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Liberal relevance criteria of TREC -: counting on negligible documents?
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Tampere, Finland
SESSION: Evaluation table of contents
Pages: 324 - 330  
Year of Publication: 2002
ISBN:1-58113-561-0
Author
Eero Sormunen  University of Tampere, Finland
Sponsor
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 46,   Citation Count: 26
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ABSTRACT

Most test collections (like TREC and CLEF) for experimental research in information retrieval apply binary relevance assessments. This paper introduces a four-point relevance scale and reports the findings of a project in which TREC-7 and TREC-8 document pools on 38 topics were reassessed. The goal of the reassessment was to build a subcollection of TREC for experiments on highly relevant documents and to learn about the assessment process as well as the characteristics of a multigraded relevance corpus.Relevance criteria were defined so that a distinction was made between documents rich in topical information (relevant and highly relevant documents) and poor in topical information (marginally relevant documents). It turned out that about 50% of documents assessed as relevant were regarded as marginal. The characteristics of the relevance corpus and lessons learned from the reassessment project are discussed. The need to develop more elaborated relevance assessment schemes is emphasized.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Hawking, D. Overview of the TREC-9 Web Track. <http://trec.nist.gov/pubs/trec9/papers/web9.pdf> {Cited 2 January 2002}.
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Saracevic, T., Kantor. P. et al. A study of information seeking and retrieving. I Background and methodology. Journal of the American Society for Information Science 39, 3, 161-176.
 
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Sormunen, E. A method for measuring wide range performance of Boolean queries in full-text databases. Doctoral Thesis. University of Tampere. Acta Electronica Universitatis Tamperensis 34, URL: <http://acta.uta.fi/teos.phtml?3786>, Tampere 2000.
 
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Sormunen, E., Kekäläinen, J., Koivisto, J. & Jäärvelin, K. Document text characteristics affect the ranking of the most relevant documents by expanded structured queries. Journal of Documentation 57, 3, 358--374.
 
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TREC homepage, Data - English relevance judgements. Available at: <http://trec.nist.gov/data/reljudge_eng.html> {Cited 31 December 2001}.
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Voorhees, E. & Harman, D. Overview of the Seventh Text Retrieval Conference (TREC-7). 1999. http://trec.nist.gov/pubs/trec7/papers/overview_7.pdf.gz {Cited 2 January 2002}.
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CITED BY  26