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ORCIDRecSys 2007: Minneapolis, MN, USA
- Joseph A. Konstan, John Riedl, Barry Smyth:
Proceedings of the 2007 ACM Conference on Recommender Systems, RecSys 2007, Minneapolis, MN, USA, October 19-20, 2007. ACM 2007, ISBN 978-1-59593-730-8
Privacy and trust
- Neal Lathia, Stephen Hailes, Licia Capra:
Private distributed collaborative filtering using estimated concordance measures. 1-8 - Shlomo Berkovsky
, Yaniv Eytani, Tsvi Kuflik, Francesco Ricci:
Enhancing privacy and preserving accuracy of a distributed collaborative filtering. 9-16 - Paolo Massa, Paolo Avesani:
Trust-aware recommender systems. 17-24 - Paul Resnick, Rahul Sami:
The influence limiter: provably manipulation-resistant recommender systems. 25-32
Algorithms: collaborative filtering
- Shlomo Berkovsky, Tsvi Kuflik, Francesco Ricci:
Distributed collaborative filtering with domain specialization. 33-40 - Amelie Anglade, Marco Tiemann, Fabio Vignoli:
Complex-network theoretic clustering for identifying groups of similar listeners in p2p systems. 41-48 - Bhaskar Mehta, Thomas Hofmann, Wolfgang Nejdl:
Robust collaborative filtering. 49-56 - Jiyong Zhang, Pearl Pu:
A recursive prediction algorithm for collaborative filtering recommender systems. 57-64
User issues in recommender systems
- Derek G. Bridge, Francesco Ricci:
Supporting product selection with query editing recommendations. 65-72 - Verus Pronk, Wim F. J. Verhaegh, Adolf Proidl, Marco Tiemann:
Incorporating user control into recommender systems based on naive bayesian classification. 73-80 - Quang Nhat Nguyen, Francesco Ricci:
Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations. 81-88 - Paolo Viappiani, Pearl Pu, Boi Faltings:
Conversational recommenders with adaptive suggestions. 89-96
Algorithms: learning
- Sandra Clara Gadanho, Nicolas Lhuillier:
Addressing uncertainty in implicit preferences. 97-104 - Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke:
Robustness of collaborative recommendation based on association rule mining. 105-112 - Nima Taghipour, Ahmad A. Kardan, Saeed Shiry Ghidary:
Usage-based web recommendations: a reinforcement learning approach. 113-120 - An-Te Nguyen, Nathalie Denos, Catherine Berrut:
Improving new user recommendations with rule-based induction on cold user data. 121-128
Research short papers
- Ming Li, M. Benjamin Dias, Wael El-Deredy, Paulo J. G. Lisboa:
A probabilistic model for item-based recommender systems. 129-132 - Michael P. O'Mahony, Barry Smyth:
A recommender system for on-line course enrolment: an initial study. 133-136 - Juha Leino, Kari-Jouko Räihä:
Case amazon: ratings and reviews as part of recommendations. 137-140 - Toine Bogers, Antal van den Bosch:
Comparing and evaluating information retrieval algorithms for news recommendation. 141-144 - Neil Rubens, Masashi Sugiyama:
Influence-based collaborative active learning. 145-148 - Tavi Nathanson, Ephrat Bitton, Kenneth Y. Goldberg:
Eigentaste 5.0: constant-time adaptability in a recommender system using item clustering. 149-152 - Nava Tintarev, Judith Masthoff:
Effective explanations of recommendations: user-centered design. 153-156 - Andi Winterboer, Johanna D. Moore:
Evaluating information presentation strategies for spoken recommendations. 157-160 - Akhmed Umyarov, Alexander Tuzhilin:
Leveraging aggregate ratings for better recommendations. 161-164 - F. Maxwell Harper, Shilad Sen, Dan Frankowski:
Supporting social recommendations with activity-balanced clustering. 165-168 - Li Chen, Pearl Pu:
The evaluation of a hybrid critiquing system with preference-based recommendations organization. 169-172 - Andrew Webster, Julita Vassileva:
The keepup recommender system. 173-176 - Marco Tiemann, Steffen Pauws:
Towards ensemble learning for hybrid music recommendation. 177-178 - Jill Freyne, Rosta Farzan, Maurice Coyle:
Toward the exploitation of social access patterns for recommendation. 179-182
Practice/industry track abstracts
- Nishikant Kapoor, Jilin Chen, John T. Butler, Gary C. Fouty, James A. Stemper, John Riedl, Joseph A. Konstan:
Techlens: a researcher's desktop. 183-184 - Joseph F. McCarthy:
The challenges of recommending digital selves in physical spaces. 185-186
Doctoral symposium
- Justin Donaldson:
A hybrid social-acoustic recommendation system for popular music. 187-190 - Xin Fu:
Evaluating sources of implicit feedback in web searches. 191-194 - Fabiana Lorenzi:
A multiagent knowledge-based recommender approach with truth maintenance. 195-198 - Mike Radmacher:
Elicitation of profile attributes by transparent communication. 199-202 - Nava Tintarev:
Explanations of recommendations. 203-206 - Riina Vuorikari:
Can social information retrieval enhance the discovery and reuse of digital educational content? 207-210
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