skip to main content
10.1145/1454008.1454063acmconferencesArticle/Chapter ViewAbstractPublication PagesrecsysConference Proceedingsconference-collections
research-article

Implications of psychological phenomenons for recommender systems

Published: 23 October 2008 Publication History

Abstract

Internet users often face the challenge of identifying the most suitable product out of some product assortment available on a certain e-sales platform. Recommender systems can substantially alleviate this typically complex task. Since the rise of such systems a lot of effort has been done in developing different recommendation approaches and algorithms, which all of them have certain strengths and weaknesses. What has been widely ignored by the recommender community so far are the potentials and impacts of psychological and decision theoretical phenomenons, which already have been investigated and applied in the field of marketing. Such phenomenons promise big capability to support users in decision making when facing a comparison situation. This paper concentrates on two classes of phenomenons, which are decoy effects and serial position effects. Tightly coupled to these phenomenons is the problem of getting the utility function of a recommender right, as this function serves both as the basis of result set calculation as well as the fundament of exploitation of above mentioned phenomenons. Putting all these aspects together an extended architecture for recommender systems will be proposed in the end of the paper.

References

[1]
D. Ariely, T. Wallsten, Seeking subjective dominance in multidimensional space: An exploration of the asymmetric dominance effect, Organizational Behaviour and Human Decision Processes, 63(3), 223--232, 1995.
[2]
A. D. Baddeley and G. Hitch. Recency re-examined. I S. Dornic (Ed.), Attentional and performance VI, pp. 647--667. Hillsdale. New York: Erlbaum, 1977.
[3]
R. Burke, Knowledge-based Recommender Systems. Encyclopedia of Lib. and Information Syst., 69(32), 180--200, 2000.
[4]
R. Burke, Hybrid Recommender Systems. User Modeling and User-Adapted Interaction, 12(4), pp. 331--370, 2002.
[5]
A. Felfernig, G. Friedrich, D. Jannach, M. Zanker, An Environment for the Development of Knowledge-based Recommender Applications, International Journal of Electronic Commerce (IJEC), 11(2), 11--34, 2006.
[6]
A. Felfernig, G. Friedrich, B. Gula, M. Hitz, G. Leitner, R.Melcher, D. Riepan, S. Strauß, E. Teppan, O. Vitouch, Persuasive Recommendation: Serial Position Effects in Knowledge-Based Recommender Systems, in Proceedings of Persuasive Technologies 07, Lecture Notes in Computer Science, pp. 283--294, Springer Verlag, 2007.
[7]
A. Felfernig, G. Friedrich, E. Teppan, K. Isak. Intelligent Debugging and Repair of Utility Constraint Sets in Knowledge-based Recommender Applications, Proceedings of the 13th ACM International Conference on Intelligent User Interfaces, pp. 218--226, 2008.
[8]
A. Felfernig, B. Gula, An Empirical Study on Consumer Behaviour in the Interaction with Knowledge-based Recommender Applications, IEEE Joint Conference on ECommerce Technology (CEC06) and Enterprise Computing, E-Commerce and E-Services (EEE06), California: IEEE Computer Society, pp. 288--296, 2006.
[9]
A. Felfernig, B. Gula, E. Teppan, Knowledge-based recommender technologies for marketing and sales, in International Journal of Pattern Recognition and Artificial Intelligence (21), pp. 333--355, World Scientific Publishing, 2007.
[10]
A. Felfernig, B. Gula, G. Leitner, R. Melcher, S. Strauß, E.Teppan, O. Vitouch, Reihenfolgeeffekte bei Produktattributen -Eine Pilotstudie zur Untersuchung von Reihenfolgeeffektenim Kontext von Recommender Systemen, Beiträge zur 49.Tagung experimentell arbeitender Psychologen, pp. 320, PapstScience Publishers, 2007.
[11]
A. Felfernig, B. Gula, G. Leitner, M. Maier, R. Melcher, E.C. Teppan, Persuasion in Knowledge-based Recommendation, to appear in proceedings of Persuasive Technologies 2008, Oulu, Finnland, 2008.
[12]
A. Felfernig, B. Gula, G. Leitner, M. Maier, R. Melcher, E.C. Teppan, A Dominance Model for the Calculation of Decoy Products in Recommendation Environments, Proceedings of the AISB conference, 2008.
[13]
Felfernig A. and Kiener A. Knowledge-based InteractiveSelling of Financial Services using FSAdvisor. Proceedings of IAAI'05, pp. 1475--1482, 2005.
[14]
F. B. Gershberg and A. P. Shimamura. Serial position effects in implicit and explicit tests of memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20: 1370--1378, 1994.
[15]
J. L. Herlocker, J. A. Konstan, J.Riedl, Explaining Collaborative Filtering Recommendations. Procs. ACM Conf. on CSCW. Pennsylvania, USA, 2000.
[16]
J. Masthoff, N. Tintarev, Effective explanations of recommendations: user-centered design, ACM conference on recommender systems, 153--156, 2007.
[17]
E. Maylor. Serial position effects in semantic memory: reconstructing the order of verses of hymns. Psychonomic Bulletin & Review, 9: 816--820, 2002.
[18]
M. Papagelis,D. Plexousakis, T. Kutsuras, Alleviating the Sparsity Problem of Collaborative Filtering using Trust Interfaces, Trust Management, ISBN: 978-3-540-26042-4, Springer Lecture Notes in Computer Science, 2005.
[19]
M. Pazzani,D. Billsus. Learning and Revising User Profiles: The Identification of Interesting Web Sites. Machine Learning, (27), pp. 313--331, 1997.
[20]
H. Pechtl, Definitions- und Wirkungsbereiche des decoy-Effekts eine empirisch-explorative Untersuchung, Nov. 2004, Diskussionspapier 10/04 ISSN 1437-6989.
[21]
J. Reilly, K. McCarthy, L. McGinty, B. Smyth, Incremental Critiquing, Knowledge Based Systems, 18(2-3), 143--151, 2005.
[22]
Reiter R. 1987. A theory of diagnosis from first principles.Artificial Intelligence, 23, 1, 57--95, 1987.
[23]
I. Simonson, A. Tversky, Choice in context: Tradeoff contrast and extremeness aversion, in: Journal of Marketing Research (39), 281--292, 1992.
[24]
I. Simonson, A. Tversky, Context-Dependent Preferences, Management Science, 39(10), 1179--1189, 1993.
[25]
C. Tan, Y. Chan, X. Yang, H. Chan, H. Teo, Effects of Choice Contrast and Order Sequence on Consumer Judgement and Decision in Comparison-Shopping Assisted Environment, Third Annual Workshop on HCI Research in MIS, 2004.
[26]
Winterfeldt D., Edwards W. Decision Analysis and Behavioral Research, Cambridge University Press,Cambridge, England, 1986.

