Sum-max monotonic ranked joins for evaluating top-k twig queries on weighted data graphs

Yan Qi, Kasim Candan, Maria Luisa Sapino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

In many applications, the underlying data (the web, an XML document, or a relational database) can be seen as a graph. These graphs may be enriched with weights, associated with the nodes and edges of the graph, denoting application specific desirability/penalty assessments, such as popularity, trust, or cost. A particular challenge when considering such weights in query processing is that results need to be ranked accordingly. Answering keyword-based queries on weighted graphs is shown to be computationally expensive. In this paper, we first show that answering queries with further structure imposed on them remains NP-hard. We next show that, while the query evaluation task can be viewed in terms of ranked structural-joins along query axes, the monotonicity property, necessary for ranked join algorithms, is violated. Consequently, traditional ranked join algorithms are not directly applicable. Thus, we establish an alternative, sum-max monotonicity property and show how to leverage this for developing a self-punctuating, horizon-based ranked join (HR-Join) operator for ranked twig-query execution on data graphs. We experimentally show the effectiveness of the proposed evaluation schemes and the HR-join operator for merging ranked sub-results under sum-max monotonicity.

Original languageEnglish (US)
Title of host publication33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings
EditorsJohannes Gehrke, Christoph Koch, Minos Garofalakis, Karl Aberer, Carl-Christian Kanne, Erich J. Neuhold, Venkatesh Ganti, Wolfgang Klas, Chee-Yong Chan, Divesh Srivastava, Dana Florescu, Anand Deshpande
PublisherAssociation for Computing Machinery, Inc
Pages507-518
Number of pages12
ISBN (Electronic)9781595936493
StatePublished - Jan 1 2007
Event33rd International Conference on Very Large Data Bases, VLDB 2007 - Vienna, Austria
Duration: Sep 23 2007Sep 27 2007

Publication series

Name33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings

Other

Other33rd International Conference on Very Large Data Bases, VLDB 2007
CountryAustria
CityVienna
Period9/23/079/27/07

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems and Management
  • Information Systems
  • Software

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    Qi, Y., Candan, K., & Sapino, M. L. (2007). Sum-max monotonic ranked joins for evaluating top-k twig queries on weighted data graphs. In J. Gehrke, C. Koch, M. Garofalakis, K. Aberer, C-C. Kanne, E. J. Neuhold, V. Ganti, W. Klas, C-Y. Chan, D. Srivastava, D. Florescu, & A. Deshpande (Eds.), 33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings (pp. 507-518). (33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings). Association for Computing Machinery, Inc.