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现代图书情报技术  2015, Vol. 31 Issue (6): 49-56    DOI: 10.11925/infotech.1003-3513.2015.06.08
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
搜索日志中命名实体识别
任育伟1, 吕学强1, 李卓2, 徐丽萍2
1 北京信息科技大学网络文化与数字传播北京市重点实验室 北京 100101;
2 北京城市系统工程研究中心 北京 100089
Named Entity Recognition from Search Log
Ren Yuwei1, Lv Xueqiang1, Li Zhuo2, Xu Liping2
1 Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China;
2 Beijing Research Center of Urban System Engineering, Beijing 100089, China
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摘要 

目的】搜索日志中命名实体识别对于优化搜索意图, 提高搜索引擎服务质量存在重要意义。【方法】利用种子命名实体和模板匹配原则抽取候选命名实体并聚类, 聚类后进行候选命名实体识别特征抽取, 包括频次、不同模板数、模板权重特征。融合这些特征构造命名实体识别权重计算公式, 并合理调整特征影响参数。【结果】对根据权重提取的命名实体进行标注和统计, 发现P@500值平均达到75%左右, 比Pa?ca方法高出7%。【局限】对模板敏感性弱的命名实体不能精确抽取。【结论】通过计算该方法抽取结果指标P@N值, 并和其他方法抽取结果指标进行比较, 证明该方法的有效性。

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任育伟
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关键词 搜索日志模板权重类K-means聚类特征权重种子命名实体    
Abstract

[Objective] Recognizing the named entity in the search logs provides great value and significance for enhancing the quality of search service. [Methods] Extract candidate named entity by using seed named entity and template matching principle. After clustering the candidate named entity, extracte the recognition feature of candidate named entity, including the frequency, the number of different templates and template weight. Fuse these features to construct calculation formula of named entity recognition weight and adjust feature influencing parameters reasonably. [Results] By marking and counting the extracted named entity, the average value of P@500 reaches 75% and is higher than Pa?ca method by 7%. [Limitations] The named entity which has weak sensitivity for the template can not be extracted correctly. [Conclusions] Calculate the P@N index value of the extracted results, which shows the effectiveness of this method.

Key wordsSearch log    Template weight    K-means clustering    Feature weight    Seed named entity
收稿日期: 2014-10-28     
:  TP391  
基金资助:

本文系国家自然科学基金项目“基于本体的专利自动标引研究”(项目编号:61271304)和北京市教委科技发展计划重点项目暨北京市自然科学基金B类重点项目“面向领域的互联网多模态信息精准搜索方法研究”(项目编号:KZ201311232037)的研究成果之一。

通讯作者: 任育伟, ORCID: 0000-0002-0236-476X, E-mail: wisdomryw@sina.cn。     E-mail: wisdomryw@sina.cn
作者简介: 作者贡献声明: 吕学强: 提出研究命题; 任育伟: 提出研究思路, 设计研究方案, 完成实验, 分析数据, 起草论文; 李卓: 修改论文; 徐丽萍: 论文最终版本修订。
引用本文:   
任育伟, 吕学强, 李卓, 徐丽萍. 搜索日志中命名实体识别[J]. 现代图书情报技术, 2015, 31(6): 49-56.
Ren Yuwei, Lv Xueqiang, Li Zhuo, Xu Liping. Named Entity Recognition from Search Log. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2015.06.08.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2015.06.08

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