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Critiquing-based recommenders: Survey and emerging trends
Li Chen
*
, Pearl Pu
*
Corresponding author for this work
Department of Computer Science
Research output
:
Contribution to journal
›
Journal article
›
peer-review
228
Citations (Scopus)
Overview
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Dive into the research topics of 'Critiquing-based recommenders: Survey and emerging trends'. Together they form a unique fingerprint.
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Engineering
Future Trend
100%
End-Users
100%
Limitations
100%
User Profile
100%
Emerging Trend
100%
Classification
100%
Content Knowledge
100%
Keyphrases
Recommender
100%
Recommender Systems
75%
Motivation
25%
Content-based
25%
User Feedback
25%
Preference-based
25%
User Study
25%
Critiquing Feedback
25%
Online Websites
25%
User Profile
25%
Classification Analysis
25%
Language-based
25%
Hybrid Framework
25%
Natural Language
25%
Content Knowledge
25%
Conversational Style
25%
Detailed Survey
25%
MovieLens
25%
Computer Science
Recommender System
100%
Conversational Style
33%
Content Knowledge
33%
Categorization Analysis
33%