Advances in Multidisciplinary Retrieval

1. Front Matter

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2. Scaling Up High-Value Retrieval to Medium-Volume Data

   • Hamish Cunningham, Allan Hanbury, Stefan Rüger

   Pages 1-5

3. Sentence-Level Attachment Prediction

   • M-Dyaa Albakour, Udo Kruschwitz, Simon Lucas

   Pages 6-19

4. Rank by Readability: Document Weighting for Information Retrieval

   • Neil Newbold, Harry McLaughlin, Lee Gillam

   Pages 20-30

5. Knowledge Modeling in Prior Art Search

   • Erik Graf, Ingo Frommholz, Mounia Lalmas, Keith van Rijsbergen

   Pages 31-46

6. Combining Wikipedia-Based Concept Models for Cross-Language Retrieval

   • Benjamin Roth, Dietrich Klakow

   Pages 47-59

7. Exploring Contextual Models in Chemical Patent Search

   • Jay Urbain, Ophir Frieder

   Pages 60-69

8. Measuring the Variability in Effectiveness of a Retrieval System

   • Mehdi Hosseini, Ingemar J. Cox, Natasa Millic-Frayling, Vishwa Vinay

   Pages 70-83

9. An Information Retrieval Model Based on Discrete Fourier Transform

   • Alberto Costa, Massimo Melucci

   Pages 84-99

10. Logic-Based Retrieval: Technology for Content-Oriented and Analytical Querying of Patent Data

    • Iraklis Angelos Klampanos, Hengzhi Wu, Thomas Roelleke, Hany Azzam

    Pages 100-119

11. Automatic Extraction and Resolution of Bibliographical References in Patent Documents

    • Patrice Lopez

    Pages 120-135

12. An Investigation of Quantum Interference in Information Retrieval

    • Massimo Melucci

    Pages 136-151

13. Abstracts versus Full Texts and Patents: A Quantitative Analysis of Biomedical Entities

    • Bernd Müller, Roman Klinger, Harsha Gurulingappa, Heinz-Theodor Mevissen, Martin Hofmann-Apitius, Juliane Fluck et al.

    Pages 152-165

14. Back Matter

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These proceedings contain the refereed papers and posters presented at the ?rst Information Retrieval Facility Conference (IRFC), which was held in Vienna on 31 May 2010. The conference provides a multi-disciplinary, scienti?c forum that aims to bring young researchers into contact with industry at an early stage. IRFC 2010 received 20 high-quality submissions, of which 11 were accepted and appear here. The decision whether a paper was presented orally or as poster was solely based on what we thought was the most suitable form of communi- tion, considering we had only a single day for the event. In particular, the form of presentation bears no relation to the quality of the accepted papers, all of which were thoroughly peer reviewed and had to be endorsed by at least three independent reviewers. The Information Retrieval Facility (IRF) is an open IR research institution, managedby a scienti?c board drawnfrom a panel of internationalexperts in the ?eldwhoseroleistopromotethehighestqualityintheresearchsupportedbythe facility. As a non-pro?t research institution, the IRF provides services to IR s- ence in the form of a reference laboratory,hardwareand softwareinfrastructure. Committed to Open Science concepts, the IRF promotes publication of recent scienti?c results and newly developed methods, both in traditional paper form and as data sets freely available to IRF members. Such transparency ensures objective evaluation and comparabilityof results and consequently diversity and sustainability of their further development.

• Semantic Web
• distributed computing
• information retrieval
• knowledge
• knowledge modeling
• large-scale computing
• modeling
• natural language
• patent search
• quantum interference
• wikipedia

• Dept. of Computer Science, University of Sheffield, Sheffield, UK

  Hamish Cunningham

• Information Retrieval Facility, Vienna, Austria

  Allan Hanbury

• Knowledge Media Institute, The Open University, Milton Keynes, UK

  Stefan Rüger

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