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Enhancing personalized search and improving accuracy and performance for keyword-based XML queries.

机译:增强个性化搜索并提高基于关键字的XML查询的准确性和性能。

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摘要

This dissertation research focuses on three aspects related to querying of XML data. The three focus areas are: (1) Improving accuracy of XML keyword queries by modeling the contexts of XML elements; (2) Enhancing XML-based personalized search by using group profiling to determine individual preferences; and (3) Improving performance of distributed XML querying by caching of frequently-used query results. For each of these three focus areas, we developed formal concepts and algorithms that lead to the improved accuracy and performance. Our contributions are as follows: (1) Improving the accuracy of XML keyword queries: We improve search accuracy by utilizing nodes' contexts in an XML tree. Overlooking nodes' contexts when building relationships between the nodes may lead to erroneous query results. The context of a data node is determined by its parent node. By treating each set of nodes consisting of a parent and its children data nodes as one unified entity and then determining the relationships between the different unified entities, an XML system can build much more accurate relationships between data nodes in less processing time, resulting in more accurate query results. (2) Enhancing XML-based personalized search: By pre-defining and categorizing social groups based on demographic, ethnic, cultural, religious, or other characteristics, a user profile could be inferred from the profiles of the social groups to which the user belongs. This would simplify personalized search and make its process more efficient. We implemented this approach in an XML-based recommender system. The system is able to output ranked lists of content items taking into account not only the initial preferences of the user, but also the preferences of the user's various social groups. (3) Improving performance of distributed XML querying: Distributed XML documents are too big and complicated to be rapidly queried every time a user submits a query due to the overhead involved in decomposing the queries, sending the decomposed queries to remote site(s), and executing structural join operations to compose the results. We investigated strategies and mechanisms to tackle these problems. We then implemented these mechanisms in a query processor, and compared their performance to standard XML query processors.
机译:本文的研究集中在与XML数据查询有关的三个方面。这三个重点领域是:(1)通过对XML元素的上下文进行建模来提高XML关键字查询的准确性; (2)通过使用组概要分析确定个人偏好来增强基于XML的个性化搜索; (3)通过缓存常用查询结果来提高分布式XML查询的性能。对于这三个重点领域,我们开发了形式化的概念和算法,从而提高了准确性和性能。我们的贡献如下:(1)提高XML关键字查询的准确性:我们通过利用XML树中节点的上下文来提高搜索准确性。在节点之间建立关系时忽略节点的上下文可能会导致错误的查询结果。数据节点的上下文由其父节点确定。通过将由父级及其子级数据节点组成的每组节点视为一个统一实体,然后确定不同统一实体之间的关系,XML系统可以在更短的处理时间内建立数据节点之间的更准确的关系,从而获得更多的结果。准确的查询结果。 (2)增强基于XML的个性化搜索:通过根据人口统计,种族,文化,宗教或其他特征对社交组进行预定义和分类,可以从用户所属的社交组的配置文件中推断出用户配置文件。这将简化个性化搜索并使其过程更有效。我们在基于XML的推荐器系统中实现了此方法。该系统能够不仅考虑用户的初始偏好,而且还考虑用户的各种社交团体的偏好来输出内容项目的排序列表。 (3)提高分布式XML查询的性能:由于分解查询,将分解后的查询发送到远程站点所涉及的开销,每次用户提交查询时,分布式XML文档太大,太复杂,以至于无法快速查询。并执行结构化联接操作以合成结果。我们研究了解决这些问题的策略和机制。然后,我们在查询处理器中实现了这些机制,并将它们的性能与标准XML查询处理器进行了比较。

著录项

  • 作者

    Taha, Kamal.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 183 p.
  • 总页数 183
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:36:50

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