An Extension of LCA Based XML Keyword Search

Umaporn Supasitthimethee, Toshiyuki Shimizu, M. Yoshikawa, Kriengkrai Porkaew
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Abstract

One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge about XML structure and without the need to learn a new user interface. However, keyword search interface is very flexible. It is hard for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address this challenge, we propose an extension of LCA based XML keyword search. First, to determine a return node, we provide a query syntax that the users can tell the system which node they are really interested in. In case that the users do not explicitly specify return information, our system will automatically analyze and choose appropriate return nodes by inferring from user keywords. Second, to return a meaningful result, we investigate the problem of the return information in the LCA and the proximity search approaches. To this end, we introduce the Lowest Element Node (LEN) and define our simple rules without any requirement on the schema information such as DTD or XML Schema. Our experiment results indicate that our system not only infers the right return nodes but also generates compact and meaningful results.
基于LCA的XML关键字搜索扩展
查询XML数据最方便的方法之一是关键字搜索,因为它不需要任何XML结构知识,也不需要学习新的用户界面。但是,关键字搜索界面非常灵活。系统很难决定哪个节点可能被选为返回节点,以及结果中应该包含多少信息。为了解决这个问题,我们提出了基于XML关键字搜索的LCA扩展。首先,为了确定返回节点,我们提供了一种查询语法,用户可以告诉系统他们真正感兴趣的节点。如果用户没有明确指定返回信息,我们的系统会根据用户关键词自动分析选择合适的返回节点。其次,为了返回一个有意义的结果,我们研究了LCA和邻近搜索方法中返回信息的问题。为此,我们引入了最低元素节点(LEN)并定义了简单的规则,而不需要DTD或XML schema等模式信息。实验结果表明,该系统不仅推导出了正确的返回节点,而且得到了紧凑而有意义的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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