RecSys 2009: New York, NY, USA

• Francisco J. Martin:
  Recsys'09 industrial keynote: top 10 lessons learned developing deploying and operating real-world recommender systems. 1-2
  
• Michel Wedel, Roland T. Rust, Tuck Siong Chung:
  Up close and personalized: a marketing view of recommendation systems. 3-4
  
• Benjamin M. Marlin, Richard S. Zemel:
  Collaborative prediction and ranking with non-random missing data. 5-12
  

Algorithms I

• Zhengdong Lu, Deepak Agarwal, Inderjit S. Dhillon:
  A spatio-temporal approach to collaborative filtering. 13-20
  
• Seung-Taek Park, Wei Chu:
  Pairwise preference regression for cold-start recommendation. 21-28
  
• Sarah K. Tyler, Shenghuo Zhu, Yun Chi, Yi Zhang:
  Ordering innovators and laggards for product categorization and recommendation. 29-36
  
• Akhmed Umyarov, Alexander Tuzhilin:
  Improving rating estimation in recommender systems using aggregation- and variance-based hierarchical models. 37-44
  

Tags and social networks

• Jonathan Gemmell, Maryam Ramezani, Thomas Schimoler, Laura Christiansen, Bamshad Mobasher:
  The impact of ambiguity and redundancy on tag recommendation in folksonomies. 45-52
  
• Ido Guy, Naama Zwerdling, David Carmel, Inbal Ronen, Erel Uziel, Sivan Yogev, Shila Ofek-Koifman:
  Personalized recommendation of social software items based on social relations. 53-60
  
• Ralf Krestel, Peter Fankhauser, Wolfgang Nejdl:
  Latent dirichlet allocation for tag recommendation. 61-68
  
• Yi Zhen, Wu-Jun Li, Dit-Yan Yeung:
  TagiCoFi: tag informed collaborative filtering. 69-76
  

Applications

• Ranieri Baraglia, Fidel Cacheda, Victor Carneiro, Diego Fernandez, Vreixo Formoso, Raffaele Perego, Fabrizio Silvestri:
  Search shortcuts: a new approach to the recommendation of queries. 77-84
  
• Jill Freyne, Michal Jacovi, Ido Guy, Werner Geyer:
  Increasing engagement through early recommender intervention. 85-92
  
• István Pilászy, Domonkos Tikk:
  Recommending new movies: even a few ratings are more valuable than metadata. 93-100
  
• Paolo Viappiani, Craig Boutilier:
  Regret-based optimal recommendation sets in conversational recommender systems. 101-108
  

Algorithms II

• Xinlong Bao, Lawrence Bergman, Rich Thompson:
  Stacking recommendation engines with additional meta-features. 109-116
  
• Asela Gunawardana, Christopher Meek:
  A unified approach to building hybrid recommender systems. 117-124
  
• Yue Shi, Martha Larson, Alan Hanjalic:
  Exploiting user similarity based on rated-item pools for improved user-based collaborative filtering. 125-132
  
• Daniel Xiaodan Zhou, Paul Resnick:
  Assessment of conversation co-mentions as a resource for software module recommendation. 133-140
  

Privacy and security

• Zunping Cheng, Neil Hurley:
  Effective diverse and obfuscated attacks on model-based recommender systems. 141-148
  
• Neil Hurley, Zunping Cheng, Mi Zhang:
  Statistical attack detection. 149-156
  
• Reza Shokri, Pedram Pedarsani, George Theodorakopoulos, Jean-Pierre Hubaux:
  Preserving privacy in collaborative filtering through distributed aggregation of offline profiles. 157-164
  
• Benjamin Van Roy, Xiang Yan:
  Manipulation-resistant collaborative filtering systems. 165-172
  

Trust and evaluation

• Xavier Amatriain, Josep M. Pujol, Nava Tintarev, Nuria Oliver:
  Rate it again: increasing recommendation accuracy by user re-rating. 173-180
  
• Mohsen Jamali, Martin Ester:
  Using a trust network to improve top-N recommendation. 181-188
  
• Hao Ma, Michael R. Lyu, Irwin King:
  Learning to recommend with trust and distrust relationships. 189-196
  
