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Author Ishikawa, M. ♦ Geczy, P. ♦ Izumi, N. ♦ Yamaguchi, T.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Technological innovation ♦ Probability distribution ♦ Information filtering ♦ Intelligent agent ♦ Information Diffusion ♦ Information analysis ♦ Uniform resource locators ♦ Knowledge management technology ♦ Databases ♦ Collaborative filtering ♦ Innovator Theory ♦ Collaborative work ♦ Information filters ♦ Marketing and sales ♦ Long Tail ♦ Recommender System
Abstract 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.
Description Author affiliation: ITRI, Nat. Inst. of Adv. Ind. Sci. & Technol., Tokyo (Geczy, P.; Izumi, N.) || Kei Univ., Yokohama (Ishikawa, M.; Yamaguchi, T.)
ISBN 9780769534961
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-12-09
Publisher Place Australia
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 2.68 MB
Page Count 4
Starting Page 785
Ending Page 788

Source: IEEE Xplore Digital Library