{'fraction_non_alphanumeric': 0.02345215759849906, 'fraction_numerical': 0.0028142589118198874, 'mean_word_length': 5.427710843373494, '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 PRIMER ON THE WEB INFORMATION RETRIEVAL PARADIGM

The unabated growth of the Web and the increasing expectation placed by the user on the search engine to anticipate and infer his/her information needs and provide relevant results has fostered the development of the field of Web Information Retrieval (Web IR). The recent surveys claim that 85% of internet users use search engines and search services to find specific information [1]. The same surveys, however, show that users are not satisfied with the performance of the current generation search engines. The slow retrieval speed, poor quality of retrieved results, handling a huge quantity of information, addressing subjective & time-varying search needs, finding fresh information and dealing with poor quality queries are commonly cited glitches. This paper expounds the Web Information Retrieval paradigm, a variant of classical Information Retrieval, by illustrating its basics, the components, model categories, tools, tasks and the performance measures that quantify the quality of retrieval results.