In this paper, we focus on efficient processing of XML keyword queries based on smallest lowest common ancestor （SLCA） semantics. For a given query Q with m keywords, we propose to use stable matches as the basis fo...In this paper, we focus on efficient processing of XML keyword queries based on smallest lowest common ancestor （SLCA） semantics. For a given query Q with m keywords, we propose to use stable matches as the basis for SLCA computation, where each stable match M consists of m nodes that belong to the m distinct keyword inverted lists of Q. M satisfies that no other lowest common ancestor （LCA） node of Q can be found to be located after the first node of M and be a descendant of the LCA of M, based on which the operation of locating a stable match can skip more useless nodes. We propose two stable match based algorithms for SLCA computation, i.e., BSLCA and HSLCA. BSLCA processes two keyword inverted lists each time from the shortest to the longest, while HSLCA processes all keyword inverted lists in a holistic way to avoid the problem of redundant computation invoked by BSLCA. Our extensive experimental results verify the performance advantages of our methods according to various evaluation metrics.展开更多
随着大量数据以XML格式保存,针对XML文档的关键词检索技术已经成为信息检索和数据库等相关领域的研究热点.以树的杜威编码为基础,分析并证明了XML关键词检索中核心概念SLCA(smallest lowest common ancestor)的两个重要性质,并在其基础...随着大量数据以XML格式保存,针对XML文档的关键词检索技术已经成为信息检索和数据库等相关领域的研究热点.以树的杜威编码为基础,分析并证明了XML关键词检索中核心概念SLCA(smallest lowest common ancestor)的两个重要性质,并在其基础上提出了Nearest Pair算法.该算法采用二分迭代查找技术寻找最邻近点,将求解中间结果的次数降低了一个量级.实验结果表明,该算法的性能在绝大多数情况下优于现有主流算法.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant Nos. 61073060, 61040023,61272124the Science and Technology Research and Development Program of Hebei Province of China under Grant No. 11213578
文摘In this paper, we focus on efficient processing of XML keyword queries based on smallest lowest common ancestor （SLCA） semantics. For a given query Q with m keywords, we propose to use stable matches as the basis for SLCA computation, where each stable match M consists of m nodes that belong to the m distinct keyword inverted lists of Q. M satisfies that no other lowest common ancestor （LCA） node of Q can be found to be located after the first node of M and be a descendant of the LCA of M, based on which the operation of locating a stable match can skip more useless nodes. We propose two stable match based algorithms for SLCA computation, i.e., BSLCA and HSLCA. BSLCA processes two keyword inverted lists each time from the shortest to the longest, while HSLCA processes all keyword inverted lists in a holistic way to avoid the problem of redundant computation invoked by BSLCA. Our extensive experimental results verify the performance advantages of our methods according to various evaluation metrics.
文摘随着大量数据以XML格式保存,针对XML文档的关键词检索技术已经成为信息检索和数据库等相关领域的研究热点.以树的杜威编码为基础,分析并证明了XML关键词检索中核心概念SLCA(smallest lowest common ancestor)的两个重要性质,并在其基础上提出了Nearest Pair算法.该算法采用二分迭代查找技术寻找最邻近点,将求解中间结果的次数降低了一个量级.实验结果表明,该算法的性能在绝大多数情况下优于现有主流算法.
