{'fraction_non_alphanumeric': 0.029985007496251874, 'fraction_numerical': 0.0, 'mean_word_length': 5.30188679245283, '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}}
Time-Aware Diversified Query Suggestion

In this paper, we study query suggestion diversi cation for time- aware queries, where query suggestions are diversified from multiple dimensions (e.g., topic and time). More precisely, we introduce the method of Time-aware Diversified Query Suggestion (TDQS) which ensures that the generated suggested queries indicate possible time points in which a searcher who issued the original query may be interested. Preliminary experiments on AOL query log demonstrate that our proposed method can significantly improve the diversity and relevance e ectiveness for time-aware queries in comparison with two state-of-the-art methods.