Table of Contents

• Tutorial on evaluating recommender systemsGuy Shani. 1 [doi]
• Query intent prediction and recommendationRicardo A. Baeza-Yates. 5-6 [doi]
• Will recommenders kill search?: recommender systems - an industry perspectiveIdo Guy, Alejandro Jaimes, Pau Agulló, Pat Moore, Palash Nandy, Chahab Nastar, Henrik Schinzel. 7-12 [doi]
• Global budgets for local recommendationsThomas Sandholm, Hang Ung, Christina Aperjis, Bernardo A. Huberman. 13-20 [doi]
• Aggregating preference graphs for collaborative rating predictionMaunendra Sankar Desarkar, Sudeshna Sarkar, Pabitra Mitra. 21-28 [doi]
• Eye-tracking product recommenders usageSylvain Castagnos, Nicolas Jones, Pearl Pu. 29-36 [doi]
• Contests: way forward or detour?Paul Resnick, Joseph A. Konstan, Andreas Hotho, Jesus Pindado. 37-38 [doi]
• Performance of recommender algorithms on top-n recommendation tasksPaolo Cremonesi, Yehuda Koren, Roberto Turrin. 39-46 [doi]
• On the stability of recommendation algorithmsGediminas Adomavicius, Jingjing Zhang. 47-54 [doi]
• Optimizing multiple objectives in collaborative filteringTamas Jambor, Jun Wang. 55-62 [doi]
• Understanding choice overload in recommender systemsDirk G. F. M. Bollen, Bart P. Knijnenburg, Martijn C. Willemsen, Mark P. Graus. 63-70 [doi]
• Fast als-based matrix factorization for explicit and implicit feedback datasetsIstván Pilászy, Dávid Zibriczky, Domonkos Tikk. 71-78 [doi]
• Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filteringAlexandros Karatzoglou, Xavier Amatriain, Linas Baltrunas, Nuria Oliver. 79-86 [doi]
• Collaborative filtering via euclidean embeddingMohammad Khoshneshin, W. Nick Street. 87-94 [doi]
• Online evolutionary collaborative filteringNathan Nan Liu, Min Zhao, Evan Wei Xiang, Qiang Yang. 95-102 [doi]
• Affiliation recommendation using auxiliary networksVishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Inderjit S. Dhillon. 103-110 [doi]
• Group-based recipe recommendations: analysis of data aggregation strategiesShlomo Berkovsky, Jill Freyne. 111-118 [doi]
• Group recommendations with rank aggregation and collaborative filteringLinas Baltrunas, Tadas Makcinskas, Francesco Ricci. 119-126 [doi]
• Interactive recommendations in social endorsement networksTheodoros Lappas, Dimitrios Gunopulos. 127-134 [doi]
• A matrix factorization technique with trust propagation for recommendation in social networksMohsen Jamali, Martin Ester. 135-142 [doi]
• Who is talking about what: social map-based recommendation for content-centric social websitesShiwan Zhao, Michelle X. Zhou, Quan Yuan, Xiatian Zhang, Wentao Zheng, Rongyao Fu. 143-150 [doi]
• Breaking out of the box of recommendations: from items to packagesMin Hao Xie, Laks V. S. Lakshmanan, Peter T. Wood. 151-158 [doi]
• Automatically building research reading listsMichael D. Ekstrand, Praveen Kannan, James A. Stemper, John T. Butler, Joseph A. Konstan, John Riedl. 159-166 [doi]
• Learning in efficient tag recommendationMarek Lipczak, Evangelos E. Milios. 167-174 [doi]
• Recommender algorithms in activity motivating gamesShlomo Berkovsky, Jill Freyne, Mac Coombe, Dipak Bhandari. 175-182 [doi]
• Transitive node similarity for link prediction in social networks with positive and negative linksPanagiotis Symeonidis, Eleftherios Tiakas, Yannis Manolopoulos. 183-190 [doi]
