期刊文献+

关系数据库关键词搜索方法的优化研究

下载PDF
导出
摘要 从关系数据关键词搜索应用来看,由于面临多个关系元组的组合,使得搜索效率普遍较低。同时,针对主流的借助于定位关键词对应元组方式来搜索结果,显然实用性不高。为此,在提升索引效率,优化关系数据库查询能力上,提出对元组的预习索引,利用基于模式图的元组连接枚举技术来构建可能的元组连接,并从检索结果紧致性上提出1到m元组连接的预习索引机制,以支撑复杂查询,加快索引效率。
出处 《信息系统工程》 2016年第9期128-128,共1页
  • 相关文献

参考文献1

二级参考文献11

  • 1文继军,王珊.SEEKER:基于关键词的关系数据库信息检索[J].软件学报,2005,16(7):1270-1281. 被引量:45
  • 2Agrawal S, et al. DBXplorer: A system for keyword-based search over relational databases [C] //Proc of the 18th Int Conf on Data Engineering. Los Alamitos, CA: IEEE Computer Society, 2002:5-16.
  • 3Bhalotia G, et al. Keyword searching and browsing in databases using banks [C] //Proc of the 18th Int Conf on Data Engineering. Los Alamitos, CA: IEEE Computer Society, 2002:431-440.
  • 4Hristidis V, Papakonstantinou Y. Discover: Keyword search in relational databases [C] //Proc of the 28th Int Conf on Very Large Data Bases. San Fransisco, CA: Morgan Kaufmann, 2002: 670-681.
  • 5Hristidis V, et al. Efficient Jr-style keyword search over relational databases [C] //Proc of the 29th Int Conf on Very Large Data Bases. San Fransisco, CA: Morgan Kaufmann, 2003:850-861.
  • 6Luo Y, et al. Spark: Top-k keyword query in relational databases [C] //Proc of the ACM SIGMOD Int Conf on Management of Data. New York: ACM, 2007:115-126.
  • 7Vu Q H, et al. A graph method for keyword-based selection of the top-k databases [C] //Proc of the ACM SIGMOD Int Conf on Management of Data. New York.. ACM, 2008:915- 926.
  • 8Yu B, et al. Effective keyword-based selection of relational databases[C] //Proc of the ACM SIGMOD Int Conf on Management of Data. New York: ACM, 2007:139-150.
  • 9Tata S, Lohman G M. SQAK: Doing more with keywords [C] //Proc of the ACM SIGMOD Int Conf on Management of Data. New York: ACM, 2008:889-902.
  • 10Zhou B, Pei J. Answering aggregate keyword queries on relational databases using minimal group-byS [C] //Proc of the 12th Int Conf on Extending Database Technology (EDBT2009). New York: ACM, 2009:108-119.

共引文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部