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Recommender systems — beyond matrix completion

Published: 28 October 2016 Publication History

Abstract

The future success of these systems depends on more than a Netflix challenge.

References

[1]
Adomavicius, G. and Tuzhilin, A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge and Data Engineering 17, 6 (2005), 734--749.
[2]
Adomavicius, G. and Tuzhilin, A. Context-aware recommender systems. Recommender Systems Handbook. Springer, 2011, 217--253.
[3]
Billsus, D. and Pazzani, M.J. Learning collaborative information filters. In Proceedings ICML '98 (1998), 46--54.
[4]
Breese, J.S., Heckerman, D. and Kadie, C.M. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings UAI '98 (1998), 43--52.
[5]
Castells, P., Wang, J., Lara, R. and Zhang, D. Introduction to the special issue on diversity and discovery in recommender systems. ACM Trans. Intell. Syst. Technology 5, 4 (2014), 52:1--52:3.
[6]
Chau, P.Y.K., Ho, S.Y., Ho, K.K.W. and Yao, Y. Examining the effects of malfunctioning personalized services on online users' distrust and behaviors. Decision Support Syst. 56 (2013), 180--191.
[7]
Cremonesi, P., Garzotto, F. and Turrin, R. Investigating the persuasion potential of recommender systems from a quality perspective: An empirical study. ACM Trans. Interact. Intell. Syst. 2, 1 (2012), 11:1--11:41.
[8]
Denning, P.J. ACM president's letter: Electronic junk. Commun. ACM 25, 3 (Mar. 1982), 163--165.
[9]
Dias, M.B., Locher, D., Li, M., El-Deredy, W. and Lisboa, P.J. The value of personalised recommender systems to e-business: A case study. In Proceedings RecSys'08 (2008), 291--294.
[10]
Felfernig, A., Friedrich, G., Jannach, D. and Zanker, M. An integrated environment for the development of knowledge-based recommender applications. Int. J. Electron. Commerce 11, 2 (2006), 11--34.
[11]
Friedrich, G. and Zanker, M. A taxonomy for generating explanations in recommender systems. AI Magazine 32, 3 (2011), 90--98.
[12]
Garcin, F., Faltings, B. Donatsch, O., Alazzawi, A., Bruttin, C. and Huber, A. Offline and online evaluation of news recommender systems at swissinfo.ch. In Proceedings RecSys '14 (2014), 169--176.
[13]
Ghose, A., Ipeirotis, P.G. and Li, B. Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Science 31, 3 (2012), 493--520.
[14]
Goldberg, D., Nichols, D., Oki, B. and Terry, D. Using collaborative filtering to weave an information tapestry. Commun. ACM (1992), 61--70.
[15]
Gomez-Uribe, C.A. and Hunt, N. The Netflix Recommender System: Algorithms, business value, and innovation. ACM Trans. Manage. Inf. Syst. 6, 4 (2015), 13:1--13:19.
[16]
Gorgoglione, M., Panniello, U. and Tuzhilin, A. The effect of context-aware recommendations on customer purchasing behavior and trust. In Proceedings RecSys '11 (2011), 85--92.
[17]
Hensley, C.B. Selective dissemination of information (SDI): State of the art in May, 1963. In Proceedings of AFIPS '63 (Spring), 1963, 257--262.
[18]
Hill, W., Stead, L., Rosenstein, M. and Furnas, G. Recommending and evaluating choices in a virtual community of use. In Proceedings CHI '95 (1995), 194--201.
[19]
Jannach, D., Lerche, L., Kamehkhosh, I. and Jugovac, M. What recommenders recommend: An analysis of recommendation biases and possible countermeasures. User Modeling and User-Adapted Interaction (2015), 25:1--65.
[20]
Jindal, N. and Liu, B. Opinion spam and analysis. In Proceedings WSDM '08, (2008), 219--230.
[21]
Konstan, J. and Riedl, J. Recommender systems: From algorithms to user experience. User Modeling and User-Adapted Interaction 22, 1--2 (2012), 101--123.
[22]
Lam, S.K. and Riedl, J. Shilling recommender systems for fun and profit. In Proceedings of WWW '04, (2004), 393--402.
[23]
Linden, G., Smith, B. and York, J. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing 7, 1 (2003), 76--80.
[24]
Mahmood, T., Ricci, F. and Venturini, A. Improving recommendation effectiveness: Adapting a dialogue strategy in online travel planning. J. of IT & Tourism 11, 4 (2009), 285--302.
[25]
Malone, T.W., Grant, K.R., Turbak, F.A., Brobst, S.A. and Cohen, M.D. Intelligent information-sharing systems. Commun. ACM 30, 5 (May 1987), 390--402.
[26]
Marlin, B.M. and Zemel, R.S. Collaborative prediction and ranking with non-random missing data. In Proceedings RecSys '09 (2009), 5--12.
[27]
McGinty, L. and Reilly, J. On the evolution of critiquing recommenders. Recommender Systems Handbook, Springer, 2011, 419--453.
[28]
McNee, S.M., Riedl, J. and Konstan, J.A. Being accurate is not enough: How accuracy metrics have hurt recommender systems. In Proceedings CHI '06, (2006), 1097--1101.
[29]
Mobasher, B., Burke, R., Bhaumik, R. and Williams, C. Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Trans. Internet Technology 7, 4 (Oct. 2007).
[30]
Neidhardt, J., Seyfang, L., Schuster, R. and Werthner, H. A picture-based approach to recommender systems. J. of IT & Tourism 15 (2015), 1--21.
[31]
Panniello, U., Tuzhilin, A. and Gorgoglione, M. Comparing context-aware recommender systems in terms of accuracy and diversity. User Modeling and User-Adapted Interaction 24, 1-2 (2014), 35--65.
[32]
Papadimitriou, A., Symeonidis, P. and Manolopoulos, Y. A generalized taxonomy of explanations styles for traditional and social recommender systems. Data Min. Knowl. Discovery 24, 3 (2012), 555--583.
[33]
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P. and Riedl, J. Grouplens: An open architecture for collaborative filtering of netnews. In Proceedings of CSCW'94 (1994), 175--186.
[34]
Resnick, P. and Sami, R. The information cost of manipulation-resistance in recommender systems. In Proceedings RecSys '08 (2008), 147--154.
[35]
Schafer, J.B., Konstan, J. and Riedl, J. Recommender systems in e-commerce. In Proceedings ACM EC '99 (1999), 158--166.
[36]
Shardanand, U. and Maes, P. Social information filtering: Algorithms for automating "word of mouth." In Proceedings CHI '95 (1995), 210--217.
[37]
Shimazu, H. Expertclerk: Navigating shoppers' buying process with the combination of asking and proposing. In Proceedings IJCAI '01 (2001), 1443--1448.
[38]
Wagstaff, K. Machine learning that matters. In Proceedings ICML (2012), 529--536.
[39]
Xiao, B. and Benbasat, I. E-commerce product recommendation agents: Use, characteristics, and impact. MIS Q. 31, 1 (Mar. 2007), 137--209.

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 59, Issue 11
November 2016
118 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/3013530
  • Editor:
  • Moshe Y. Vardi
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 October 2016
Published in CACM Volume 59, Issue 11

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  • (2024)Editorial: Reviews in recommender systems: 2022Frontiers in Big Data10.3389/fdata.2024.13844607Online publication date: 2-Apr-2024
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