• A lightweight privacy preserving SMS-based recommendation system for mobile usersElisa Baglioni, Luca Becchetti, Lorenzo Bergamini, Ugo Maria Colesanti, Luca Filipponi, Andrea Vitaletti, Giuseppe Persiano. 191-198 [doi]
• Recommending twitter users to follow using content and collaborative filtering approachesJohn Hannon, Mike Bennett, Barry Smyth. 199-206 [doi]
• RECON: a reciprocal recommender for online datingLuiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Judy Kay. 207-214 [doi]
• Recommendation analytics: the business view, and the business caseEdouard Servan-Schreiber. 215-216 [doi]
• A belief propagation based recommender system for online servicesErman Ayday, Faramarz Fekri. 217-220 [doi]
• Using self-defined group activities for improvingrecommendations in collaborative tagging systemsDanielle H. Lee, Peter Brusilovsky. 221-224 [doi]
• Evaluating the dynamic properties of recommendation algorithmsRobin Burke. 225-228 [doi]
• Hydra: an open framework for virtual-fusion of recommendation filtersSavvas Karagiannidis, Stefanos Antaris, Christos Zigkolis, Athena Vakali. 229-232 [doi]
• Recommending based on rating frequenciesFatih Gedikli, Dietmar Jannach. 233-236 [doi]
• Content-based recommendation in social tagging systemsIván Cantador, Alejandro Bellogín, David Vallet. 237-240 [doi]
• Merging multiple criteria to identify suspicious reviewsGuangyu Wu, Derek Greene, Padraig Cunningham. 241-244 [doi]
• Personalizing the settings for Cf-based recommender systemsIl Im, Byung Ho Kim. 245-248 [doi]
• Do clicks measure recommendation relevancy?: an empirical user studyHua Zheng, Dong Wang, Qi Zhang, Hang Li, Tinghao Yang. 249-252 [doi]
• A supervised machine learning link prediction approach for academic collaboration recommendationNesserine Benchettara, Rushed Kanawati, Céline Rouveirol. 253-256 [doi]
• Beyond accuracy: evaluating recommender systems by coverage and serendipityMouzhi Ge, Carla Delgado-Battenfeld, Dietmar Jannach. 257-260 [doi]
• Recommending structure in collaborative semistructured information systemsEva Zangerle, Wolfgang Gassler, Günther Specht. 261-264 [doi]
• Iterative voting under uncertainty for group recommender systemsLihi Naamani Dery, Meir Kalech, Lior Rokach, Bracha Shapira. 265-268 [doi]
• List-wise learning to rank with matrix factorization for collaborative filteringYue Shi, Martha Larson, Alan Hanjalic. 269-272 [doi]
• Nantonac collaborative filtering: a model-based approachToshihiro Kamishima, Shotaro Akaho. 273-276 [doi]
• Social networking feeds: recommending items of interestJill Freyne, Shlomo Berkovsky, Elizabeth M. Daly, Werner Geyer. 277-280 [doi]
• Time dependency of data quality for collaborative filtering algorithmsToon De Pessemier, Simon Dooms, Tom Deryckere, Luc Martens. 281-284 [doi]
• MED-StyleR: METABO diabetes-lifestyle recommenderStephan Hammer, Jonghwa Kim, Elisabeth André. 285-288 [doi]
• Towards context-aware personalization and a broad perspective on the semantics of news articlesJeremy Jancsary, Friedrich Neubarth, Harald Trost. 289-292 [doi]
• The YouTube video recommendation systemJames Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, Dasarathi Sampath. 293-296 [doi]
• Increasing consumers' understanding of recommender results: a preference-based hybrid algorithm with strong explanatory powerPaul Marx, Thorsten Hennig-Thurau, André Marchand. 297-300 [doi]
• The network effects of recommending social connectionsElizabeth M. Daly, Werner Geyer, David R. Millen. 301-304 [doi]
