RecSys 2010:
Barcelona,
Spain
Xavier Amatriain, Marc Torrens, Paul Resnick, Markus Zanker (Eds.):
Proceedings of the 2010 ACM Conference on Recommender Systems, RecSys 2010, Barcelona, Spain, September 26-30, 2010.
ACM 2010, ISBN 978-1-60558-906-0
Tutorial program
Industry panel
Innovative preference expressions and usage assessments
Contests:
way forward or detour?
Beyond prediction accuracy
Algorithms
All about groups
Recommending in social networks
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
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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