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CADIAL search engine at INEX. Jure Mijić 1 , Marie-Francine Moens 2 , Bojana Dalbelo Bašić 1 1 Faculty of Electrical Engineering and Computing jure.mijic@fer.hr, bojana.dalbelo@fer.hr 2 Department of Computer Science, Katholieke Universiteit Leuven sien.moens @ cs.kuleuven.be

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cadial search engine at inex
CADIAL search engine at INEX

ITI2008Cavtat2008-06-25

Jure Mijić1, Marie-Francine Moens2, Bojana Dalbelo Bašić1

1Faculty of Electrical Engineering and Computing

jure.mijic@fer.hr, bojana.dalbelo@fer.hr

2Department of Computer Science, Katholieke Universiteit Leuven

sien.moens@cs.kuleuven.be

INEX 2008Schloss Dagstuhl Conference Center, Wadern, Germany2008-12-16

presentation overview
Presentation overview

INEX 2008Dagstuhl2008-12-16

  • What is CADIAL project?
  • System overview
  • Ranking model
  • Ad hoc results
  • Conclusion
  • Future work
what is cadial project
What is CADIAL project?

INEX 2008Dagstuhl2008-12-16

  • Bilateral project between the Government of Flanders and the Ministry of Science, Education and Sports of the Republic of Croatia
  • Aims of the CADIAL project:
    • Provide access to a collection of Croatian legislative documents
    • Enable the use of the Eurovoc thesaurus, an EU standard thesaurus for document indexing and retrieval
system overview
System overview

INEX 2008Dagstuhl2008-12-16

  • Built with expandability in mind
  • Supports multiple information retrieval models
  • Supports morphological normalization modules
  • An indexer tool is used for document indexing
    • Input documents are in XML format
    • Output is an index database (a base structure for every search engine model)‏
    • Index database is upgraded with additional data required by the model (various statistical information)‏
ranking model
Ranking model

INEX 2008Dagstuhl2008-12-16

  • Language model
    • Element priors based on element location and depth
    • Smoothing on document and collection level
  • Additional features
    • Support for CAS queries
    • Support for +/- keyword operators
    • Simple overlapping element removal
    • Stemming
ad hoc results
Ad hoc results

INEX 2008Dagstuhl2008-12-16

  • Our runs:
    • Three CO runs
      • One returning only documents
      • Two returning elements
    • Three CAS runs with various smoothing factors
ad hoc results1
Ad hoc results

INEX 2008Dagstuhl2008-12-16

conclusion
Conclusion

INEX 2008Dagstuhl2008-12-16

  • Retrieving whole documents performed better than element retrieval at higher levels of recall
  • CAS queries performed slightly better that CO queries
  • Higher smoothing at the document level contributed to better performance
future work
Future work

INEX 2008Dagstuhl2008-12-16

  • Other smoothing techniques
  • Pseudo relevance feedback
  • Incorporating link evidence
  • Information extraction methods
the end
The End

INEX 2008Dagstuhl2008-12-16

Thank you

language model
Language model

INEX 2008Dagstuhl2008-12-16

ad