A Hybrid Approach to Making Recommendations and Its Application to the Movie Domain

Authors:
Shawn Grant;Gordon I. McCalla
Affiliations:
-;-
Venue:
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Year:
2001

Citing 12
Cited 3

Using collaborative filtering to weave an information tapestry

Communications of the ACM - Special issue on information filtering
A case-based approach to intelligent information retrieval

SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Social information filtering: algorithms for automating “word of mouth”

CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommender systems

Communications of the ACM
Fab: content-based, collaborative recommendation

Communications of the ACM
Recommendation as classification: using social and content-based information in recommendation

AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Feature-based and Clique-based User Models for Movie Selection: A Comparative Study

User Modeling and User-Adapted Interaction
The State of the Art in Text Filtering

User Modeling and User-Adapted Interaction
Conceptual Indexing: Practical Large-Scale AI for Efficient Information Access

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Social Choice Theory and Recommender Systems: Analysis of the Axiomatic Foundations of Collaborative Filtering

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
PTV: Intelligent Personalised TV Guides

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Cliche Recognition in Legacy Software: A Scalable, Knowledge-Based Approach

WCRE '97 Proceedings of the Fourth Working Conference on Reverse Engineering (WCRE '97)

An efficient collaborative recommender system based on k-separability

ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
A Hybrid Movie Recommender Based on Ontology and Neural Networks

GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Scaling down candidate sets based on the temporal feature of items for improved hybrid recommendations

ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization

Quantified Score

Hi-index	0.00

Visualization

Abstract

There are two main techniques used to capture an individual's personal preferences in order to make recommendations to them about various items of interest: feature-based and clique-based. In this paper we present an approach that can use either technique or a hybrid of the two. Features are captured in the granularity knowledge formalism, giving the feature-based approach more representational power than in most systems. But, the most novel feature of the approach is its ability to use a hybrid technique, which aims to combine the advantages of both feature-based and clique-based approaches while minimising the disadvantages. The hybrid technique also allows for the construction of a personalised explanation to accompany the recommendation. A prototype for the movie domain, MovieMagician, has been developed. A formative evaluation of this prototype has been undertaken in all of its modes: feature-based, clique-based, and hybrid. Other evidence of effectiveness has also been gathered.