Keyword Query Routing

被引:4
作者
Thanh Tran [1 ]
Zhang, Lei [1 ]
机构
[1] Karlsruhe Inst Technol, Inst AIFB, D-76128 Karlsruhe, Germany
关键词
Keyword search; keyword query; keyword query routing; graph-structured data; RDF;
D O I
10.1109/TKDE.2013.13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Keyword search is an intuitive paradigm for searching linked data sources on the web. We propose to route keywords only to relevant sources to reduce the high cost of processing keyword search queries over all sources. We propose a novel method for computing top-k routing plans based on their potentials to contain results for a given keyword query. We employ a keyword-element relationship summary that compactly represents relationships between keywords and the data elements mentioning them. A multilevel scoring mechanism is proposed for computing the relevance of routing plans based on scores at the level of keywords, data elements, element sets, and subgraphs that connect these elements. Experiments carried out using 150 publicly available sources on the web showed that valid plans (precision@1 of 0.92) that are highly relevant (mean reciprocal rank of 0.89) can be computed in 1 second on average on a single PC. Further, we show routing greatly helps to improve the performance of keyword search, without compromising its result quality.
引用
收藏
页码:363 / 375
页数:13
相关论文
共 50 条
  • [31] Improving the effectiveness of keyword search in databases using query logs
    Yu, Ziqiang
    Abraham, Ajith
    Yu, Xiaohui
    Liu, Yang
    Zhou, Jing
    Ma, Kun
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2019, 81 : 169 - 179
  • [32] Learned-Index-Based Semantic Keyword Query on Blockchain
    Yao, Zhongming
    Xin, Junchang
    Hao, Kun
    Wang, Zhiqiong
    Zhu, Wancheng
    MATHEMATICS, 2023, 11 (09)
  • [33] Keyword Query over Error-Tolerant Knowledge Bases
    Yu-Rong Cheng
    Ye Yuan
    Jia-Yu Li
    Lei Chen
    Guo-Ren Wang
    Journal of Computer Science and Technology, 2016, 31 : 702 - 719
  • [34] A novel XML keyword query approach using entity subtree
    Lin, Xudong
    Wang, Ning
    Xu, De
    Zeng, Xiaoning
    JOURNAL OF SYSTEMS AND SOFTWARE, 2010, 83 (06) : 990 - 1003
  • [35] Effective and Efficient Keyword Query Interpretation Using a Hybrid Graph
    Chen, Junquan
    Xu, Kaifeng
    Wang, Haofen
    Jin, Wei
    Yu, Yong
    WEB INFORMATION SYSTEM ENGINEERING-WISE 2010, 2010, 6488 : 175 - +
  • [36] Keyword Query Approach over RDF Data Based on Tree Template
    Sima, Qiang
    Li, Huiying
    PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA), 2016, : 61 - 66
  • [37] A semantic tree model-based approach for XML keyword query
    Li, X. (lgjsjlx@163.com), 1600, Binary Information Press (10): : 4973 - 4980
  • [38] A Novel Method of Keyword Query for RDF Data Based on Bipartite Graph
    Zheng, Zhiyun
    Ding, Yang
    Wang, Zhentao
    Wang, Zhenfei
    2016 IEEE 22ND INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS), 2016, : 466 - 473
  • [39] A Metadata Search Approach with Branch and Bound Algorithm to Keyword Query in Relational Databases
    Saelee, Jarunee
    Boonjing, Veera
    ICCIT: 2009 FOURTH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND CONVERGENCE INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2009, : 653 - 658
  • [40] iTopic: Influential Topic Discovery from Information Networks via Keyword Query
    Li, Jianxin
    Liu, Chengfei
    Chen, Lu
    He, Zhenying
    Datta, Amitava
    Xia, Feng
    WWW'17 COMPANION: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 2017, : 231 - 235