RecSys 2010: Barcelona, Spain

Tutorial program

• Guy Shani:
  Tutorial on evaluating recommender systems. 1
  
• Ricardo A. Baeza-Yates:
  Query intent prediction and recommendation. 5-6
  

Industry panel

• Ido Guy, Alejandro Jaimes, Pau Agulló, Pat Moore, Palash Nandy, Chahab Nastar, Henrik Schinzel:
  Will recommenders kill search?: recommender systems - an industry perspective. 7-12
  

Innovative preference expressions and usage assessments

• Thomas Sandholm, Hang Ung, Christina Aperjis, Bernardo A. Huberman:
  Global budgets for local recommendations. 13-20
  
• Maunendra Sankar Desarkar, Sudeshna Sarkar, Pabitra Mitra:
  Aggregating preference graphs for collaborative rating prediction. 21-28
  
• Sylvain Castagnos, Nicolas Jones, Pearl Pu:
  Eye-tracking product recommenders' usage. 29-36
  

Contests: way forward or detour?

• Paul Resnick, Joseph A. Konstan, Andreas Hotho, Jesus Pindado:
  Contests: way forward or detour? 37-38
  

Beyond prediction accuracy

• Paolo Cremonesi, Yehuda Koren, Roberto Turrin:
  Performance of recommender algorithms on top-n recommendation tasks. 39-46
  
• Gediminas Adomavicius, Jingjing Zhang:
  On the stability of recommendation algorithms. 47-54
  
• Tamas Jambor, Jun Wang:
  Optimizing multiple objectives in collaborative filtering. 55-62
  
• Dirk G. F. M. Bollen, Bart P. Knijnenburg, Martijn C. Willemsen, Mark P. Graus:
  Understanding choice overload in recommender systems. 63-70
  

Algorithms

• István Pilászy, Dávid Zibriczky, Domonkos Tikk:
  Fast als-based matrix factorization for explicit and implicit feedback datasets. 71-78
  
• Alexandros Karatzoglou, Xavier Amatriain, Linas Baltrunas, Nuria Oliver:
  Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering. 79-86
  
• Mohammad Khoshneshin, W. Nick Street:
  Collaborative filtering via euclidean embedding. 87-94
  
• Nathan Nan Liu, Min Zhao, Evan Wei Xiang, Qiang Yang:
  Online evolutionary collaborative filtering. 95-102
  

All about groups

• Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Inderjit S. Dhillon:
  Affiliation recommendation using auxiliary networks. 103-110
  
• Shlomo Berkovsky, Jill Freyne:
  Group-based recipe recommendations: analysis of data aggregation strategies. 111-118
  
• Linas Baltrunas, Tadas Makcinskas, Francesco Ricci:
  Group recommendations with rank aggregation and collaborative filtering. 119-126
  

Recommending in social networks

• Theodoros Lappas, Dimitrios Gunopulos:
  Interactive recommendations in social endorsement networks. 127-134
  
• Mohsen Jamali, Martin Ester:
  A matrix factorization technique with trust propagation for recommendation in social networks. 135-142
  
• Shiwan Zhao, Michelle X. Zhou, Quan Yuan, Xiatian Zhang, Wentao Zheng, Rongyao Fu:
  Who is talking about what: social map-based recommendation for content-centric social websites. 143-150
  

Recommending non-standard items

• Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
  Breaking out of the box of recommendations: from items to packages. 151-158
  
• Michael D. Ekstrand, Praveen Kannan, James A. Stemper, John T. Butler, Joseph A. Konstan, John Riedl:
  Automatically building research reading lists. 159-166
  
• Marek Lipczak, Evangelos E. Milios:
  Learning in efficient tag recommendation. 167-174
  
• Shlomo Berkovsky, Jill Freyne, Mac Coombe, Dipak Bhandari:
  Recommender algorithms in activity motivating games. 175-182
  

Friends and lovers

• Panagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos:
  Transitive node similarity for link prediction in social networks with positive and negative links. 183-190
  
