From "Dango" to "Japanese Cakes": Query Reformulation Models and Patterns
From "Dango" to "Japanese Cakes": Query Reformulation Models and Patterns
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从“团子”到“日本蛋糕”：查询重构模型和模式
DOI：
10.1109/wi-iat.2009.34
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
S. Vigna
中科院分区：
文献类型：
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作者：
P. Boldi;F. Bonchi;C. Castillo;S. Vigna
理解查询重组模式是迈向下一代网络搜索引擎的关键一步：它可以通过预测用户的意图来帮助改善用户的网络搜索体验，从而帮助他们更有效地定位信息。作为这一方向的一步，我们建立了一个准确的模型，将用户查询重写划分为广泛的类别(泛化、特化、纠错或并行移动)，达到92%的准确率。我们应用该模型自动标记两个大型查询日志，创建带注释的查询流图。我们研究了由此产生的重述模式，发现结果与之前在较小的手动标注数据集上所做的研究一致，并发现了新的有趣模式，包括重述类型和主题类别之间的联系。最后，将我们的发现应用于第三个公开可用于研究目的的查询日志，我们证明了我们的重构分类器在查询推荐系统中导致了改进的推荐。
Understanding query reformulation patterns is a key step towards next generation web search engines: it can help improving users' web-search experience by predicting their intent, and thus helping them to locate information more effectively. As a step in this direction, we build an accurate model for classifying user query reformulations into broad classes (generalization, specialization, error correction or parallel move), achieving 92\% accuracy. We apply the model to automatically label two large query logs, creating annotated query-flow graphs. We study the resulting reformulation patterns, finding results consistent with previous studies done on smaller manually annotated datasets, and discovering new interesting patterns, including connections between reformulation types and topical categories. Finally, applying our findings to a third query log that is publicly available for research purposes, we demonstrate that our reformulation classifier leads to improved recommendations in a query recommendation system.
DOI：
10.1145/347090.347176
发表时间：
2000-08
期刊：
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影响因子：
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作者：
Doug Beeferman;A. Berger
通讯作者：
Doug Beeferman;A. Berger