Article

Intelligent profiling by example

Authors:

Sybil Shearin,

Henry LiebermanAuthors Info & Claims

IUI '01: Proceedings of the 6th international conference on Intelligent user interfaces

Pages 145 - 151

https://doi.org/10.1145/359784.360325

Published: 01 January 2001 Publication History

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Abstract

The Apt Decision agent learns user preferences in the domain of rental real estate by observing the user's critique of apartment features. Users provide a small number of criteria in the initial interaction, receive a display of sample apartments, and then react to any feature of any apartment independently, in any order. Users learn which features are important to them as they discover the details of specific apartments. The agent uses interactive learning techniques to build a profile of user preferences, which can then be saved and used in further retrievals. Because the user's actions in specifying preferences are also used by the agent to create a profile, the result is an agent that builds a profile without redundant or unnecessary effort on the user's part.

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Cited By

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Gharahighehi APliakos KVens C(2021)Recommender Systems in the Real Estate Market—A SurveyApplied Sciences10.3390/app1116750211:16(7502)Online publication date: 16-Aug-2021
https://doi.org/10.3390/app11167502
Rehman FMasood HUl-Hasan ANawaz RShafait F(2019)An Intelligent Context Aware Recommender System for Real-EstatePattern Recognition and Artificial Intelligence10.1007/978-3-030-37548-5_14(177-191)Online publication date: 18-Dec-2019
https://doi.org/10.1007/978-3-030-37548-5_14
Knoll JGroß RSchwanke ARinn BSchreyer M(2018)Applying Recommender Approaches to the Real Estate e-Commerce MarketInnovations for Community Services10.1007/978-3-319-93408-2_9(111-126)Online publication date: 6-Jun-2018
https://doi.org/10.1007/978-3-319-93408-2_9
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Intelligent profiling by example

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Published In

IUI '01: Proceedings of the 6th international conference on Intelligent user interfaces

January 2001

174 pages

ISBN:1581133251

DOI:10.1145/359784

Chairmen:
Candy Sidner
MERL
,
Johanna Moore
Univ. of Edinburgh, Edinburgh, Scotland

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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Association for Computing Machinery

New York, NY, United States

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Published: 01 January 2001

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IUI01

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IUI01: International Conference on Intelligent User Interfaces 2001

January 14 - 17, 2001

New Mexico, Santa Fe, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

View all

Gharahighehi APliakos KVens C(2021)Recommender Systems in the Real Estate Market—A SurveyApplied Sciences10.3390/app1116750211:16(7502)Online publication date: 16-Aug-2021
https://doi.org/10.3390/app11167502
Rehman FMasood HUl-Hasan ANawaz RShafait F(2019)An Intelligent Context Aware Recommender System for Real-EstatePattern Recognition and Artificial Intelligence10.1007/978-3-030-37548-5_14(177-191)Online publication date: 18-Dec-2019
https://doi.org/10.1007/978-3-030-37548-5_14
Knoll JGroß RSchwanke ARinn BSchreyer M(2018)Applying Recommender Approaches to the Real Estate e-Commerce MarketInnovations for Community Services10.1007/978-3-319-93408-2_9(111-126)Online publication date: 6-Jun-2018
https://doi.org/10.1007/978-3-319-93408-2_9
Xie HWang DRao YWong TRaymond LChen LWang F(2016)Incorporating user experience into critiquing-based recommender systems: a collaborative approach based on compound critiquingInternational Journal of Machine Learning and Cybernetics10.1007/s13042-016-0611-29:5(837-852)Online publication date: 3-Oct-2016
https://doi.org/10.1007/s13042-016-0611-2
Centeno RHermoso RFasli M(2015)On the inaccuracy of numerical ratingsInformation Systems Frontiers10.1007/s10796-014-9526-117:4(809-825)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1007/s10796-014-9526-1
Lamche BTrottmann UWörndl WSaid ADe Luca EQuercia DBöhmer M(2014)Active learning strategies for exploratory mobile recommender systemsProceedings of the 4th Workshop on Context-Awareness in Retrieval and Recommendation10.1145/2601301.2601304(10-17)Online publication date: 13-Apr-2014
https://dl.acm.org/doi/10.1145/2601301.2601304
Hermoso RCenteno RFasli M(2014)From blurry numbers to clear preferencesExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.09.02541:5(2269-2285)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1016/j.eswa.2013.09.025
Babas KChalkiadakis GTripolitakis EYang QKing ILi QPu PKarypis G(2013)You are what you consumeProceedings of the 7th ACM conference on Recommender systems10.1145/2507157.2507158(221-228)Online publication date: 12-Oct-2013
https://dl.acm.org/doi/10.1145/2507157.2507158
Li HLai LXu XShen YXu XXia C(2013)User Interest Profile Identification Using Wikipedia Knowledge Database2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing10.1109/HPCC.and.EUC.2013.340(2362-2367)Online publication date: Nov-2013
https://doi.org/10.1109/HPCC.and.EUC.2013.340
Pommeranz ABroekens JWiggers PBrinkman WJonker C(2012)Designing interfaces for explicit preference elicitationUser Modeling and User-Adapted Interaction10.1007/s11257-011-9116-622:4-5(357-397)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1007/s11257-011-9116-6
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