Article

Supporting product selection with query editing recommendations

Authors:

Derek Bridge,

Francesco RicciAuthors Info & Claims

RecSys '07: Proceedings of the 2007 ACM conference on Recommender systems

Pages 65 - 72

https://doi.org/10.1145/1297231.1297243

Published: 19 October 2007 Publication History

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Abstract

Consider a conversational product recommender system in which a user repeatedly edits and resubmits a query until she finds a product that she wants. We show how an advisor can: observe the user's actions; infer constraints on the user's utility function and add them to a user model; use the constraints to deduce which queries the user is likely to try next; and advise the user to avoid those that are unsatisfiable. We call this information recommendation. We give a detailed formulation of information recommendation for the case of products that are described by a set of Boolean features. Our experimental results show that if the user is given advice, the number of queries she needs to try before finding the product of highest utility is greatly reduced. We also show that an advisor that confines its advice to queries that the user model predicts are likely to be tried next will give shorter advice than one whose advice is unconstrained by the user model.

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Kar PRoy MDatta SKar PRoy MDatta S(2024)A Surveillance Framework of Suspicious Browsing Activities on the Internet Using Recommender Systems: A Case StudyRecommender Systems: Algorithms and their Applications10.1007/978-981-97-0538-2_11(131-141)Online publication date: 12-Jun-2024
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Toffano FWilson N(2022)Minimality and comparison of sets of multi-attribute vectorsAutonomous Agents and Multi-Agent Systems10.1007/s10458-022-09572-836:2Online publication date: 1-Oct-2022
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Kalloori SRicci FGennari RPera SEkstrand MAmatriain XO'Donovan J(2018)Eliciting pairwise preferences in recommender systemsProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3240364(329-337)Online publication date: 27-Sep-2018
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Index Terms

Supporting product selection with query editing recommendations
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Information

Published In

RecSys '07: Proceedings of the 2007 ACM conference on Recommender systems

October 2007

222 pages

ISBN:9781595937308

DOI:10.1145/1297231

General Chair:
Joseph A. Konstan
University of Minnesota, USA
,
Program Chairs:
John Riedl
University of Minnesota, USA
,
Barry Smyth
University College, Dublin, Ireland

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]

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Published: 19 October 2007

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RecSys07: ACM Conference on Recommender Systems

October 19 - 20, 2007

MN, Minneapolis, USA

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

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Kar PRoy MDatta SKar PRoy MDatta S(2024)A Surveillance Framework of Suspicious Browsing Activities on the Internet Using Recommender Systems: A Case StudyRecommender Systems: Algorithms and their Applications10.1007/978-981-97-0538-2_11(131-141)Online publication date: 12-Jun-2024
https://doi.org/10.1007/978-981-97-0538-2_11
Toffano FWilson N(2022)Minimality and comparison of sets of multi-attribute vectorsAutonomous Agents and Multi-Agent Systems10.1007/s10458-022-09572-836:2Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s10458-022-09572-8
Kalloori SRicci FGennari RPera SEkstrand MAmatriain XO'Donovan J(2018)Eliciting pairwise preferences in recommender systemsProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3240364(329-337)Online publication date: 27-Sep-2018
https://dl.acm.org/doi/10.1145/3240323.3240364
George AWilson NO'Sullivan B(2016)Towards fast algorithms for the preference consistency problem based on hierarchical modelsProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060771(1081-1087)Online publication date: 9-Jul-2016
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George AWilson N(2016)Preference Inference Based on Pareto ModelsScalable Uncertainty Management10.1007/978-3-319-45856-4_12(170-183)Online publication date: 30-Aug-2016
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Wilson NGeorge AO'Sullivan B(2015)Computation and complexity of preference inference based on hierarchical modelsProceedings of the 24th International Conference on Artificial Intelligence10.5555/2832581.2832705(3271-3277)Online publication date: 25-Jul-2015
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George ARazak AWilson N(2015)The Comparison of Multi-objective Preference Inference Based on Lexicographic and Weighted Average ModelsProceedings of the 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)10.1109/ICTAI.2015.26(88-95)Online publication date: 9-Nov-2015
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Blanco HRicci FYang QKing ILi QPu PKarypis G(2013)Acquiring user profiles from implicit feedback in a conversational recommender systemProceedings of the 7th ACM conference on Recommender systems10.1145/2507157.2507217(307-310)Online publication date: 12-Oct-2013
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Blanco HRicci FShin SMaldonado J(2013)Inferring user utility for query revision recommendationProceedings of the 28th Annual ACM Symposium on Applied Computing10.1145/2480362.2480416(245-252)Online publication date: 18-Mar-2013
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Abstract

References

Cited By

Index Terms

Recommendations

Integrating collaborative filtering and matching-based search for product recommendations

Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews

Naïve filterbots for robust cold-start recommendations

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