{'fraction_non_alphanumeric': 0.008486562942008486, 'fraction_numerical': 0.0, 'mean_word_length': 4.488372093023256, '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}}
Building a query log via crowdsourcing

A query log is a key asset in a commercial search engine. Everyday millions of users rely on search engines to find information on the Web by entering a few keywords on a simple search interface. Those queries represent a subset of user behavioral data which is used to mine and discover search patterns for improving the overall end user experience. While queries are very useful, it is not always possible to capture precisely what the user was looking for when the intent is not that clear. We explore a different alternative based on human computation to gather a bit more information from users and show the type of query log that would be possible to construct.