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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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. |
doi_str_mv | 10.1109/WIIAT.2008.352 |
format | Conference Proceeding |
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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. 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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><subject>Applied computing -- Operations research -- Decision analysis</subject><subject>Collaborative filtering</subject><subject>Collaborative work</subject><subject>Computing methodologies -- Artificial intelligence -- Knowledge representation and reasoning</subject><subject>Information analysis</subject><subject>Information Diffusion</subject><subject>Information filtering</subject><subject>Information filters</subject><subject>Information systems -- Information systems applications -- Data mining</subject><subject>Information systems -- Information systems applications -- Decision support systems</subject><subject>Innovator Theory</subject><subject>Intelligent agent</subject><subject>Knowledge management technology</subject><subject>Long Tail</subject><subject>Marketing and sales</subject><subject>Probability distribution</subject><subject>Recommender System</subject><subject>Technological innovation</subject><subject>Theory of computation -- Logic</subject><subject>Uniform resource locators</subject><isbn>9780769534961</isbn><isbn>0769534961</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNqNkD1LxEAURQdEUNa0NjbprLK--chkAjbLqmsgIEgWy2GSeaOjSUaSWKy_3sT1B1jdC-dyi0PIJYU1pZDfvBTFplozALXmKTshUZ4pyGSecpFLekaicXwHAEoZiFSck9sy9K9xZXwbP2MTug57i0O8n3zrv_2Mit6FoTOTD3185537GpdWvWEYDhfk1Jl2xOgvV2T_cF9tH5PyaVdsN2ViqIQp4calIJFRxhRaBTVyhyCprFMhatkIVBysdWCUsxSoywyiZc5KwVWjgK_I1fHXI6L-HHxnhoMWmYBU5DNNjtQ0na5D-Bg1Bb3Y0L829GJDzzZ0PXh08_76f3v-A0q9YGw</recordid><startdate>20081209</startdate><enddate>20081209</enddate><creator>Ishikawa, Masayuki</creator><creator>Geczy, Peter</creator><creator>Izumi, Noriaki</creator><creator>Yamaguchi, Takahira</creator><general>IEEE Computer Society</general><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20081209</creationdate><title>Long Tail Recommender Utilizing Information Diffusion Theory</title><author>Ishikawa, Masayuki ; Geczy, Peter ; Izumi, Noriaki ; Yamaguchi, Takahira</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a160t-3af506e21228ed80be3fe0616b544b6c4e830ddf0a8fd101f7aeed2fd6438c803</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Applied computing -- Operations research -- Decision analysis</topic><topic>Collaborative filtering</topic><topic>Collaborative work</topic><topic>Computing methodologies -- Artificial intelligence -- Knowledge representation and reasoning</topic><topic>Information analysis</topic><topic>Information Diffusion</topic><topic>Information filtering</topic><topic>Information filters</topic><topic>Information systems -- Information systems applications -- Data mining</topic><topic>Information systems -- Information systems applications -- Decision support systems</topic><topic>Innovator Theory</topic><topic>Intelligent agent</topic><topic>Knowledge management technology</topic><topic>Long Tail</topic><topic>Marketing and sales</topic><topic>Probability distribution</topic><topic>Recommender System</topic><topic>Technological innovation</topic><topic>Theory of computation -- Logic</topic><topic>Uniform resource locators</topic><toplevel>online_resources</toplevel><creatorcontrib>Ishikawa, Masayuki</creatorcontrib><creatorcontrib>Geczy, Peter</creatorcontrib><creatorcontrib>Izumi, Noriaki</creatorcontrib><creatorcontrib>Yamaguchi, Takahira</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ishikawa, Masayuki</au><au>Geczy, Peter</au><au>Izumi, Noriaki</au><au>Yamaguchi, Takahira</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Long Tail Recommender Utilizing Information Diffusion Theory</atitle><btitle>2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology</btitle><stitle>WIIATW</stitle><date>2008-12-09</date><risdate>2008</risdate><volume>1</volume><spage>785</spage><epage>788</epage><pages>785-788</pages><isbn>9780769534961</isbn><isbn>0769534961</isbn><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.</abstract><cop>Washington, DC, USA</cop><pub>IEEE Computer Society</pub><doi>10.1109/WIIAT.2008.352</doi><tpages>4</tpages></addata></record> |
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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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language | eng |
recordid | cdi_acm_books_10_1109_WIIAT_2008_352 |
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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