...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The international arab journal of information technology >Logical Schema-Based Mapping Technique to Reduce Search Space in the Data Warehouse for Keyword-Based Search
【24h】

Logical Schema-Based Mapping Technique to Reduce Search Space in the Data Warehouse for Keyword-Based Search

机译：基于逻辑架构的映射技术可减少数据仓库中基于关键字的搜索的搜索空间

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Data warehouse systems are used for decision-making purposes. The Online Analytical Processing (OLAP) tools are commonly used to query and analysis of results on such systems. It is complex task for non-technical users (executives, managers etc.,) to query the data warehouse using OLAP tool keeping in view the schema knowledge. For such data warehouse users, a natural language interface is a viable solution that transparently access data to Alfa their requirement. As data warehouse contain several times more data (that increase with incremental refreshes) than the operational systems. So keyword-based searching in such systems cannot be performed similar to database based natural language systems. Existing natural language interfaces to data warehouse commonly explore keywords in data instances directly that takes more than sufficient time in generating results. This paper proposes a Logical Schema-based Mapping (LSM) technique to reduce search space in the data warehouse data instances. It performs mapping of the natural language query keywords with logical schema of the data warehouse to identify the elements prior to search in the data instances. The retrieved matches for a keyword are ranked based on six criteria proposed in this paper. Further, an algorithm has been presented which is developed upon the proposed criteria. Targeted search in the data instances is then performed efficiently after the identification of schema elements. The in-depth experiments have been carried out on real dataset to evaluate the system with respect to completeness, accuracy and performance parameters. The results show that LSM technique outperforms the existing systems.
机译：数据仓库系统用于决策目的。在线分析处理（OLAP）工具通常用于在此类系统上查询和分析结果。对于非技术用户（执行人员，管理人员等），使用OLAP工具查询数据仓库是非常复杂的任务，同时要保持对模式知识的了解。对于此类数据仓库用户，自然语言界面是一种可行的解决方案，可以透明地访问数据以满足他们的要求。由于数据仓库包含的数据（随着增量刷新而增加）是操作系统的几倍。因此，无法在此类系统中执行类似于基于数据库的自然语言系统的基于关键字的搜索。现有的到数据仓库的自然语言接口通常直接在数据实例中探索关键字，这花费了足够多的时间来生成结果。本文提出了一种基于逻辑架构的映射（LSM）技术，以减少数据仓库数据实例中的搜索空间。它执行自然语言查询关键字与数据仓库的逻辑架构的映射，以在搜索数据实例之前识别元素。根据本文提出的六个标准对检索到的关键字匹配进行排序。此外，已经提出了一种根据提出的标准开发的算法。识别架构元素之后，可以高效地执行数据实例中的目标搜索。在真实数据集上进行了深入的实验，以评估系统的完整性，准确性和性能参数。结果表明，LSM技术优于现有系统。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号