Internet public informatioan text data mining and intelligence influence analysis for user intent understanding

Issue title: Special Section: Fuzzy Logic for Analysis of Clinical Diagnosis and Decision-Making in Health Care

Article type: Research Article

Authors: Wu, Shaofei^{a; b; *}

Affiliations: [a] Hubei Province Key Laboratory of Intelligent Robots, Wuhan Institute of Technology, Wuhan, P.R. China | [b] School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, P.R. China

Correspondence: [*] Corresponding author. Shaofei Wu, E-mail: wasbfc@yeah.net.

Abstract: We propose models based on SVM, Naïve Bayes and deep learning to solve the consumption intention classification problem. Applying consumption intention mining to prediction tasks in social media. This paper discusses consumption intention towards a certain kind of product, i.e. movie, and uses movie consumption intention as an important feature in box office prediction. We combine consumption intention with traditional features used in the problem of box office prediction, and achieve a outperforms previous work of this problem We build a system based on linear regression which automatically predicts movies’ total box office and opening weekend box office one day prior to the movie’s release date.

Keywords: Text intention mining, SVM, deep learning

DOI: 10.3233/JIFS-179423

Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 487-494, 2020