将查询映射到问题:了解用户的信息需求

Yunjun Gao, Lu Chen, Rui Li, Gang Chen
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引用次数: 2

摘要

在本文中,我们首次研究了基于社区的问答(CQA)网站上关键字查询与问题的映射问题。将一般的网络查询映射到问题,使搜索引擎不仅可以发现关键字查询背后明确的、特定的信息需求(问题),还可以找到高质量的信息(答案)来回答关键字查询。为了将查询映射到问题,我们提出了一种包含三个步骤的排序算法:候选问题选择、候选问题排序和候选问题分组。对60条商业搜索日志的初步实验结果表明,该方法可以有效地找到明确捕获用户信息需求的问题。
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Mapping queries to questions: towards understanding users' information needs
In this paper, for the first time, we study the problem of mapping keyword queries to questions on community-based question answering (CQA) sites. Mapping general web queries to questions enables search engines not only to discover explicit and specific information needs (questions) behind keywords queries, but also to find high quality information (answers) for answering keyword queries. In order to map queries to questions, we propose a ranking algorithm containing three steps: Candidate Question Selection, Candidate Question Ranking, and Candidate Question Grouping. Preliminary experimental results using 60 queries from search logs of a commercial engine show that the presented approach can efficiently find the questions which capture user's information needs explicitly.
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