skip to main content
10.1145/2063576.2064017acmconferencesArticle/Chapter ViewAbstractPublication PagescikmConference Proceedingsconference-collections
demonstration

Conkar: constraint keyword-based association discovery

Published:24 October 2011Publication History

ABSTRACT

In many domains, such as bioinformatics, cheminformatics, health informatics and social networks, data can be represented naturally as labeled graphs. To address the increasing needs in discovering interesting associations between entities in such data graphs, especially under complicated keyword-based and structural constraints, we introduce Conkar (Constrained Keyword-based Association DiscoveRy) System. Conkar is the first system for discovering constrained acyclic paths (CAP) in graph data under keyword-based constraints, with the highlight being the set of quantitative constraint metrics that we proposed, including coverage and relevance. We will demonstrate the key features of Conkar: powerful and userfriendly query specification, efficient query evaluation, flexible and on-demand result ranking, visual result display, as well as an insight tour on our novel CAP query evaluation algorithms.

References

  1. B. Aleman-Meza, et al. Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection. In WWW, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. F. Alkhateeb, et al. Constrained Regular Expressions in SPARQL. In SWWS, 2008.Google ScholarGoogle Scholar
  3. K. Anyanwu, et al. p-Queries: Enabling Querying for Semantic Associations on the Semantic Web. In WWW, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. K. Anyanwu, et al. SPARQ2L: Towards Support for Subgraph Extraction Queries in RDF Databases. In WWW, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. C. Bin, et al. Chem2Bio2RDF: a Semantic Framework for Linking and Data Mining Chemogenomic and Systems Chemical Biology Data. In BMC Bioinformatics, 2010.Google ScholarGoogle Scholar
  6. Y. Ding, et al. Semantic Web Portal: A Platform for Better Browsing and Visualizing Semantic Data. In AMT, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. H. He, et al. BLINKS: Ranked Keyword Searches on Graphs. In SIGMOD, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. R. Jin, et al. Computing Label Constraint Reachability in Graph Databases. In SIGMOD, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. K. Kochut, et al. SPARQLeR: Extended SPARQL for Semantic Association Discovery. In ESWC, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. S. Lee, et al. Building the Process-drug-side Effect Network to Discover the Relationship Between Biological Processes and Side Effects. In BMC Bioinformatics, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  11. F. Manola, et al. RDF Primer. W3C Recommendation, 2004.Google ScholarGoogle Scholar
  12. E. Prud'hommeaux, et al. SPARQL Query Language for RDF. W3C Recommendation, 2008.Google ScholarGoogle Scholar
  13. M. Zhou, et al. Efficient Association Discovery with Keyword-based Constraints on Large Graph Data. In CIKM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Conkar: http://www.cs.indiana.edu/~mozhou/conkar.htmlGoogle ScholarGoogle Scholar

Index Terms

  1. Conkar: constraint keyword-based association discovery

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
      October 2011
      2712 pages
      ISBN:9781450307178
      DOI:10.1145/2063576

      Copyright © 2011 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 October 2011

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • demonstration

      Acceptance Rates

      Overall Acceptance Rate1,861of8,427submissions,22%

      Upcoming Conference

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader