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ORCIDRecSys 2014: Foster City, Silicon Valley, CA, USA
- Alfred Kobsa, Michelle X. Zhou, Martin Ester, Yehuda Koren:
Eighth ACM Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, USA - October 06 - 10, 2014. ACM 2014, ISBN 978-1-4503-2668-1
Novel applications
- Mathieu Bastian, Matthew Hayes, William Vaughan, Sam Shah, Peter Skomoroch, Hyung Jin Kim, Sal Uryasev, Christopher Lloyd:
LinkedIn skills: large-scale topic extraction and inference. 1-8 - Maria Soledad Pera
, Yiu-Kai Ng:
Automating readers' advisory to make book recommendations for K-12 readers. 9-16 - Guangchao Yuan, Pradeep K. Murukannaiah, Zhe Zhang, Munindar P. Singh:
Exploiting sentiment homophily for link prediction. 17-24 - Xiang Liu, Torsten Suel, Nasir D. Memon:
A robust model for paper reviewer assignment. 25-32
Novel setups -- context aware
- Maryam Tavakol, Ulf Brefeld:
Factored MDPs for detecting topics of user sessions. 33-40 - Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Context adaptation in interactive recommender systems. 41-48 - Diyi Yang, David Adamson, Carolyn Penstein Rosé:
Question recommendation with constraints for massive open online courses. 49-56
Novel setups -- privacy & security
- Carlos E. Seminario, David C. Wilson:
Attacking item-based recommender systems with power items. 57-64 - Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Nina Taft:
Recommending with an agenda: active learning of private attributes using matrix factorization. 65-72
Cold start and hybrid recommenders
- Liang Tang, Yexi Jiang, Lei Li, Tao Li:
Ensemble contextual bandits for personalized recommendation. 73-80 - Michele Trevisiol, Luca Maria Aiello, Rossano Schifanella, Alejandro Jaimes:
Cold-start news recommendation with domain-dependent browse graph. 81-88 - Martin Saveski, Amin Mantrach:
Item cold-start recommendations: learning local collective embeddings. 89-96 - Haishan Liu, Anuj Goyal, Trevor Walker, Anmol Bhasin:
Improving the discriminative power of inferred content information using segmented virtual profile. 97-104 - Guang Ling, Michael R. Lyu, Irwin King:
Ratings meet reviews, a combined approach to recommend. 105-112
Metrics and evaluation
- Xing Yi, Liangjie Hong, Erheng Zhong, Nathan Nan Liu, Suju Rajan:
Beyond clicks: dwell time for personalization. 113-120 - Daniel Kluver, Joseph A. Konstan:
Evaluating recommender behavior for new users. 121-128 - Alan Said, Alejandro Bellogín:
Comparative recommender system evaluation: benchmarking recommendation frameworks. 129-136 - Sanjay Krishnan, Jay Patel, Michael J. Franklin, Ken Goldberg:
A methodology for learning, analyzing, and mitigating social influence bias in recommender systems. 137-144
Diversity, novelty and serendipity
- Saul Vargas, Pablo Castells:
Improving sales diversity by recommending users to items. 145-152 - Panagiotis Adamopoulos, Alexander Tuzhilin:
On over-specialization and concentration bias of recommendations: probabilistic neighborhood selection in collaborative filtering systems. 153-160 - Michael D. Ekstrand, F. Maxwell Harper, Martijn C. Willemsen, Joseph A. Konstan:
User perception of differences in recommender algorithms. 161-168 - Florent Garcin, Boi Faltings, Olivier Donatsch, Ayar Alazzawi, Christophe Bruttin, Amr Huber:
Offline and online evaluation of news recommender systems at swissinfo.ch. 169-176
Recommendation methods and theory
- Koen Verstrepen, Bart Goethals:
Unifying nearest neighbors collaborative filtering. 177-184 - Yidan Liu, Min Xie, Laks V. S. Lakshmanan:
Recommending user generated item lists. 185-192 - José San Pedro, Alexandros Karatzoglou:
Question recommendation for collaborative question answering systems with RankSLDA. 193-200 - Yong-Deok Kim, Seungjin Choi:
Bayesian binomial mixture model for collaborative prediction with non-random missing data. 201-208
Ranking and Top-N recommendation
- Saúl Vargas, Linas Baltrunas, Alexandros Karatzoglou, Pablo Castells:
Coverage, redundancy and size-awareness in genre diversity for recommender systems. 209-216 - Xin Liu, Karl Aberer:
Towards a dynamic top-N recommendation framework. 217-224 - Hastagiri P. Vanchinathan, Isidor Nikolic, Fabio De Bona, Andreas Krause:
Explore-exploit in top-N recommender systems via Gaussian processes. 225-232 - Modou Gueye, Talel Abdessalem, Hubert Naacke:
A parameter-free algorithm for an optimized tag recommendation list size. 233-240
Matrix factorization
- Fabio Petroni, Leonardo Querzoni:
GASGD: stochastic gradient descent for distributed asynchronous matrix completion via graph partitioning. 241-248 - Josef Bauer, Alexandros Nanopoulos:
A framework for matrix factorization based on general distributions. 249-256 - Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, Ulrich Paquet:
Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. 257-264 - Chen Cheng, Fen Xia, Tong Zhang, Irwin King, Michael R. Lyu:
Gradient boosting factorization machines. 265-272 - Róbert Pálovics, András A. Benczúr, Levente Kocsis, Tamás Kiss, Erzsébet Frigó:
Exploiting temporal influence in online recommendation. 273-280
Short papers
- Babak Loni, Alan Said, Martha A. Larson, Alan Hanjalic:
'Free lunch' enhancement for collaborative filtering with factorization machines. 281-284 - Tommaso Di Noia, Vito Claudio Ostuni, Jessica Rosati, Paolo Tomeo, Eugenio Di Sciascio:
An analysis of users' propensity toward diversity in recommendations. 285-288 - Yanan Sui, Joel W. Burdick:
Clinical online recommendation with subgroup rank feedback. 289-292 - Fabio Aiolli:
Convex AUC optimization for top-N recommendation with implicit feedback. 293-296 - Paolo Cremonesi, Massimo Quadrana:
Cross-domain recommendations without overlapping data: myth or reality? 297-300 - Yong Zheng, Bamshad Mobasher, Robin D. Burke:
CSLIM: contextual SLIM recommendation algorithms. 301-304 - Jason L. Harman, John O'Donovan, Tarek F. Abdelzaher, Cleotilde Gonzalez:
Dynamics of human trust in recommender systems. 305-308 - Julia Neidhardt, Rainer Schuster, Leonhard Seyfang, Hannes Werthner:
Eliciting the users' unknown preferences. 309-312 - Wesley Waldner, Julita Vassileva:
Emphasize, don't filter!: displaying recommendations in Twitter timelines. 313-316 - Soude Fazeli, Babak Loni, Alejandro Bellogín, Hendrik Drachsler, Peter B. Sloep:
Implicit vs. explicit trust in social matrix factorization. 317-320 - Dimitrios Rafailidis, Alexandros Nanopoulos:
Modeling the dynamics of user preferences in coupled tensor factorization. 321-324 - Elizabeth M. Daly, Adi Botea, Akihiro Kishimoto, Radu Marinescu:
Multi-criteria journey aware housing recommender system. 325-328 - Roy J. Adams, Rajani S. Sadasivam, Kavitha Balakrishnan, Rebecca L. Kinney, Thomas K. Houston, Benjamin M. Marlin:
PERSPeCT: collaborative filtering for tailored health communications. 329-332 - Lihi Naamani Dery, Meir Kalech, Lior Rokach, Bracha Shapira:
Preference elicitation for narrowing the recommended list for groups. 333-336 - Dietmar Jannach, Simon Fischer:
Recommendation-based modeling support for data mining processes. 337-340 - Kunpeng Zhang, Aris M. Ouksel, Shaokun Fan, Hengchang Liu:
Scalable audience targeted models for brand advertising on social networks. 341-344 - Suvash Sedhain, Scott Sanner, Darius Braziunas, Lexing Xie, Jordan Christensen:
Social collaborative filtering for cold-start recommendations. 345-348 - Matthias Braunhofer, Victor Codina, Francesco Ricci:
Switching hybrid for cold-starting context-aware recommender systems. 349-352 - Lukas Lerche, Dietmar Jannach:
Using graded implicit feedback for bayesian personalized ranking. 353-356 - Parantapa Bhattacharya, Muhammad Bilal Zafar, Niloy Ganguly, Saptarshi Ghosh, Krishna P. Gummadi:
Inferring user interests in the Twitter social network. 357-360
Demonstrations
- Vaishak Suresh, Syeda Roohi, Magdalini Eirinaki:
