{'fraction_non_alphanumeric': 0.01520086862106406, 'fraction_numerical': 0.0, 'mean_word_length': 4.726708074534161, '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}}
A Brief Survey on Meta-Heuristic Approaches for Web Document Clustering

Internet is a gigantic information resource, which is growing rapidly as more and more data are being added to the World Wide Web. It is now becoming ever harder to search useful information from the web. It has been also been found that HTML tags which have particular meanings could be used to enhance the performance of IR system. Still, the bulk of data on the web is speedily growing. Clustering can be used to play a key role in organizing such a bulky amount of documents into groups. However, due to restrictions in prevailing clustering techniques, scientists started to use meta-heuristic algorithms for the document clustering problem. This paper provides a brief survey of the available literature on a web search in which HTML tags have been used in information retrieval and Meta-heuristics approaches used in web document clustering.