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Evaluating expertise recommendations
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Source Conference on Supporting Group Work archive
Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work table of contents
Boulder, Colorado, USA
Session: Session 6 table of contents
Pages: 214 - 223  
Year of Publication: 2001
ISBN:1-58113-294-8
Author
David W. McDonald  FX Palo Alto Laboratory, Inc., Palo Alto, CA
Sponsor
SIGGROUP: ACM Special Interest Group on Supporting Group Work
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 80,   Citation Count: 11
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ABSTRACT

Finding a person who has the expertise to solve a specific problem is an important application of recommender systems to a difficult organizational problem. Prior systems have made attempts to implement solutions to this problem, but few systems have undergone systematic user evaluation. This work describes a systematic evaluation of the Expertise Recommender (ER), a system that recommends people who are likely to have expertise in a specific problem. ER and the organizational context for which it was designed are described to provide a basis for understanding this evaluation. Prior to conducting the evaluation, a baseline experiment showed that people are relatively good at judging coworkers' expertise when given an appropriate context. This finding provides a way to demonstrate the effectiveness of ER by comparing ER's performance to ratings by coworkers. The evaluation, the design, and results are described in detail. The results suggest that the participants agree with the recommendations made by ER, and that ER significantly outperforms other expertise recommender systems when compared using similar metrics.


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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CITED BY  11