• Elisa Baglioni, Luca Becchetti, Lorenzo Bergamini, Ugo Maria Colesanti, Luca Filipponi, Andrea Vitaletti, Giuseppe Persiano:
  A lightweight privacy preserving SMS-based recommendation system for mobile users. 191-198
  
• John Hannon, Mike Bennett, Barry Smyth:
  Recommending twitter users to follow using content and collaborative filtering approaches. 199-206
  
• Luiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Judy Kay:
  RECON: a reciprocal recommender for online dating. 207-214
  

Closing keynote

• Edouard Servan-Schreiber:
  Recommendation analytics: the business view, and the business case. 215-216
  

Posters

• Erman Ayday, Faramarz Fekri:
  A belief propagation based recommender system for online services. 217-220
  
• Danielle H. Lee, Peter Brusilovsky:
  Using self-defined group activities for improvingrecommendations in collaborative tagging systems. 221-224
  
• Robin D. Burke:
  Evaluating the dynamic properties of recommendation algorithms. 225-228
  
• Savvas Karagiannidis, Stefanos Antaris, Christos Zigkolis, Athena Vakali:
  Hydra: an open framework for virtual-fusion of recommendation filters. 229-232
  
• Fatih Gedikli, Dietmar Jannach:
  Recommending based on rating frequencies. 233-236
  
• Iván Cantador, Alejandro Bellogín, David Vallet:
  Content-based recommendation in social tagging systems. 237-240
  
• Guangyu Wu, Derek Greene, Padraig Cunningham:
  Merging multiple criteria to identify suspicious reviews. 241-244
  
• Il Im, Byung Ho Kim:
  Personalizing the settings for Cf-based recommender systems. 245-248
  
• Hua Zheng, Dong Wang, Qi Zhang, Hang Li, Tinghao Yang:
  Do clicks measure recommendation relevancy?: an empirical user study. 249-252
  
• Nesserine Benchettara, Rushed Kanawati, Céline Rouveirol:
  A supervised machine learning link prediction approach for academic collaboration recommendation. 253-256
  
• Mouzhi Ge, Carla Delgado-Battenfeld, Dietmar Jannach:
  Beyond accuracy: evaluating recommender systems by coverage and serendipity. 257-260
  
• Eva Zangerle, Wolfgang Gassler, Günther Specht:
  Recommending structure in collaborative semistructured information systems. 261-264
  
• Lihi Naamani Dery, Meir Kalech, Lior Rokach, Bracha Shapira:
  Iterative voting under uncertainty for group recommender systems. 265-268
  
• Yue Shi, Martha Larson, Alan Hanjalic:
  List-wise learning to rank with matrix factorization for collaborative filtering. 269-272
  
• Toshihiro Kamishima, Shotaro Akaho:
  Nantonac collaborative filtering: a model-based approach. 273-276
  
• Jill Freyne, Shlomo Berkovsky, Elizabeth M. Daly, Werner Geyer:
  Social networking feeds: recommending items of interest. 277-280
  
• Toon De Pessemier, Simon Dooms, Tom Deryckere, Luc Martens:
  Time dependency of data quality for collaborative filtering algorithms. 281-284
  
• Stephan Hammer, Jonghwa Kim, Elisabeth André:
  MED-StyleR: METABO diabetes-lifestyle recommender. 285-288
  
• Jeremy Jancsary, Friedrich Neubarth, Harald Trost:
  Towards context-aware personalization and a broad perspective on the semantics of news articles. 289-292
  
• James Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, Dasarathi Sampath:
  The YouTube video recommendation system. 293-296
  
• Paul Marx, Thorsten Hennig-Thurau, André Marchand:
  Increasing consumers' understanding of recommender results: a preference-based hybrid algorithm with strong explanatory power. 297-300
  
• Elizabeth M. Daly, Werner Geyer, David R. Millen:
  The network effects of recommending social connections. 301-304
  
• Sandra Garcia Esparza, Michael P. O'Mahony, Barry Smyth:
  On the real-time web as a source of recommendation knowledge. 305-308
  