Cited By

View all
  • (2024)Human Factors in User Modeling for Intelligent SystemsA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_1(3-42)Online publication date: 1-May-2024
  • (2021)Nudging Healthy Choices in Food Search Through List Re-RankingAdjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3450614.3464621(293-298)Online publication date: 21-Jun-2021
  • (2020)Systematic Review on Recommendation Systems2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)10.1109/ICACCCN51052.2020.9362888(952-956)Online publication date: 18-Dec-2020
  • Show More Cited By

Index Terms

  1. Implications of psychological phenomenons for recommender systems

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems
    October 2008
    348 pages
    ISBN:9781605580937
    DOI:10.1145/1454008
    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 ACM 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]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 October 2008

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. decoy effects
    2. model-based diagnosis
    3. recommender systems
    4. serial position effects

    Qualifiers

    • Research-article

    Conference

    RecSys08: ACM Conference on Recommender Systems
    October 23 - 25, 2008
    Lausanne, Switzerland

    Acceptance Rates

    Overall Acceptance Rate 254 of 1,295 submissions, 20%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)9
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 22 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Human Factors in User Modeling for Intelligent SystemsA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_1(3-42)Online publication date: 1-May-2024
    • (2021)Nudging Healthy Choices in Food Search Through List Re-RankingAdjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3450614.3464621(293-298)Online publication date: 21-Jun-2021
    • (2020)Systematic Review on Recommendation Systems2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)10.1109/ICACCCN51052.2020.9362888(952-956)Online publication date: 18-Dec-2020
    • (2019)An ANN-Based Text Mining Approach Over Hash Tag and Blogging Text DataSoft Computing for Problem Solving10.1007/978-981-15-0184-5_35(399-408)Online publication date: 28-Nov-2019
    • (2016)The Interplay of Aesthetics, Usability and Credibility in Mobile Websites and the Moderation by CultureProceedings of the 15th Brazilian Symposium on Human Factors in Computing Systems10.1145/3033701.3033711(1-10)Online publication date: 4-Oct-2016
    • (2015)A study of the dynamic features of recommender systemsArtificial Intelligence Review10.1007/s10462-012-9359-643:1(141-153)Online publication date: 1-Jan-2015

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media