Improving Predictions with an Ensemble of Linguistic Approach and Matrix Factorization

被引：0

作者：

Angioni, Manuela ^{[1
]}

Clemente, Maria Laura ^{[1
]}

Tuveri, Franco ^{[1
]}

机构：

[1] Ctr Adv Studies Res & Dev Sardinia, CRS4, Parco Sci & Tecnol,Ed 1, I-09010 Pulam, CA, Italy

来源：

WEB INFORMATION SYSTEMS AND TECHNOLOGIES, WEBIST 2015 | 2016年 / 246卷

关键词：

Opinion mining; Sentiment analysis; Text categorization; Collaborative filtering; Matrix factorization; Latent factors; Ensemble methods;

D O I：

10.1007/978-3-319-30996-5_9

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper extends a previous work done by the same authors [1] having the aim of improving the predictions coming from a matrix factorization based on latent factor models through an ensemble with the predictions obtained by an Opinion Mining methodology based on a linguistic approach. The experimental analysis was carried out on the Yelp business dataset, limited to the Restaurant category. An hypothesis of influence of the restaurant average rating on the number of stars given by the users is tested. An analysis of the meaning of some of the latent factors is shown.

引用

页码：169 / 190

页数：22

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