{'fraction_non_alphanumeric': 0.012515644555694618, 'fraction_numerical': 0.0, 'mean_word_length': 4.673758865248227, '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}}
Sequential web page access analysis using web log

The world wide web contains an increasing amount of websites which in turn contain an increasing number of web pages. When a client views a new website, it has to go through a huge number of web pages to confront their requirements. Web usage scooping is the process of clipping useful information from server logs. Hence, this research reviews the process of discovering sequential patterns of web files by applying genetic method. This method can be applied to analyse the recent visitor’s trend and lead to the creation of repeated and most visited pages. The purpose of using a genetic algorithm is to make evolution approach for knowledge extraction and it is also simpler to implement. It can be implemented in several real time applications.