基于词汇集聚的文档相关性计算

赵玉茗; 徐志明; 王晓龙; 朱鲲鹏

doi:10.3724/SP.J.1146.2007.00493

基于词汇集聚的文档相关性计算

doi: 10.3724/SP.J.1146.2007.00493

基金项目:

国家863计划项目(2006AA01Z197)和国家自然科学基金重点项目(60435020)资助课题

计量
- 文章访问数: 2998
- HTML全文浏览量: 130
- PDF下载量: 810
- 被引次数: 0
出版历程
- 收稿日期: 2007-04-02
- 修回日期: 2007-09-28
- 刊出日期: 2008-10-19

Document Relevance Calculation Based on Lexical Cohesion

摘要

摘要: 该文提出了一种基于词汇集聚的文档相关性计算方法。该方法以知网为知识库，依靠词汇集聚，将文档中存在语义关联的词语连接成链，计算各条词汇链权重，以词汇链为元素对文档进行形式化表示，最终利用文档的此种形式化表示进行相关匹配计算。该文在中图法分类的语料上，开展了文档相关性计算的实验，准确率达到了85.4%。实验结果表明，该方法在一定程度上描述了文档的语义信息，将文档间的相关比较从字符或词层面的直接比较提升到近似概念层次的比较，是一种计算文档间相关性的有效方法。
- 词汇集聚 /
- 文档相关性 /
- 向量空间模型
Abstract: A new document relevance calculating method based on lexical cohesion is presented in this paper. The main principle is: documents are formalized with lexicon chains which are constructed by extracting semantic-relative word clusters according to the lexicon cohesion principle under the help of semantic dictionary HowNet; then weight of each lexical chain is evaluated; finally relevance of documents is calculated with their representations. Experiments are conducted on corpus of Chinese Library Classification, and precision about 85.4% is achieved. The experimental results show that the method describes the semantic feature of documents to a certain extent, and it is an effective method for relevance calculating of documents.
- L /
- e

HTML全文

参考文献(1)

[1] Cuadra C A and Katter R V. Experimental studies of relevance judgments: final report. Vol. 1: Project Summary, NSF Report No.TM-3520/001/00, System Development Corporation, 1967. Rees A M and Schultz D G. A field experimental approach to the study of relevance assessments in relation to document searching. Vol. 1: Final Report, NSF Contract No. C-423, 1967. [2] Saracevic T. The concept of relevance in information science: a historical review, In T. Saracevic ed. Introduction to Information Science. New York. 1970: 111-151. [3] Cooper W S. A definition of relevance for information retrieval[J].Information Storage and Retrieval.1971, 7(1):19-37 [4] Cooper W S. On selecting a measure of retrieval effectiveness, part 1, The subjective philosophy of evaluation[J].Journal of the American Society for Information Science.1973, 24(2):87-100 [5] MacMullin S E and Taylor R S. Problem dimensions and information traits[J].The Information Society.1984, 3(1):91-111 [6] Taylor R S. Value-Added Processes in Information Systems. Norwood, NJ: Ablex Publishing Corporation, 1986. [7] Belkin N J, Oddy R N, and Brooks H M. Ask for information retrieval[J].Journal of Documentation.1982, 38(2):61-71 [8] Mizzaro S. How many relevances in information retrieval?. Interacting with computers. Elsevier, The Netherlands, 1998, 10(3): 305-322. [9] 孙建军, 成颖. 信息检索技术. 第1版, 北京: 科学出版社, 2004, 10: 341-377.Sun Jian-jun and Cheng Ying. Information Retrieval Technology. Beijing: Science Press, 2004, 10: 341-377. [10] Hasan M and Halliday R. Cohesion in English, London: Longman, 1976: 1-392. [11] Hoey M. Patterns of Lexis in Text. Oxford: Oxford University Press, 1991: 45-47. [12] Morris J and Hirst G. Lexical cohesion computed by thesaural relations as an indicator of the structure of the text. Computational Linguistics, 1991, 17(1): 21-48. [13] 尤文建, 李绍滋, 李堂秋. 基于词汇链的文本过滤模型. 计算机应用研究, 2003, 9: 32-35.You Wen-jian, Li Shao-zi, and Li Tang-qiu. A text filtering module based on lexical chain. Application Research of Computers, 2003, 9: 32-35.

施引文献

资源附件(0)

访问统计