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recsys | ACM Conference on Recommender Systems (RecSys)

  • 主办方 / 出版社:ACM
  • 方向:推荐系统
  • CCF等级 / JCR分区:无类
Proceedings of the 2007 ACM Conference on Recommender Systems, RecSys 2007, Minneapolis, MN, USA, October 19-20, 2007.
Private distributed collaborative filtering using estimated concordance measures.

Neal Lathia, Stephen Hailes, Licia Capra

Enhancing privacy and preserving accuracy of a distributed collaborative filtering.

Shlomo Berkovsky, Yaniv Eytani, Tsvi Kuflik, Francesco Ricci

Trust-aware recommender systems.

Paolo Massa, Paolo Avesani

The influence limiter: provably manipulation-resistant recommender systems.

Paul Resnick, Rahul Sami

Distributed collaborative filtering with domain specialization.

Shlomo Berkovsky, Tsvi Kuflik, Francesco Ricci

Complex-network theoretic clustering for identifying groups of similar listeners in p2p systems.

Amelie Anglade, Marco Tiemann, Fabio Vignoli

Robust collaborative filtering.

Bhaskar Mehta, Thomas Hofmann, Wolfgang Nejdl

A recursive prediction algorithm for collaborative filtering recommender systems.

Jiyong Zhang, Pearl Pu

Supporting product selection with query editing recommendations.

Derek G. Bridge, Francesco Ricci

Incorporating user control into recommender systems based on naive bayesian classification.

Verus Pronk, Wim F. J. Verhaegh, Adolf Proidl, Marco Tiemann

Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations.

Quang Nhat Nguyen, Francesco Ricci

Conversational recommenders with adaptive suggestions.

Paolo Viappiani, Pearl Pu, Boi Faltings

Addressing uncertainty in implicit preferences.

Sandra Clara Gadanho, Nicolas Lhuillier

Robustness of collaborative recommendation based on association rule mining.

Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke

Usage-based web recommendations: a reinforcement learning approach.

Nima Taghipour, Ahmad A. Kardan, Saeed Shiry Ghidary

Improving new user recommendations with rule-based induction on cold user data.

An-Te Nguyen, Nathalie Denos, Catherine Berrut

A probabilistic model for item-based recommender systems.

Ming Li, M. Benjamin Dias, Wael El-Deredy, Paulo J. G. Lisboa

A recommender system for on-line course enrolment: an initial study.

Michael P. O'Mahony, Barry Smyth

Case amazon: ratings and reviews as part of recommendations.

Juha Leino, Kari-Jouko Räihä

Comparing and evaluating information retrieval algorithms for news recommendation.

Toine Bogers, Antal van den Bosch

Influence-based collaborative active learning.

Neil Rubens, Masashi Sugiyama

Eigentaste 5.0: constant-time adaptability in a recommender system using item clustering.

Tavi Nathanson, Ephrat Bitton, Kenneth Y. Goldberg

Effective explanations of recommendations: user-centered design.

Nava Tintarev, Judith Masthoff

Evaluating information presentation strategies for spoken recommendations.

Andi Winterboer, Johanna D. Moore

Leveraging aggregate ratings for better recommendations.

Akhmed Umyarov, Alexander Tuzhilin

Supporting social recommendations with activity-balanced clustering.

F. Maxwell Harper, Shilad Sen, Dan Frankowski

The evaluation of a hybrid critiquing system with preference-based recommendations organization.

Li Chen, Pearl Pu

The keepup recommender system.

Andrew Webster, Julita Vassileva

Towards ensemble learning for hybrid music recommendation.

Marco Tiemann, Steffen Pauws

Toward the exploitation of social access patterns for recommendation.

Jill Freyne, Rosta Farzan, Maurice Coyle

Techlens: a researcher's desktop.

Nishikant Kapoor, Jilin Chen, John T. Butler, Gary C. Fouty, James A. Stemper, John Riedl, Joseph A. Konstan

The challenges of recommending digital selves in physical spaces.

Joseph F. McCarthy

A hybrid social-acoustic recommendation system for popular music.

Justin Donaldson

Evaluating sources of implicit feedback in web searches.

Xin Fu

A multiagent knowledge-based recommender approach with truth maintenance.

Fabiana Lorenzi

Elicitation of profile attributes by transparent communication.

Mike Radmacher

Explanations of recommendations.

Nava Tintarev

Can social information retrieval enhance the discovery and reuse of digital educational content?

Riina Vuorikari


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