License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2016.23
URN: urn:nbn:de:0030-drops-57923
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2016/5792/
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Golenberg, Konstantin ; Sagiv, Yehoshua

A Practically Efficient Algorithm for Generating Answers to Keyword Search Over Data Graphs

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Abstract

In keyword search over a data graph, an answer is a non-redundant subtree that contains all the keywords of the query. A naive approach to producing all the answers by increasing height is to generalize Dijkstra's algorithm to enumerating all acyclic paths by increasing weight. The idea of freezing is introduced so that (most) non-shortest paths are generated only if they are actually needed for producing answers. The resulting algorithm for generating subtrees, called GTF, is subtle and its proof of correctness is intricate. Extensive experiments show that GTF outperforms existing systems, even ones that for efficiency's sake are incomplete (i.e., cannot produce all the answers). In particular, GTF is scalable and performs well even on large data graphs and when many answers are neede

BibTeX - Entry

@InProceedings{golenberg_et_al:LIPIcs:2016:5792,
  author =	{Konstantin Golenberg and Yehoshua Sagiv},
  title =	{{A Practically Efficient Algorithm for Generating Answers to Keyword Search Over Data Graphs}},
  booktitle =	{19th International Conference on Database Theory (ICDT 2016)},
  pages =	{23:1--23:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-002-6},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{48},
  editor =	{Wim Martens and Thomas Zeume},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2016/5792},
  URN =		{urn:nbn:de:0030-drops-57923},
  doi =		{10.4230/LIPIcs.ICDT.2016.23},
  annote =	{Keywords: Keyword search over data graphs, subtree enumeration by height, top-k answers, efficiency}
}

Keywords: Keyword search over data graphs, subtree enumeration by height, top-k answers, efficiency
Collection: 19th International Conference on Database Theory (ICDT 2016)
Issue Date: 2016
Date of publication: 14.03.2016

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