XML检索中的有效谓词识别算法

Roko Abubakar, S. Doraisamy, B. Nakone
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引用次数: 0

摘要

查询结构化系统是最近用于有效检索XML文档的关键字搜索系统。现有系统在查询预处理过程中没有考虑到关键字查询歧义问题。因此,系统返回不相关的用户搜索意图。搜索意图由XML数据的实体节点和谓词节点组成。本文提出了一种基于实体的查询分割(EBQS)方法,该方法将用户查询解释为关键字和/或命名实体的列表,以消除歧义。然后,提出了分段术语接近度评分器(STPS),为包含查询关键字的XML片段分配相关性分数。包含由EBQS解释的关键字的片段会获得更高的分数。最后,介绍了一种利用EBQS和STPS返回相关谓词的有效谓词识别算法(EPIA)。通过对实际XML文档的实验性能研究,验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective Predicate Identification Algorithm for XML Retrieval
Query structuring systems are keyword search systems recently used for effective retrieval of XML documents. Existing systems fail to put keyword query ambiguity problems into consideration during query preprocessing. Thus, the systems return irrelevant user search intentions. A search intention consists of entity nodes and predicate nodes of XML data. In this paper, an entity based query segmentation (EBQS) method which interprets a user query as a list of keywords and/or named entities to resolve ambiguity. Then, segment terms proximity scorer (STPS) that assigns relevance scores to XML fragments that contains query keywords is proposed. Fragments containing the keywords as interpreted by EBQS are assigned higher scores. Finally, an effective predicate identification algorithm (EPIA) which uses EBQS and STPS to return relevant predicates is introduced. The effectiveness of the algorithm is demonstrated through experimental performance study on some real world XML documents.
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