{'fraction_non_alphanumeric': 0.012403100775193798, 'fraction_numerical': 0.0031007751937984496, 'mean_word_length': 5.271844660194175, '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}}
Automatic Term Reweighting for Query Expansion

Query expansion is used to overcome the vocabulary mismatch between the documents and queries, but it can lead to query drift. We propose an automatic term reweighting strategy for BM25 ranking functions. Using expansion terms obtained from general purpose thesauri, we found that reweighting through term frequency merging is more effective than standard query expansion. Instead of appending the new terms directly to the original query, we merge the term frequencies with the original query term. This reduces the impact of spurious expansion terms being over represented in the modified query.