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山东大学学报（理学版） ›› 2017, Vol. 52 ›› Issue (9): 13-18.doi: 10.6040/j.issn.1671-9352.0.2016.107

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一种查询意图边界检测方法研究

王凯,洪宇*,邱盈盈,王剑,姚建民,周国栋   

  1. 苏州大学计算机科学与技术学院, 江苏 苏州 215006
  • 收稿日期:2016-11-25 出版日期:2017-09-20 发布日期:2017-09-15
  • 作者简介:王凯(1990— ),男,硕士,研究方向为信息检索和信息抽取. E-mail: wangkainlp@gmail.com*通迅作者: 洪宇(1978— ),男,副教授,研究方向为话题检测、信息检索和信息抽取. E-mail: tianxianer@gmail.com
  • 基金资助:
    国家自然科学基金资助项目(61672368,61672367,61373097,61331011)

Study on boundary detection of users query intents

WANG Kai, HONG Yu*, QIU Ying-ying, WANG Jian, YAO Jian-min, ZHOU Guo-dong   

  1. School of Computer Science and Technology Soochow University, Suzhou 215006, Jiangsu, China
  • Received:2016-11-25 Online:2017-09-20 Published:2017-09-15

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摘要： 针对一个特定的查询意图,用户往往需要提交多次查询请求。有效地识别连续查询请求之间的意图变化边界,能够帮助检索系统更好地理解用户完整查询意图,以提高查询推荐及查询扩展的效果,并能够辅助个性化检索中用户模型的建立。在充分分析前人研究的有效特征基础上,提出了基于主题相似度检测意图边界的方法,并在SVM及CRF模型上都取得一定的提升。实验结果显示,所提方法的最优性能比Baseline系统F值提高了2%。

关键词: 查询意图, 边界检测, 信息检索

Abstract: In generally, several query requests will be submit by user to capture specific query intent. It is quite a meaningful work to detect the boundary among continuous query requests effectively, which could help search engine to understand the query intent completely. Moreover, identifying the integrated query intent is considerable helpful to query suggestion, query expansion and the construction of user profile. On the basis of fully analyzing the features mentioned from previous research, this paper proposed topic distribution-based similarity and this similarity is effective with SVM model and CRF model. The results show that, with topic distribution similarity, F-measure is improved by 2% in comparison to the baseline system.

Key words: information retrieval, boundary detection, query intent

中图分类号: 

  • TP391
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