Abstract
Objective. Collaborative filtering is a knowledge-discovery technique that can help guide readers to items of potential interest based on the experience of prior users. This study sought to determine the impact of collaborative filtering on navigation of a large, Web-based radiology knowledge resource. Materials and Methods. Collaborative filtering was applied to a collection of 1,168 radiology hypertext documents available via the Internet. An item-based collaborative filtering algorithm identified each document’s six most closely related documents based on 248,304 page views in an 18-day period. Documents were amended to include links to their related documents, and use was analyzed over the next 5 days. Results. The mean number of documents viewed per visit increased from 1.57 to 1.74 (P < 0.0001). Conclusions. Collaborative filtering can increase a radiology information resource’s utilization and can improve its usefulness and ease of navigation. The technique holds promise for improving navigation of large Internet-based radiology knowledge resources.
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References
Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl J: GroupLens: an open architecture for collaborative filtering of Netnews. Proceedings of the ACM Conference on Computer Supported Cooperative Work, Chapel Hill, NC, pp 175–186, 1994
Hill W, Stead L, Rosenstein M, Furnas G: Recommending and evaluating choices in a virtual community of use. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, pp 194–201, 1995
J Konstan B Miller D Maltz J Herlocker L Gordon J Riedl (1997) ArticleTitleGroupLens: applying collaborative filtering to Usenet news Commun ACM 40 77–87 Occurrence Handle10.1145/245108.245126
Shardanand U, Maes P: Social information filtering: algorithms for automating “word of mouth.” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Denver, CO, pp 210–217, 1995
CE Kahn SuffixJr (1995) ArticleTitleCHORUS: a computer-based radiology handbook for international collaboration via the World Wide Web Radiographics 15 963–970 Occurrence Handle7569141
National Library of Medicine Fact Sheet: The National Library of Medicine. U.S. Department of Health and Human Services, Public Health Service. <http://www.nlm.nih.gov/pubs/factsheets/nlm.html>. Accessed 6 July 2004
TW Malone KR Grant FA Turbak SA Brobst MD Cohen (1987) ArticleTitleIntelligent information-sharing systems Commun ACM 30 390–402 Occurrence Handle10.1145/22899.22903
InstitutionalAuthorNameAmerican College of Radiology (1986) Index for Radiological Diagnoses EditionNumber3 American College of Radiology Reston, VA
DAB Lindberg BL Humphreys AT McCray (1993) ArticleTitleThe unified medical language system Methods Inf Med 32 281–291 Occurrence Handle1:STN:280:ByuD3Mfnslw%3D Occurrence Handle8412823
Griffith J, O’Riordan C: Collaborative filtering. Technical Report NUIG-IT-160900. Department of Information Technology, National University of Ireland, Galway, Ireland, 2000. <http://citeseer.ist.psu.edu/griffith00collaborative.html>. Accessed 28 April 2004
Karypis G: Evaluation of item-based top-N recommendation algorithms. Department of Computer Science, University of Minnesota, Minneapolis, MN. Technical Report CS-TR-00-046, 2000
M Deshpande G Karypis (2004) ArticleTitleItem-based top-N recommendation algorithms ACM Trans Inf Sys 22 143–177 Occurrence Handle10.1145/963770.963776
E Siegel D Channin J Perry C Carr B Reiner (2002) ArticleTitleMedical Image Resource Center 2002: an update on the RSNA’s Medical Image Resource Center J Digit Imaging 15 2–4 Occurrence Handle10.1007/s10278-002-1000-9 Occurrence Handle12134208
Vorwek D: Neue internationale Wege in der radiologischen Fort- und Weiterbildung http://www.eurorad.org—ein Projekt der EAR zur Onlinepublikation radiologischer Daten. [New international networks in radiology graduate and continuing education: http://www.eurorad.org—an EAR project for online publication of radiological data]. Radiologe 42: 109–112, 2002
JR Galvin MP D’Alessandro WE Erkonen DL Knutson DL Lacey (1994) ArticleTitleThe Virtual Hospital: a new paradigm for lifelong learning in radiology Radiographics 14 875–879 Occurrence Handle1:STN:280:ByqD38vps1M%3D Occurrence Handle7938774
Sarwar BM, Karypis G, Konstan JA, Reidl J: Item-based collaborative filtering recommendation algorithms. Proceedings of the Tenth International Conference on the World Wide Web, Hong Kong, pp 285–295, 2001
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Kahn, C.E. Collaborative Filtering to Improve Navigation of Large Radiology Knowledge Resources. J Digit Imaging 18, 131–137 (2005). https://doi.org/10.1007/s10278-004-1910-9
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DOI: https://doi.org/10.1007/s10278-004-1910-9