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Convolutional Matrix Factorization for Recommendation Explanation
Author(s)
Date Issued
2018-03-11
Date Available
2019-04-15T09:00:36Z
Abstract
In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACS
Series
Article No. 34
Copyright (Published Version)
2018 the Authors
Language
English
Status of Item
Peer reviewed
Journal
IUI'18 Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion
Conference Details
The 23rd International Conference on Intelligent User Interfaces Companion, Tokyo, Japan, 07-11 March 2018
This item is made available under a Creative Commons License
File(s)
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Name
insight_publication.pdf
Size
325.08 KB
Format
Adobe PDF
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