast pace. K.R.Popper believed that selection for scientifictheory was just a progress of natural selection which waslike Darwin's natural selection. The selection of scientific theories is also a process of natural selection,which can eliminate the fake and retain the truth through continuous practice in the life [1]. K.R.Popperapplied the theory of biological evolution to explain the process of scientific development and illuminate how scientific knowledge is reasonably evolved in the process of human understanding and exploring nature, which is the theory of knowledge evolution.Ander thought that knowledge evolution was a process in which knowledge was constantly improved and developed by constantly refreshment and replacement [2]. Tang deemed that scientific development was similar to biological evolution, and the evolution process of scientific knowledge was a process in which errors were continuously found, errors were corrected, and corrected knowledge was temporarily retained [3].In general, knowledge evolution is the process of replacing old knowledge with new knowledge and old thoughts with new thoughts.
Geroski mentioned that desire for human to learn knowledge was extremely strong and instinctive [4]. Senge thought that people can improve its capability of acknowledging relationships among everything in the world and understanding the world through learning [5]. Hendrik pointed that knowledge group made great impact on knowledge evolution and also deemed that knowledge group should be assigned and cooperated in accordance with the acknowledged knowledge difference by knowledge individuals so as to boost knowledge development [6].
For the enterprise, enterprise knowledge system construction simply relied on natural knowledge evolution manners such as knowledge individual evolution and knowledge group mutual learning is a long-term progress in which enterprise technology introduction and self-dependent innovation connect together. From the angle of knowledge mapping, enterprise knowledge evolution mainly shows that points, numbers of knowledge groups, connection points, numbers of relationships, densitiesof knowledge mapping which represents enterprise knowledge system have increased and the knowledge mapping structure has turned into be more orderly, and will further represent some professional knowledge fields that more close to all-fields knowledge mapping.

Human Resources Impacting on Knowledge Evolution
Establishing human resources management system in the center of knowledge and knowledge personnel has become a new tendency, which regards knowledge management more important part of enterprise human resources management and its aim to improve enterprise management efficiency and innovation level through discovering, combing, innovating knowledge, transmitting and sharing knowledge. Human resources management makes direct or indirect impact on enterprise knowledge system construction, etc. by the manners of achieving enterprise external knowledge introduction and motivating enterprise internal knowledge evolution. Modes on human resources management mainly include recruitment, training, position allocation, remuneration and performance index, etc. Meanwhile, human resources management can bring in knowledge individuals from enterprise externalities via combing and use these modes. For example, recruitment can achieve that knowledge individuals of enterprise internal knowledge obtain new external research knowledge; and training can motivate enterprise self-learning capability of the knowledge individuals of enterprise internal knowledge so as to enhance communication among the knowledge individuals of enterprise internal knowledge; utilize position allocation or remuneration for motivation.

Chart 1 Completing Enterprise Knowledge Evolution Through Increasing Numbers of Nodes
From the angle of knowledge mapping, we apply to human resources management to increase numbers of nodes in the knowledge mapping and to achieve enterprise knowledge evolution. For instance, we compare knowledge mapping of enterprise knowledge system with all-fields knowledge mapping to discover shortages in knowledge contents of enterprise knowledge system. As chart 1 showed, if, chart 1 (b) represents knowledge mapping of one certain enterprise in which we can easily find that enterprise knowledge system divides into two isolated groups with dispersed structure and efficient combination between contents. However, we can acknowledge that the cause for that problem is the loss of key node A in the enterprise knowledge mapping through comparison with all-fields knowledge mapping 1 (a).At this point, we are able to introduce new knowledge node A in the enterprise internalities to achieve converting enterprise knowledge mapping into all-fields knowledge mapping to further complete enterprise internal knowledge evolution.

Chart 2 Accomplishing Knowledge Communication Through Position Allocation
In addition, from the angle of knowledge mapping, enterprise knowledge evolution can also be achieved by improving relationships among enterprise internal knowledge nodes. We mainly depend on enterprise knowledge management strategy implementation with enhancing internal knowledge share and communication of enterprise personnel to finish this target. Specific human resources management basically counts on such management modes as position allocation management, performance index implementation and remuneration management to motivate knowledge communication between personnel and departments. As Chart 2 showed, A and B represent respectively two business departments and internal knowledge od A and B combine together well in the assumption Chart 2 (a). But through comparison with all-fields knowledge mapping, we can understand that A and B two departments only achieve valid knowledge combination that will be more perfect knowledge system. Under such circumstances, human resources management may accomplish

KM-HS Knowledge Evolution Model Construction
KM-HS knowledge evolution model to optimize the enterprise knowledge system as the aim and to regard enterprise knowledge mapping as the analysis object by using social network analysis method. The method analyzes some indicators such as points, connection points, numbers of relationships, density, knowledge groups to find the existing problems in the enterprise knowledge mapping and propose the corresponding human resource management plan.
As Chart 4 showed, KM-HS enterprise knowledge evolution model basically makes benchmark comparison between enterprise internal knowledge and enterprise external knowledge to seek and improve problems in order for achieving circulation and evolution of enterprise internal knowledge. The model initiates and counts on enterprise knowledge system to construct enterprise knowledge mapping, and discovers shortages in the enterprise knowledge mapping via benchmark comparison with external knowledge of all-fields knowledge mapping. We put forward some advices on enterprise knowledge system construction to solve those shortages in the knowledge mapping.

Knowledge Analysis Progress Based on KM-HS Knowledge Evolution Models
KM-HS knowledge evolution models frequently start from enterprise internal knowledge and finally reflect on self-enterprise internal knowledge system to form a cyclic process. Detailed analysis progress is divided into 5 steps as follows: 1) Knowledge Acquisition; 2) External and internal knowledge mapping construction of enterprise; 3) Knowledge mapping benchmark analysis to discover shortages; 4) Putting forward advices on enterprise knowledge system construction; 5) Setting and Implementing Human Resources Plan.

Knowledge Acquisition
Enterprise knowledge include explicit and tacit knowledge. Explicit knowledge refers to those of clear and explicit knowledge that can be clearly expressed by others and can be easily disseminated and communicated through summary, reports, manuals, books and journals, articles, electronic literature and video data.Tacit knowledge means that the knowledge of experience, ideals and beliefs that are hidden in the human brain and not visible to others.Therefore, in KM-HS models analysis, papers can more comprehensively reflect on the knowledge composition of enterprises than patents. Thus, data from CNKI journalsare also used for the source of enterprise knowledge acquisition.

Knowledge Mapping Construction
Knowledge mapping construction basically counts on co-occurrence analysis relationship. Main elements of co-occurrence analysis methods contain co-word, co-citation, cooperation, etc. So far, there are four existing common co-occurrence analysis methods such as co-word comparison, literature co-citation, writers co-citation and cooperation. Co-word analysis is more suitable to expose knowledge system construction of enterprise. Therefore, We usually regard co-word analysis as a primary method for knowledge mapping construction of enterprise in KM-HS knowledge evolution models.
Operation of co-word analysis method mainly embodied that all literature key words in a group of literature collection to make comparison to count up frequencies appearing in the group of literature collection. And then, we will build co-occurrence matrix and mapping in order to mirror affinitydisaffinity relationship of research contents between literatures. Co-word analysis generally utilizes three indexes such as tolerance index, proximity index and equivalence index to balance co-word connection.