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Modeling Transactional Queries via Templates

机译:通过模板建模交易查询

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Search queries have been roughly classified into three categories - navigational, informational and transactional. The latter group includes queries that aim to perform some Web-mediated task, often by interacting with parameterized Web services. In order to assist users in completing tasks online, one of the first building blocks is identifying whether and which transactional use-case is associated with each query. This paper describes a framework and an algorithm for automatically generating compact representations of queries associated with transactional use cases. We mine search click logs for queries that lead to clicks on pages associated with a use-case, generalize the set of mined queries into templates by replacing query terms with taxonomy categories, and eliminate redundancies. This approach allows associating the use-case with queries unseen in the log sample, while keeping a concise model. Our methodology allows a business owner to select an appropriate operating point that balances the tradeoff between precision and recall. We report the results of an offline evaluation of our framework on three transactional domains, and demonstrate the viability of the approach.
机译:搜索查询大致分为三类-导航,信息和事务。后一组包括旨在通过与参数化Web服务进行交互来执行某些Web介导任务的查询。为了帮助用户在线完成任务,第一个构建块是确定每个查询是否与哪个事务用例相关联。本文介绍了一种框架和一种算法,用于自动生成与事务用例关联的查询的紧凑表示。我们对搜索点击日志进行挖掘,以获取导致与用例相关联的页面获得点击的查询,通过将查询字词替换为分类类别将挖掘的查询集概括为模板,并消除冗余。这种方法允许将用例与日志样本中未发现的查询相关联,同时保持简洁的模型。我们的方法允许企业所有者选择合适的工作点,以平衡精度和召回率之间的权衡。我们报告了对三个交易领域的框架进行离线评估的结果,并证明了该方法的可行性。

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