关键词: 最小最近公共祖先, 关键字查询, 语义相关实体子树集, 查准率

Abstract: A keywords retrieval method of semantic relevant was proposed to deal with the loss of semantics information in XML keywords retrieval. The implied semantics in document were fetched by using the semi-structured feature of XML document; the user inquiry intents were also captured by analyzing the inquiry syntax. And then, the elements satisfying the demands were retrieved according to user inquiry intent. Finally, in combination with semantics of the document, the expressions of inquiry results were improved by using the semantic relevant entity sub-tree set, instead of the traditional Smallest Lowest Common Ancestor (SLCA). The experimental results indicate that the precision ratio of keywords retrieval can be improved by using this method.

Key words: smallest lowest common ancestor, keyword search, semantic relevant entity sub tree set, precision ratio