• Ernesto Diaz-Aviles, Mihai Georgescu, Avaré Stewart, Wolfgang Nejdl:
  LDA for on-the-fly auto tagging. 309-312
  
• Suhrid Balakrishnan:
  On-demand set-based recommendations. 313-316
  
• Gawesh Jawaheer, Martin Szomszor, Patty Kostkova:
  Characterisation of explicit feedback in an online music recommendation service. 317-320
  
• Anne Gutschmidt:
  An approach to situational market segmentation on on-line newspapers based on current tasks. 321-324
  
• Mohammad Khoshneshin, W. Nick Street:
  Incremental collaborative filtering via evolutionary co-clustering. 325-328
  
• Massimiliano Albanese, Antonio d'Acierno, Vincenzo Moscato, Fabio Persia, Antonio Picariello:
  Modeling recommendation as a social choice problem. 329-332
  
• Robert G. Farrell, Nitendra Rajput, Rajarshi Das, Catalina M. Danis, Ketki A. Dhanesha:
  Social navigation for the spoken web. 333-336
  
• Julia M. Mayer, Sara Motahari, Richard P. Schuler, Quentin Jones:
  Common attributes in an unusual context: predicting the desirability of a social match. 337-340
  
• Carlos Eduardo R. de Mello, Marie-Aude Aufaure, Geraldo Zimbrão:
  Active learning driven by rating impact analysis. 341-344
  

Demos

• János Moldvay, Ingo Bax, Alexander Frerichs, Mirko Schuh:
  Tagmantic: a social recommender service based on semantic tag graphs and tag clusters. 345-346
  
• Josep Bachs Barrio, Xavier Amatriain Rubio:
  Geolocated movie recommendations based on expert collaborative filtering. 347-348
  
• Toni Cebrián, Marc Planagumà, Paulo Villegas, Xavier Amatriain:
  Music recommendations with temporal context awareness. 349-352
  
• Luiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Kalina Yacef, Judy Kay:
  Reciprocal recommender system for online dating. 353-354
  
• Verus Pronk, Mauro Barbieri, Jan H. M. Korst, Adolf Proidl:
  Integrating broadcast and web video content into personal tv channels. 355-356
  

Doctoral symposium

• Rong Hu:
  Design and user issues in personality-based recommender systems. 357-360
  
• Cataldo Musto:
  Enhanced vector space models for content-based recommender systems. 361-364
  
• Alan Said:
  Identifying and utilizing contextual data in hybrid recommender systems. 365-368
  
• Rafael Schirru:
  Topic-based recommendations in enterprise social media sharing platforms. 369-372
  

Workshop program

• Jérôme Picault, Dimitre Kostadinov, Pablo Castells, Alejandro Jaimes:
  Workshop on the practical use of recommender systems algorithms & technology. 373-374
  
• Peter Brusilovsky, Iván Cantador, Yehuda Koren, Tsvi Kuflik, Markus Weimer:
  Workshop on information heterogeneity and fusion in recommender systems (HetRec 2010). 375-376
  
• Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos:
  Workshop on recommender systems for technology enhanced learning. 377-378
  
• Werner Geyer, Jill Freyne, Bamshad Mobasher, Sarabjot S. Anand, Casey Dugan:
  2nd workshop on recommender systems and the social web. 379-380
  
• Amelie Anglade, Claudio Baccigalupo, Norman Casagrande, Òscar Celma, Paul Lamere:
  Workshop report: WOMRAD 2010. 381-382
  
• Bart P. Knijnenburg, Lars Schmidt-Thieme, Dirk G. F. M. Bollen:
  Workshop on user-centric evaluation of recommender systems and their interfaces. 383-384
  
• Gediminas Adomavicius, Alexander Tuzhilin, Shlomo Berkovsky, Ernesto William De Luca, Alan Said:
  Context-awareness in recommender systems: research workshop and movie recommendation challenge. 385-386
  

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