Will Hill
- 1.Allen, R.B. (1990) User models: Theory, method and prac tice, International Journal of Man-Machine Studies, 32, 511-543. Google Scholar
Digital Library
- 2.Brothers, L., Hollan, J., Nielsen, J., Stornetta, S., Abney, S., Furnas, G., and Littman, M., Supporting informal communication via ephemeral interest groups. Proc. ACM CSCW'92 Conf. Computer-Supported Cooperative Work (Toronto, Canada, 1P4 November 1992), 84-90. Google ScholarDigital Library
- 3.Goldberg, D., Nichols, D., Oki, B.M. and Terry, D. (1992) Using Collaborative Filtering to Weave an Information Tap estry. Communications of the ACM, 35, 12, pp. 51-60. Google ScholarDigital Library
- 4.Grudin, J., Social Evaluation of the User Interface: Who Does the Work and Who Gets the BENEFIT?, Proceedings of IFIP INTERACT'87: Human-Computer Interaction, 1987, 805-811.Google ScholarCross Ref
- 5.Hill, W. C., Hollan, J. D., Wroblewski, D., and McCandless, T. (1992) Edit Wear and Read Wear. In: Proceedings of ACM Conference on Human Factors in Computing Systems, CHI'92. ACM Press, New York City, New York, pp.3-9. Google ScholarDigital Library
- 6.Hill, W.C., Hollan, J.D. (1994) History-Enriched Digital Objects: Prototypes and Policy Issues, The Information Society, 10, pp. 139-145.Google ScholarCross Ref
- 7.Malone, T.W., Grant, K.R., Turbak, F.A., Brobst, S.A. and Cohen, M.D. (1987) Intelligent Information Sharing Systems. Communications of the ACM, 30, 5, pp. 390-402. Google ScholarDigital Library
- 8.Morita, M., Shinoda, Y. (1994) Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, Proceedings of the 17th Annual International SIGIR Con ference on Research and Development, pp. 272-281. Google ScholarDigital Library
- 9.Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J. (1994) GroupLens: An Open Architecture for Collaborative Filtering of Netnews. Center for Coordination Science, MIT Sloan School of Management Report WP #3666-94.Google Scholar
- 10.Rheingold, H., (1993) The virtual community: homestead ing on the electronic frontier, Reading Mass: Addison Wesley. Google ScholarDigital Library
- 11.Wroblewski, D., McCandless, T., Hill, W. (1994) Advertise ments, Proxies and Wear: Three Methods for Feedback in Interactive Systems, in Dialogue and Instruction, Beun, R., Baker, M., and Reiner, M. editors. Springer-Verlag (forth coming).Google Scholar
Index Terms
- Recommending and evaluating choices in a virtual community of use
Recommendations
Recommending social media content to community owners
SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrievalOnline communities within the enterprise offer their leaders an easy and accessible way to attract, engage, and influence others. Our research studies the recommendation of social media content to leaders (owners) of online communities within the ...
Virtual Community Success: A Uses and Gratifications Perspective
HICSS '05: Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 07In this study we report the findings of a survey on a virtual community of knowledge and interest for end-users. We approach a community participant both as a member and a user, who is also a virtual value initiator for other members. The central issue ...
Recommending new movies: even a few ratings are more valuable than metadata
RecSys '09: Proceedings of the third ACM conference on Recommender systemsThe Netflix Prize (NP) competition gave much attention to collaborative filtering (CF) approaches. Matrix factorization (MF) based CF approaches assign low dimensional feature vectors to users and items. We link CF and content-based filtering (CBF) by ...
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