{'fraction_non_alphanumeric': 0.014238773274917854, 'fraction_numerical': 0.0, 'mean_word_length': 4.858974358974359, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Survey on Algorithms Predicting Performance of Keyword Queries

Querying using keywords is easily the most widely used form of querying today. Data in database can be easily access with the help of Keyword queries but it may be suffer with low ranking i.e., low precision and/or recall. Responses to keyword searches are often imprecise. It would be beneficial to identify queries having low ranking quality to improve result. Generally in existing systems result is retrieved based on user keyword query, but it may happen that due to low ranking the expected result is discarded. User remains unsatisfied on retrieved result. Hence it is necessary to study different algorithms which help to predict the difficulty level of the keyword query so that alternate query can be used to improve results. This paper provides different algorithms and their comparative study for prediction of difficult keyword queries.