Convolutional Matrix Factorization for Recommendation Explanation

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Title: Convolutional Matrix Factorization for Recommendation Explanation
Authors: Lu, Yichao
Dong, Ruihai
Smyth, Barry
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Date: 11-Mar-2018
Online since: 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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACS
Series/Report no.: Article No. 34
Copyright (published version): 2018 the Authors
Keywords: Recommendation explanationConvulutional neural networkMatrix factorizationCustomer reviews
DOI: 10.1145/3180308.3180343
Language: en
Status of Item: Peer reviewed
Is part of: 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
Appears in Collections:Insight Research Collection

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