Aspect-based opinion mining and recommendationsystem for restaurant reviews. 361-362 - David Ben-Shimon, Alexander Tsikinovsky, Michael Friedmann, Johannes Hörle:
Configuring and monitoring recommender system as a service. 363-364 - Travis Gingerich, Omar Alonso:
Content ordering based on commuting patterns. 365-366 - Thorben Keller, Matthias Raffelsieper:
Cosibon: an E-commerce like platform enabling bricks-and-mortar stores to use sophisticated product recommender systems. 367-368 - Florent Garcin, Frederik Galle, Boi Faltings:
Focal: a personalized mobile news reader. 369-370 - Alan Said, Alejandro Bellogín:
Rival: a toolkit to foster reproducibility in recommender system evaluation. 371-372 - Hernan Badenes, Mateo N. Bengualid, Jilin Chen, Liang Gou, Eben M. Haber, Jalal Mahmud, Jeffrey W. Nichols, Aditya Pal, Jerald Schoudt, Barton A. Smith, Ying Xuan, Huahai Yang, Michelle X. Zhou:
System U: automatically deriving personality traits from social media for people recommendation. 373-374 - Hongwei Liu, Gang Wu, Guoren Wang:
Tell me where to go and what to do next, but do not bother me. 375-376 - Babak Loni, Alan Said:
WrapRec: an easy extension of recommender system libraries. 377-378
Workshops
- Toine Bogers, Marijn Koolen, Iván Cantador:
Workshop on new trends in content-based recommender systems: (CBRecSys 2014). 379-380 - Martha A. Larson, Paolo Cremonesi, Alexandros Karatzoglou:
Overview of ACM RecSys CrowdRec 2014 workshop: crowdsourcing and human computation for recommender systems. 381-382 - Nava Tintarev, John O'Donovan, Peter Brusilovsky, Alexander Felfernig, Giovanni Semeraro, Pasquale Lops:
RecSys'14 joint workshop on interfaces and human decision making for recommender systems. 383-384 - Tao Ye, Danny Bickson, Qiang Yan:
Second workshop on large-scale recommender systems: research and best practice (LSRS 2014). 385-386 - Alan Said, Simon Dooms, Babak Loni, Domonkos Tikk:
Recommender systems challenge 2014. 387-388 - Ya Xu, Rajesh Parekh, Juliette Aurisset:
Controlled experimentation in recommendations, ranking & response prediction. 389 - Danny Bickson, John Hannon, Jan Neumann, Hassan Sayyadi:
First workshop on recommendation systems for television and online video: (RecSysTV 2014). 391-392 - Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, Paolo Cremonesi, Harald Steck:
REDD 2014 - international workshop on recommender systems evaluation: dimensions and design. 393-394 - Dietmar Jannach, Jill Freyne, Werner Geyer, Ido Guy, Andreas Hotho, Bamshad Mobasher:
The sixth ACM RecSys workshop on recommender systems and the social web. 395
Tutorials
- Xavier Amatriain:
The recommender problem revisited. 397-398 - Huiji Gao, Jiliang Tang, Huan Liu:
Personalized location recommendation on location-based social networks. 399-400 - Iván Cantador, Paolo Cremonesi:
Tutorial on cross-domain recommender systems. 401-402 - Ido Guy, Werner Geyer:
Social recommender system tutorial. 403-404
Doctoral consortium
- Matthias Braunhofer:
Hybridisation techniques for cold-starting context-aware recommender systems. 405-408 - Evangelia Christakopoulou:
Moving beyond linearity and independence in top-N recommender systems. 409-412 - Betty Mayeku:
Enhancing personalization and learner engagement through context-aware recommendation in TEL. 413-415 - Tien T. Nguyen:
Improving recommender systems: user roles and lifecycles. 417-420 - Amit Sharma:
Modeling the effect of people's preferences and social forces on adopting and sharing items. 421-424 - Martin Stettinger:
Choicla: towards domain-independent decision support for groups of users. 425-428 - Fatemeh Vahedian:
Weighted hybrid recommendation for heterogeneous networks. 429-432 - Yongfeng Zhang:
Browser-oriented universal cross-site recommendation and explanation based on user browsing logs. 433-436 - Yong Zheng:
Deviation-based and similarity-based contextual SLIM recommendation algorithms. 437-440
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