Size-l object summaries for relational keyword search

  • Authors:

  • Georgios J. Fakas;Zhi Cai;Nikos Mamoulis

  • Affiliations:

  • Manchester Metropolitan University, UK;Manchester Metropolitan University, UK;The University of Hong Kong, Hong Kong

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2011

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Abstract

A previously proposed keyword search paradigm produces, as a query result, a ranked list of Object Summaries (OSs). An OS is a tree structure of related tuples that summarizes all data held in a relational database about a particular Data Subject (DS). However, some of these OSs are very large in size and therefore unfriendly to users that initially prefer synoptic information before proceeding to more comprehensive information about a particular DS. In this paper, we investigate the effective and efficient retrieval of concise and informative OSs. We argue that a good size-l OS should be a stand-alone and meaningful synopsis of the most important information about the particular DS. More precisely, we define a size-l OS as a partial OS composed of l important tuples. We propose three algorithms for the efficient generation of size-l OSs (in addition to the optimal approach which requires exponential time). Experimental evaluation on DBLP and TPC-H databases verifies the effectiveness and efficiency of our approach.