A three-layer model on users’ interests mining

Author:

Yang Renfeng1,Xie Wenbo1,Chen Duanbing2

Affiliation:

1. School of Computer Science and Engineering and Big Data Research Center, University of Electronic Science and Technology of China, People’s Republic of China

2. School of Computer Science and Engineering, Big Data Research Center and The Center for Digitized Culture and Media, University of Electronic Science and Technology of China, People’s Republic of China

Abstract

With the advent of big data era, social media plays an important role in many areas such as security and finance. Researchers pay more attention on mining users’ interests through the social media data. A three-layer model (TLM) based on keyword extracting is proposed to mine users’ interests, which includes candidate words extracting, semantic structures analysing and interest words ranking. The TLM mainly focuses on both self-importance and semantic-importance of interest words. In addition, the TLM also considers the interest drifting to track long-term and short-term interests of users. Experiments conducted on 10 SINA Weibo datasets show that TLM is more efficient than existing methods to identify users’ interests based on hit rate.

Funder

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems

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1. Information Science-Knowledge Management-HCI-Project Management-CRM Models-Software Processes:;Computational Science and Its Applications – ICCSA 2020;2020

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