• On the real-time web as a source of recommendation knowledgeSandra Garcia Esparza, Michael P. O Mahony, Barry Smyth. 305-308 [doi]
• LDA for on-the-fly auto taggingErnesto Diaz-Aviles, Mihai Georgescu, Avaré Stewart, Wolfgang Nejdl. 309-312 [doi]
• On-demand set-based recommendationsSuhrid Balakrishnan. 313-316 [doi]
• Characterisation of explicit feedback in an online music recommendation serviceGawesh Jawaheer, Martin Szomszor, Patty Kostkova. 317-320 [doi]
• An approach to situational market segmentation on on-line newspapers based on current tasksAnne Gutschmidt. 321-324 [doi]
• Incremental collaborative filtering via evolutionary co-clusteringMohammad Khoshneshin, W. Nick Street. 325-328 [doi]
• Modeling recommendation as a social choice problemMassimiliano Albanese, Antonio d Acierno, Vincenzo Moscato, Fabio Persia, Antonio Picariello. 329-332 [doi]
• Social navigation for the spoken webRobert G. Farrell, Nitendra Rajput, Rajarshi Das, Catalina M. Danis, Ketki A. Dhanesha. 333-336 [doi]
• Common attributes in an unusual context: predicting the desirability of a social matchJulia M. Mayer, Sara Motahari, Richard P. Schuler, Quentin Jones. 337-340 [doi]
• Active learning driven by rating impact analysisCarlos Eduardo R. de Mello, Marie-Aude Aufaure, Geraldo Zimbrão. 341-344 [doi]
• Tagmantic: a social recommender service based on semantic tag graphs and tag clustersJános Moldvay, Ingo Bax, Alexander Frerichs, Mirko Schuh. 345-346 [doi]
• Music recommendations with temporal context awarenessToni Cebrián, Marc Planagumà, Paulo Villegas, Xavier Amatriain. 349-352 [doi]
• Reciprocal recommender system for online datingLuiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Kalina Yacef, Judy Kay. 353-354 [doi]
• Integrating broadcast and web video content into personal tv channelsVerus Pronk, Mauro Barbieri, Jan H. M. Korst, Adolf Proidl. 355-356 [doi]
• Design and user issues in personality-based recommender systemsRong Hu. 357-360 [doi]
• Enhanced vector space models for content-based recommender systemsCataldo Musto. 361-364 [doi]
• Identifying and utilizing contextual data in hybrid recommender systemsAlan Said. 365-368 [doi]
• Topic-based recommendations in enterprise social media sharing platformsRafael Schirru. 369-372 [doi]
• Workshop on the practical use of recommender systems algorithms & technologyJérôme Picault, Dimitre Kostadinov, Pablo Castells, Alejandro Jaimes. 373-374 [doi]
• Workshop on information heterogeneity and fusion in recommender systems (HetRec 2010)Peter Brusilovsky, Iván Cantador, Yehuda Koren, Tsvi Kuflik, Markus Weimer. 375-376 [doi]
• Workshop on recommender systems for technology enhanced learningNikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos. 377-378 [doi]
• 2nd workshop on recommender systems and the social webWerner Geyer, Jill Freyne, Bamshad Mobasher, Sarabjot S. Anand, Casey Dugan. 379-380 [doi]
• Workshop report: WOMRAD 2010Amelie Anglade, Claudio Baccigalupo, Norman Casagrande, Òscar Celma, Paul Lamere. 381-382 [doi]
• Workshop on user-centric evaluation of recommender systems and their interfacesBart P. Knijnenburg, Lars Schmidt-Thieme, Dirk G. F. M. Bollen. 383-384 [doi]
• Context-awareness in recommender systems: research workshop and movie recommendation challengeGediminas Adomavicius, Alexander Tuzhilin, Shlomo Berkovsky, Ernesto William De Luca, Alan Said. 385-386 [doi]