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山东大学学报(理学版) ›› 2017, Vol. 52 ›› Issue (9): 26-34.doi: 10.6040/j.issn.1671-9352.1.2016.047

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异质搜索环境下的用户偏好性预测方法研究

张帆,罗成,刘奕群,张敏,马少平   

  1. 清华大学计算机系, 智能技术与系统国家重点实验室, 北京 100084
  • 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:张帆(1994— ),男,硕士研究生,研究方向为信息检索. E-mail:frankyzf94@gmail.com
  • 基金资助:
    国家自然科学基金资助项目(61622208,61532011,61472206);国家重点基础研究发展计划(973计划)资助项目(2015CB358700)

User preference prediction in heterogeneous search environment

ZHANG Fan, LUO Cheng, LIU Yi-qun, ZHANG Min, MA Shao-ping   

  1. State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
  • Received:2016-11-25 Online:2017-09-20 Published:2017-09-15

摘要: 提出了一系列基于搜索结果页面的特征用于学习分类器,自动预测用户的偏好性,并尝试将预测模型与用户实验结合起来。实验结果表明,尽管异质环境下搜索结果页面有着丰富的信息,但仅基于搜索结果页面的展现形式难以对用户的偏好性做出可靠的预测。

关键词: 异质环境, 用户偏好性, 自动预测

Abstract: We propose a series of SERP based features for learning classifiers to automatically predict user preference and we attempt to combine prediction model and user study. The experimental results show that it is difficult to make reliable prediction for user preference only based on appearances of SERPs despite the abundant information of SERPs in heterogeneous environment.

Key words: heterogeneous environments, user preferences, automatic prediction

中图分类号: 

  • TP391
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