Query-Task映射

Michael Völske, Ehsan Fatehifar, Benno Stein, Matthias Hagen
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引用次数: 7

摘要

最近一些基于任务的搜索研究旨在将查询日志拆分为同一任务或信息需求的查询集。我们解决了自然的下一步:将当前提交的查询映射到已经任务分割日志中的适当任务。例如,这种查询任务映射可以增强查询建议——映射的呈现效率,除了准确性之外,这是一个关键目标。我们的主要贡献是三个大型基准数据集和四种查询任务映射方法的初步实验:(1)基于trie的方法,(2)MinHash~LSH, (3) Word2Vec设置中的字移动距离,以及(4)基于倒排索引的方法。实验表明,基于倒排索引的方法快速准确地形成了一个强基线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Query-Task Mapping
Several recent task-based search studies aim at splitting query logs into sets of queries for the same task or information need. We address the natural next step: mapping a currently submitted query to an appropriate task in an already task-split log. This query-task mapping can, for instance, enhance query suggestions---rendering efficiency of the mapping, besides accuracy, a key objective. Our main contributions are three large benchmark datasets and preliminary experiments with four query-task mapping approaches: (1) a Trie-based approach, (2) MinHash~LSH, (3) word movers distance in a Word2Vec setup, and (4) an inverted index-based approach. The experiments show that the fast and accurate inverted index-based method forms a strong baseline.
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