（北京师范大学管理学院 北京 100875）

作为大规模的语义知识资源库，Ontology在信息处理中具有重要的作用。但是，如何有效地构建Ontology却是一个重要的问题。对于自动构建Ontology的过程来说，首要的问题就是如何获取领域概念。本文尝试了一种利用词语共现获取领域概念的方法，用于支持领域Ontology的构建。该方法首先通过人工领域分析，获得起始领域概念，然后利用起始概念从语料库中抽取共现的概念，从而获取相关的概念知识。同时，本文以1998年1月份的人民日报语料库为语料，针对外交和体育两个领域，尝试从中提取相关的概念，从而检验利用词语共现获取领域概念的实际效果。

(School of Management, Beijing Normal University, Beijing 100875, China)

As a large semantic knowledge resource, Ontology plays an important role in information processing. However, how to construct an effective Ontology is an important problem to its application. The first issue in automatic Ontology creation is domain concepts acquisition. In this article we experiment on a method to obtain domain concepts which are based on lexical cooccurrence (and then to support the automatic Ontology construction). The first step of this method is to obtain the primary starting concepts by manual analysis, and then to extract relative co-occurrence concepts from the corpus. Based on the corpus of People’s Daily, January 1998, the article focuses especially on the fields of sports and diplomacy. We extract the relative concepts, to examine the practical results of co-occurrence-based domain concepts acquisition.

G250.7

1Brian Roark and Eugene Charniak, Noun-phrase co-occurrence statistics for semi-automatic semantic lexicon construction. In: Proceedings of ACL-98, Montreal, Quebec, Canada, 1998
2张敏, 面向自然语言检索的索引研究，北京师范大学硕士学位论文. 2004
3Gomez-Perez A., ManzanoMacho D. A Survey of Ontology Learning Methods and Techniques. Deliverable 15, OntoWeb Project, 2003
4耿骞，毛瑞.汉语自然语言检索中的词法分析处理.情报科学 2004.4
5Shamsfard M., Barforoush A. Learning ontologies from natural language text. International Journal of Human-Computer Studies 60 (1): 17-63, 2004
6Richardson, S.D., Dolan, W.B., Vanderwende, L. MindNet: Acquiring and Structuring Semantic Information from Text. Proceedings of the joint ACL and COLING conference, Montreal. 1998
7詹卫东. 面向自然语言处理的大规模语义知识库研究述要. 见：载徐波，孙茂松，靳光谨主编.中文信息处理若干重要问题. 北京：科学出版社，2003 .107~121