Generating High-Quality Query Suggestion Candidates for Task-Based Search
Generating High-Quality Query Suggestion Candidates for Task-Based Search
复制标题
为基于任务的搜索生成高质量的查询建议候选
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
K. Balog
中科院分区：
文献类型：
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作者：
Heng Ding;Shuo Zhang;Darío Garigliotti;K. Balog
我们解决为基于任务的搜索生成查询建议的任务。当前的技术水平在很大程度上依赖于主要搜索引擎提供的建议。在本文中，我们在不依赖搜索引擎的情况下解决了该任务。具体来说，我们关注两阶段管道方法的第一步，该方法致力于生成查询建议候选。我们提出了三种生成候选建议的方法并将其应用于多个信息源。使用专门构建的测试集，我们发现这些方法能够生成高质量的候选建议。
We address the task of generating query suggestions for task-based search. The current state of the art relies heavily on suggestions provided by a major search engine. In this paper, we solve the task without reliance on search engines. Specifically, we focus on the first step of a two-stage pipeline approach, which is dedicated to the generation of query suggestion candidates. We present three methods for generating candidate suggestions and apply them on multiple information sources. Using a purpose-built test collection, we find that these methods are able to generate high-quality suggestion candidates.