research-article

An interactive agent system for supporting knowledge-based recommendation: a case study on an e-novel recommender system

Authors:

Rui-Tang Huang,

Jim-Min LinAuthors Info & Claims

ICUIMC '10: Proceedings of the 4th International Conference on Uniquitous Information Management and Communication

Article No.: 53, Pages 1 - 8

https://doi.org/10.1145/2108616.2108681

Published: 14 January 2010 Publication History

Abstract

With the fast development of e-commerce, a large number variety of information existed on the Internet. Many researches tend to design a recommender system for assisting users to search the information that they have interested over the internet. The knowledge-based recommendation is one of solutions to guide the users to provide their needs, and further create a user preference model. In the past, agents commonly played the role of information retriever in a recommender system. Agents have the capability of autonomy and cooperation to assist in collecting the users' profiles and analyzing users' preferences. However, few of researches adopted embodied conversational agents (ECAs) to interact with users. In this study, we design an interactive agent system to support the knowledge-based recommendation. In addition to recommend products by using the knowledge from users' profiles, the knowledge-based approach also emphasizes the system should explain the cause of the recommendation result. For this reason, this study used ECAs to promote and explain recommendation results. As a result, our proposed system could reach the purpose of advertising products and receiving user feedbacks. In this paper, to demonstrate the usability of our system, we implement the interactive agent system in an e-novel web site, called Angel City, for recommending e-novels to readers.

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Cited By

Kleemann TLoepp BZiegler J(2024)Knowledge Graph-Based Integration of Conversational Advisors and Faceted FilteringInteracting with Computers10.1093/iwc/iwae044Online publication date: 18-Sep-2024
https://doi.org/10.1093/iwc/iwae044
LeBlanc PBanks DFu LLi MTang ZWu Q(2024)Recommender Systems: A ReviewJournal of the American Statistical Association10.1080/01621459.2023.2279695119:545(773-785)Online publication date: 4-Jan-2024
https://doi.org/10.1080/01621459.2023.2279695
Sakai KNakamura YYoshikawa YKano SIshiguro H(2023)Expressing Robot’s Understanding of Human Preference Based on Successive Estimations during DialogInternational Journal of Human–Computer Interaction10.1080/10447318.2023.223219540:18(5139-5160)Online publication date: 10-Jul-2023
https://doi.org/10.1080/10447318.2023.2232195
Show More Cited By

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An interactive agent system for supporting knowledge-based recommendation: a case study on an e-novel recommender system

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Published In

cover image ACM Conferences

ICUIMC '10: Proceedings of the 4th International Conference on Uniquitous Information Management and Communication

January 2010

550 pages

ISBN:9781605588933

DOI:10.1145/2108616

Conference Chairs:
Kwan-Ho You
Sungkyunkwan University, Korea
,
Sang-Won Lee
Sungkyunkwan University, Korea
,
General Chairs:
Won Kim
Sungkyunkwan University, Korea
,
Dongho Won
SungKyunkwan University, Korea

Copyright © 2010 ACM.

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

Publication History

Published: 14 January 2010

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National Science Council Taiwan
Feng Chia University, Taiwan

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ICUIMC '10

Sponsor:

SIGKDD

ICUIMC '10: The 4th International Conference on Ubiquitous Information Management and Communication

January 14 - 15, 2010

Suwon, Republic of Korea

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Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

Kleemann TLoepp BZiegler J(2024)Knowledge Graph-Based Integration of Conversational Advisors and Faceted FilteringInteracting with Computers10.1093/iwc/iwae044Online publication date: 18-Sep-2024
https://doi.org/10.1093/iwc/iwae044
LeBlanc PBanks DFu LLi MTang ZWu Q(2024)Recommender Systems: A ReviewJournal of the American Statistical Association10.1080/01621459.2023.2279695119:545(773-785)Online publication date: 4-Jan-2024
https://doi.org/10.1080/01621459.2023.2279695
Sakai KNakamura YYoshikawa YKano SIshiguro H(2023)Expressing Robot’s Understanding of Human Preference Based on Successive Estimations during DialogInternational Journal of Human–Computer Interaction10.1080/10447318.2023.223219540:18(5139-5160)Online publication date: 10-Jul-2023
https://doi.org/10.1080/10447318.2023.2232195
Jannach D(2022)Evaluating conversational recommender systemsArtificial Intelligence Review10.1007/s10462-022-10229-x56:3(2365-2400)Online publication date: 12-Jul-2022
https://doi.org/10.1007/s10462-022-10229-x
Yu Huang K(2010)Applying a set of strict criteria to find the β-reducts of variable precision rough setsJournal of Information and Optimization Sciences10.1080/02522667.2010.1070003731:6(1421-1440)Online publication date: Nov-2010
https://doi.org/10.1080/02522667.2010.10700037

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