• Frank Edward Walter, Stefano Battiston, Frank Schweitzer:
  Personalised and dynamic trust in social networks. 197-204
  

Short papers

• Dietmar Jannach, Kolja Hegelich:
  A case study on the effectiveness of recommendations in the mobile internet. 205-208
  
• Umar Qasim, Vincent Oria, Yi-fang Brook Wu, Michael E. Houle, M. Tamer Özsu:
  A partial-order based active cache for recommender systems. 209-212
  
• Carlos Castro-Herrera, Jane Cleland-Huang, Bamshad Mobasher:
  A recommender system for dynamically evolving online forums. 213-216
  
• Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompatsiaris, Paul C. Davis:
  A semantic framework for personalized ad recommendation based on advanced textual analysis. 217-220
  
• Rong Hu, Pearl Pu:
  Acceptance issues of personality-based recommender systems. 221-224
  
• Li Chen:
  Adaptive tradeoff explanations in conversational recommenders. 225-228
  
• Rajat Bhattacharjee, Ashish Goel, Konstantinos Kollias:
  An incentive-based architecture for social recommendations. 229-232
  
• Paolo Cremonesi, Roberto Turrin:
  Analysis of cold-start recommendations in IPTV systems. 233-236
  
• Denis Parra, Peter Brusilovsky:
  Collaborative filtering for social tagging systems: an experiment with CiteULike. 237-240
  
• Ajith Kodakateri Pudhiyaveetil, Susan Gauch, Hiep Phuc Luong, Josh Eno:
  Conceptual recommender system for CiteSeerX. 241-244
  
• Linas Baltrunas, Francesco Ricci:
  Context-based splitting of item ratings in collaborative filtering. 245-248
  
• Pearl Pu, Maoan Zhou, Sylvain Castagnos:
  Critiquing recommenders for public taste products. 249-252
  
• Tavi Nathanson, Ephrat Bitton, Kenneth Y. Goldberg:
  Donation dashboard: a recommender system for donation portfolios. 253-256
  
• Fabrizio Antonelli, Gianluca Francini, Marina Geymonat, Skjalg Lepsøy:
  DynamicTV: a culture-aware recommender. 257-260
  
• Alon Schclar, Alexander Tsikinovsky, Lior Rokach, Amnon Meisels, Liat Antwarg:
  Ensemble methods for improving the performance of neighborhood-based collaborative filtering. 261-264
  
• Umberto Panniello, Alexander Tuzhilin, Michele Gorgoglione, Cosimo Palmisano, Anto Pedone:
  Experimental comparison of pre- vs. post-filtering approaches in context-aware recommender systems. 265-268
  
• Samaneh Moghaddam, Mohsen Jamali, Martin Ester, Jafar Habibi:
  FeedbackTrust: using feedback effects in trust-based recommendation systems. 269-272
  
• Daniele Quercia, Licia Capra:
  FriendSensing: recommending friends using mobile phones. 273-276
  
• Berardina De Carolis, Nicole Novielli, Vito Leonardo Plantamura, Enrica Gentile:
  Generating comparative descriptions of places of interest in the tourism domain. 277-280
  
• Stephen J. Green, Paul Lamere, Jeffrey Alexander, François Maillet, Susanna Kirk, Jessica Holt, Jackie Bourque, Xiao-Wen Mak:
  Generating transparent, steerable recommendations from textual descriptions of items. 281-284
  
• Zeinab Abbassi, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu:
  Getting recommender systems to think outside the box. 285-288
  
• Maryam Khezrzadeh, Alex Thomo, William W. Wadge:
  Harnessing the power of "favorites" lists for recommendation systems. 289-292
  
• Alexandros Nanopoulos, Milos Radovanovic, Mirjana Ivanovic:
  How does high dimensionality affect collaborative filtering? 293-296
  
• Michael Hart, Rob Johnson, Amanda Stent:
  iTag: a personalized blog tagger. 297-300
  
• Giovanni Semeraro, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis:
  Knowledge infusion into content-based recommender systems. 301-304
  
• Michael P. O'Mahony, Barry Smyth:
  Learning to recommend helpful hotel reviews. 305-308
  
• Markus Weimer, Alexandros Karatzoglou, Marcel Bruch:
  Maximum margin matrix factorization for code recommendation. 309-312
  
• Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete, Miguel A. Rueda-Morales:
  Measuring predictive capability in collaborative filtering. 313-316
  
• Panagiotis Symeonidis, Alexandros Nanopoulos, Yannis Manolopoulos:
  MoviExplain: a recommender system with explanations. 317-320
  
• Klaus Seyerlehner, Arthur Flexer, Gerhard Widmer:
  On the limitations of browsing top-N recommender systems. 321-324
  
• Juan A. Recio-García, Guillermo Jiménez-Díaz, Antonio A. Sánchez-Ruiz-Granados, Belén Díaz-Agudo:
  Personality aware recommendations to groups. 325-328
  
• Noriaki Kawamae, Hitoshi Sakano, Takeshi Yamada:
  Personalized recommendation based on the personal innovator degree. 329-332
  
• Sharon Givon, Victor Lavrenko:
  Predicting social-tags for cold start book recommendations. 333-336
  
• Jacob P. Baskin, Shriram Krishnamurthi:
  Preference aggregation in group recommender systems for committee decision-making. 337-340
  
• Craig Boutilier, Kevin Regan, Paolo Viappiani:
  Preference elicitation with subjective features. 341-344
  
• Emden R. Gansner, Yifan Hu, Stephen G. Kobourov, Chris Volinsky:
  Putting recommendations on the map: visualizing clusters and relations. 345-348
  
• Florent Garcin, Boi Faltings, Radu Jurca, Nadine Joswig:
  Rating aggregation in collaborative filtering systems. 349-352
  
• Aditya G. Parameswaran, Hector Garcia-Molina:
  Recommendations with prerequisites. 353-356
  
• Don Conry, Yehuda Koren, Naren Ramakrishnan:
  Recommender systems for the conference paper assignment problem. 357-360
  
• Sylvain Castagnos, Nicolas Jones, Pearl Pu:
  Recommenders' influence on buyers' decision process. 361-364
  
• Michele Brocco, Georg Groh:
  Team recommendation in open innovation networks. 365-368
  
• Robert Jäschke, Folke Eisterlehner, Andreas Hotho, Gerd Stumme:
  Testing and evaluating tag recommenders in a live system. 369-372
  
• Sandy El Helou, Christophe Salzmann, Stéphane Sire, Denis Gillet:
  The 3A contextual ranking system: simultaneously recommending actors, assets, and group activities. 373-376
  
• Tarik Hadzic, Barry O'Sullivan:
  Uncovering functional dependencies in MDD-compiled product catalogues. 377-380
  
• Bart P. Knijnenburg, Martijn C. Willemsen:
  Understanding the effect of adaptive preference elicitation methods on user satisfaction of a recommender system. 381-384
  
• Owen Phelan, Kevin McCarthy, Barry Smyth:
  Using twitter to recommend real-time topical news. 385-388
  
• Fabián P. Lousame, Eduardo Sánchez:
  View-based recommender systems. 389-392
  

Doctoral symposium

• Ephrat Bitton:
  A spatial model for collaborative filtering of comments in an online discussion forum. 393-396
  
• Mi Zhang:
  Enhancing diversity in Top-N recommendation. 397-400
  
• Nkechi Nnadi:
  Applying relevant set correlation clustering to multi-criteria recommender systems. 401-404
  
• Marius Kaminskas:
  Matching information content with music. 405-408
  
• Monika Schubert:
  Personalized query relaxations and repairs in knowledge-based recommendation. 409-412
  
• Mozhgan Tavakolifard:
  Situation-aware trust management. 413-416
  
• Gabriele Tolomei:
  Search the web x.0: mining and recommending web-mediated processes. 417-420
  

Workshops

• Dietmar Jannach, Werner Geyer, Casey Dugan, Jill Freyne, Sarabjot S. Anand, Bamshad Mobasher, Alfred Kobsa:
  Workshop on recommender systems and the social web. 421-422
  
• Gediminas Adomavicius, Francesco Ricci:
  RecSys'09 workshop 3: workshop on context-aware recommender systems (CARS-2009). 423-424
  

Tutorials

• Jennifer Golbeck:
  Tutorial on using social trust for recommender systems. 425-426