{'fraction_non_alphanumeric': 0.016455696202531647, 'fraction_numerical': 0.0, 'mean_word_length': 4.902985074626866, '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}}
User search goals using classified average precision inference

Information Surfing is one of the vital phenomenon in today's world. Users prefer to surf internet by their queries to clarify their known uncertain information. Search engines do not often bring the user required information and does not fulfill the request completely. Hence it is necessary to infer and mine user specific interest about a topic. Using Internet the user collects the required information through the search engine. To provide the best result by the internet, the user search goal has to be analyzed. The feedback sessions are clustered to find out special user search goals for a query and the Pseudo-documents for it. The user search goals are understand using Classified Average precision (CAP) algorithm.