Long Tail Recommender Utilizing Information Diffusion Theory

Our approach aims to provide a mechanism for recommending long tail items to knowledge workers. The approach employs collaborative filtering using browsing features of identified key population of the diffusion of information. We conducted analytic experiment for a novel recommendation algorithm bas...

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Hauptverfasser: Ishikawa, Masayuki, Geczy, Peter, Izumi, Noriaki, Yamaguchi, Takahira
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creator Ishikawa, Masayuki
Geczy, Peter
Izumi, Noriaki
Yamaguchi, Takahira
description Our approach aims to provide a mechanism for recommending long tail items to knowledge workers. The approach employs collaborative filtering using browsing features of identified key population of the diffusion of information. We conducted analytic experiment for a novel recommendation algorithm based on the browsing features of identified selected users and discovered that the first 10 users accessing a particular page play the key role in information spread. The evaluation indicated that our approach is effective for long tail recommendation.
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identifier ISBN: 9780769534961
ispartof 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008, Vol.1, p.785-788
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Applied computing -- Operations research -- Decision analysis
Collaborative filtering
Collaborative work
Computing methodologies -- Artificial intelligence -- Knowledge representation and reasoning
Information analysis
Information Diffusion
Information filtering
Information filters
Information systems -- Information systems applications -- Data mining
Information systems -- Information systems applications -- Decision support systems
Innovator Theory
Intelligent agent
Knowledge management technology
Long Tail
Marketing and sales
Probability distribution
Recommender System
Technological innovation
Theory of computation -- Logic
Uniform resource locators
title Long Tail Recommender Utilizing Information Diffusion Theory
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