Social Recommendation with Time and Sentiment Analysis

被引：2

作者：

Giammarino, Domenico ^{[1
]}

Gurini, Davide Feltoni ^{[1
]}

Micarelli, Alessandro ^{[1
]}

Sansonetti, Giuseppe ^{[1
]}

机构：

[1] Roma Tre Univ, Via Vasca Navale 79, I-00146 Rome, Italy

来源：

ADJUNCT PUBLICATION OF THE 25TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'17) | 2017年

关键词：

User modeling; temporal dynamics; sentiment analysis;

D O I：

10.1145/3099023.3099104

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the increasing information overload, the identification of new users really relevant to the target user becomes more and more complicated. In this paper, we propose a social recommender based on a user model that takes into account not only her interests and preferences, but also their evolution over time and actual nature. To accurately assess the effectiveness of the proposed approach, over 1,600 users were monitored for a full year, thus collecting over 2,700,000 tweets. In this way, it was possible to deeply evaluate the proposed model, also through a comparative analysis with other state-of-the-art social recommender systems.

引用

页码：376 / 380

页数：5

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Gurini, Davide Feltoni ;

Gasparetti, Fabio ;

Micarelli, Alessandro ;

Sansonetti, Giuseppe .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 78 :430-439

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