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山东大学学报（理学版） ›› 2016, Vol. 51 ›› Issue (3): 77-85.doi: 10.6040/j.issn.1671-9352.1.2015.070

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微博城市投诉文本中的地理位置实体识别

孙赫1,2,李淑琴2,吕学强1,2*,刘克会3,4   

  1. 1. 网络文化与数字传播北京市重点实验室, 北京 100101; 2. 北京信息科技大学计算机学院, 北京 100101;3. 北京理工大学管理与经济学院, 北京 100081;4.北京城市系统工程研究中心, 北京 100035
  • 收稿日期:2015-11-14 出版日期:2016-03-20 发布日期:2016-04-07
  • 通讯作者: 吕学强(1970— ),男,教授,研究方向为中文信息处理、多媒体信息处理.E-mail:lv.xueqiang@trs.com.cn E-mail:s-hehe@126.com
  • 作者简介:孙赫(1987— ),男,硕士研究生,研究方向为中文信息处理.E-mail:s-hehe@126.com
  • 基金资助:
    国家自然科学基金资助项目(61271304);北京市属高等学校创新团队建设与教师职业发展计划项目(IDHT20130519);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(KZ201311232037);北京市财政项目(PXM2014-17825-000005);网络文化与数字传播北京市重点实验室开放课题项目(ICDD2015)

Recognition of geographical entity in city complaints of Micro-blog

SUN He1,2, LI Shu-qin2, L(¨overU)Xue-qiang1,2*, LIU Ke-hui3,4   

  1. 1. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing 100101, China;
    2. College of Computer, Beijing Information Science and Technology University, Beijing 100101, China;
    3. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;
    4. Beijing Research Center of Urban Systems Engineering, Beijing 100035, China
  • Received:2015-11-14 Online:2016-03-20 Published:2016-04-07

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摘要： 微博投诉文本中地理位置实体通常存在结构复杂,长度较长,描述较详细的特点。通过对投诉微博文本的分析,提出了地理位置实体自动识别的方法。该方法首先利用特征资源库对微博进行特征标注,使用条件随机场(conditional random fields, CRF)模型识别地理位置实体。其次根据微博和地理位置实体的特点,对CRF识别后的数据进行二次标注。最后利用微博规则库对识别结果进行补召,修正地理位置实体,最终实现地理位置实体的识别。实验结果表明该方法有显著效果,F值可达到85.52%。

关键词: 地理位置实体识别, 微博规则库, CRF, 微博城市投诉文本

Abstract: Geographical entity in city complaints of Micro-blog has usually has the characteristics of complicated structure, long length, the location of detailed description. This paper presents an automatic method to recognize geographical entities through analysis complaints of Micro-blog. First of all, the method utilizes the feature repository of Micro-blog to mark features, using the conditional random field(CRF)model to identify the geographical entities. Second, according to the characteristics of Micro-blog and geographical entity, recognized data by CRF is second marked. Third, rule bank is utilized to supplementing the recognition result and correcting geographical entities, consequently, the recognition of geographical entities are implemented. At last, Experimental results on the proposed method proved to have an F-Score of 85.52%.

Key words: city complaints of Micro-blog, rule bank of Micro-blog, recognition of geographical entity, CRF

中图分类号: 

  • TP393
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