节点文献
使用粗糙集进行智能信息检索的方法
Intelligent Information Retrieval Using Rough Set
【摘要】 提出了一种在信息检索过程中利用粗糙集理论和用户的查询兴趣扩充和优化查询的新方法。首先利用粗糙集理论对文档中用到的关键词进行同义等价类划分,并用同义等价类表示文档简化其描述,然后根据用户的不同查询级别进行不同程度的查询得到查询结果文档集,若结果集中文档数量较大则按文档与查询的相似度高低排序,先返回相似度较高的相关文档。实验表明该方法不仅解决了查询中同义词智能检索的问题,而且也提高了用户查询的准确率和有效性。
【Abstract】 The paper puts forward a new method to extend and optimize the query using rough set theory and the users characterized interest. In the information retrieval, at first it partitiones equivalently the keyword-set showed in the documents, simply the documents description using the
【关键词】 信息检索;
粗糙集;
粗包含;
相似度;
同义优化;
【Key words】 synonym equivalences, then gets the documents through different methods, and sorts them by the descending similarities between documents and queryies. The experiment shows that it can accomplish the intelligent retrieval of the synonyms and increase the precise percentage. Key words Information retrieval; Rough set; Rough including; Similarity; Synonym optimization;
【Key words】 synonym equivalences, then gets the documents through different methods, and sorts them by the descending similarities between documents and queryies. The experiment shows that it can accomplish the intelligent retrieval of the synonyms and increase the precise percentage. Key words Information retrieval; Rough set; Rough including; Similarity; Synonym optimization;
【基金】 国家自然科学基金资助项目(60275019);山西省自然科学基金资助项目
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2004年02期
- 【分类号】TP391.1
- 【被引频次】6
- 【下载频次】207