Modeling document features for expert finding

ABSTRACT

We argue that expert finding is sensitive to multiple document features in an organization, and therefore, can benefit from the incorporation of these document features. We propose a unified language model, which integrates multiple document features, namely, multiple levels of associations, PageRank, indegree, internal document structure, and URL length. Our experiments on two TREC Enterprise Track collections, i.e., the W3C and CSIRO datasets, demonstrate that the natures of the two organizational intranets and two types of expert finding tasks, i.e., key contact finding for CSIRO and knowledgeable person finding for W3C, influence the effectiveness of different document features. Our work provides insights into which document features work for certain types of expert finding tasks, and helps design expert finding strategies that are effective for different scenarios.

REFERENCES

• 1: Bailey, P., Craswell, N., de Vries, A. P., Soboroff, I. (2008) Overview of the TREC 2007 Enterprise Track. In TREC 2007.
• 2: Krisztian Balog , Leif Azzopardi , Maarten de Rijke, Formal models for expert finding in enterprise corpora, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148181]
• 3: Craswell, N., and Hawking, D. (2005) Overview of the TREC-2004 Web Track. In TREC 2004.
• 4: Nick Craswell , Stephen Robertson , Hugo Zaragoza , Michael Taylor, Relevance weighting for query independent evidence, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076106]
• 5: Craswell, N., de Vries, A. P., Soboroff, I. (2006) Overview of the TREC-2005 Enterprise Track. In TREC 2005.
• 6: Desislava Petkova , W. Bruce Croft, Proximity-based document representation for named entity retrieval, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, November 06-10, 2007, Lisbon, Portugal [doi>10.1145/1321440.1321542]
• 7: Soboroff, I., de Vries, A. P. and Craswell, N. (2007) Overview of the TREC 2006 Enterprise Track. In TREC 2006.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

General Terms:
Algorithms, Experimentation, Measurement, Performance

Keywords:
enterprise search, expert finding, language models