{'fraction_non_alphanumeric': 0.012239902080783354, 'fraction_numerical': 0.0036719706242350062, 'mean_word_length': 5.014705882352941, '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}}
Assigning documents to master sites in distributed search

An appealing solution to scale Web search with the growth of the Internet is the use of distributed architectures. Distributed search engines rely on multiple sites deployed in distant regions across the world, where each site is specialized to serve queries issued by the users of its region. This paper investigates the problem of assigning each document to a master site. We show that by leveraging similarities between a document and the activity of the users, we can accurately detect which site is the most relevant to place a document. We conduct various experiments using two document assignment approaches, showing performance improvements of up to 20.8% over a baseline technique which assigns the documents to search sites based on their language.