A novel keyword search paradigm in relational databases: Object summaries

被引:25
|
作者
Fakas, Georgios John [1 ]
机构
[1] Manchester Metropolitan Univ, Dept Comp & Math, Manchester M15 6BH, Lancs, England
关键词
Information retrieval; Data extraction; Relational databases; Keyword search;
D O I
10.1016/j.datak.2010.11.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces a novel keyword search paradigm in relational databases, where the result of a search is an Object Summary (OS). An OS summarizes all data held about a particular Data Subject (DS) in a database. More precisely, it is a tree with a tuple containing the keyword(s) as a root and neighboring tuples as children. In contrast to traditional relational keyword search, an OS comprises a more complete and therefore semantically meaningful set of information about the enquired DS. The proposed paradigm introduces the concept of Affinity in order to automatically generate OSs. More precisely, it investigates and quantifies the Affinity of relations (i.e. Affinity) and their attributes (i.e. Attribute Affinity) in order to decide which tuples and attributes to include in the OS. Experimental evaluation on the TPC-H and Northwind databases verifies the searching quality of the proposed paradigm on both large and small databases; precision, recall, f-score, CPU and space measures are presented. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:208 / 229
页数:22
相关论文
共 50 条
  • [1] Automated generation of object summaries from relational databases: A novel keyword searching paradigm
    Fakas, Georgios John
    [J]. 2008 IEEE 24TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOP, VOLS 1 AND 2, 2008, : 239 - 242
  • [2] Size-l Object Summaries for Relational Keyword Search
    Fakas, Georgios J.
    Cai, Zhi
    Mamoulis, Nikos
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2011, 5 (03): : 229 - 240
  • [3] Versatile Size-l Object Summaries for Relational Keyword Search
    Fakas, Georgios J.
    Cai, Zhi
    Mamoulis, Nikos
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014, 26 (04) : 1026 - 1038
  • [4] Keyword search on relational databases
    Wang, Wei
    Lin, Xuemin
    Luo, Yi
    [J]. 2007 IFIP INTERNATIONAL CONFERENCE ON NETWORK AND PARALLEL COMPUTING WORKSHOPS, PROCEEDINGS, 2007, : 7 - 10
  • [5] Keyword search in relational databases
    Park, Jaehui
    Lee, Sang-goo
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2011, 26 (02) : 175 - 193
  • [6] Keyword search in relational databases
    Jaehui Park
    Sang-goo Lee
    [J]. Knowledge and Information Systems, 2011, 26 : 175 - 193
  • [7] Keyword search over relational databases
    Hassan, Mohammad
    [J]. INFORMATION MANAGEMENT IN THE MODERN ORGANIZATIONS: TRENDS & SOLUTIONS, VOLS 1 AND 2, 2008, : 1 - 6
  • [8] Keyword search for XML in relational databases
    Xu, Zhengchuan
    Chen, Zhongmin
    Sun, Hai
    Zhou, Aoying
    [J]. Gaojishu Tongxin/High Technology Letters, 2004, 14 (02):
  • [9] Progressive Keyword Search in Relational Databases
    Li, Guoliang
    Zhou, Xiaofang
    Feng, Jianhua
    Wang, Jianyong
    [J]. ICDE: 2009 IEEE 25TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 2009, : 1183 - +
  • [10] Object-Level Data Model for Keyword Search Over Relational Databases
    Zhang, Jun
    Shao, Renjun
    [J]. TRUSTCOM 2011: 2011 INTERNATIONAL JOINT CONFERENCE OF IEEE TRUSTCOM-11/IEEE ICESS-11/FCST-11, 2011, : 1361 - 1366