{'fraction_non_alphanumeric': 0.010905125408942203, 'fraction_numerical': 0.0, 'mean_word_length': 4.961038961038961, '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}}
Web usage mining: A review of recent works

Web mining is the application of data mining on web data and web usage mining is an important component of web mining. The goal of web usage mining is to understand the behavior of web site users through the process of data mining of web access data. Knowledge obtained from web usage mining can be used to enhance web design, introduce personalization service and facilitate more effective browsing. This paper presents a review of literature containing latest works done in this field. Our objective is to provide an overview of web usage mining concepts relevant to pattern mining phase of web usage mining process. We provide review of pattern discovery algorithms which utilize association rules, classification and sequential patterns, and since sequential pattern mining is gaining much interest from WUM research community extra emphasis is given to related papers.