A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels

碩士 === 國立交通大學 === 資訊管理研究所 === 96 === The convenience of Internet makes enterprises employ Multi-Channel to develop the marketing models. Customers can choose prefer channels to make purchases from enterprises. Integrating and analyzing transactions from Multi-Channel can provide personal recommendat...

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Bibliographic Details
Main Authors:	Yu-Ting Chen, 陳鈺婷
Other Authors:	Duen-Ren Liu
Format:	Others
Language:	zh-TW
Published:	2008
Online Access:	http://ndltd.ncl.edu.tw/handle/41732111723090044682

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spelling	ndltd-TW-096NCTU53960722015-10-13T12:18:06Z http://ndltd.ncl.edu.tw/handle/41732111723090044682 A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels 雙重通路複合式協同過濾之產品推薦研究 Yu-Ting Chen 陳鈺婷碩士國立交通大學資訊管理研究所 96 The convenience of Internet makes enterprises employ Multi-Channel to develop the marketing models. Customers can choose prefer channels to make purchases from enterprises. Integrating and analyzing transactions from Multi-Channel can provide personal recommendation to increase customer loyalty. To reduce the issue of data sparsity in transaction records, this research proposes a Hybrid Collaborative Filtering (CF) in dual channels for product recommendation. The proposed method employs Nearst-Neighbor approach by integrating the User-based CF and Item-based CF. The experimental results show that the proposed hybrid approach in dual channels can improve recommendation quality. Duen-Ren Liu 劉敦仁 2008 學位論文 ; thesis 56 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立交通大學 === 資訊管理研究所 === 96 === The convenience of Internet makes enterprises employ Multi-Channel to develop the marketing models. Customers can choose prefer channels to make purchases from enterprises. Integrating and analyzing transactions from Multi-Channel can provide personal recommendation to increase customer loyalty. To reduce the issue of data sparsity in transaction records, this research proposes a Hybrid Collaborative Filtering (CF) in dual channels for product recommendation. The proposed method employs Nearst-Neighbor approach by integrating the User-based CF and Item-based CF. The experimental results show that the proposed hybrid approach in dual channels can improve recommendation quality.
author2	Duen-Ren Liu
author_facet	Duen-Ren Liu Yu-Ting Chen 陳鈺婷
author	Yu-Ting Chen 陳鈺婷
spellingShingle	Yu-Ting Chen 陳鈺婷 A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
author_sort	Yu-Ting Chen
title	A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
title_short	A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
title_full	A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
title_fullStr	A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
title_full_unstemmed	A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels
title_sort	study of hybrid collaborative filtering for product recommendation in dual channels
publishDate	2008
url	http://ndltd.ncl.edu.tw/handle/41732111723090044682
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A Study of Hybrid Collaborative Filtering for Product Recommendation in Dual Channels

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