Open AccessPredict Consumers’ Automobile Purchase Behavior Based on the Preferences of Explicit Features and Implicit Topic
Author(s) -
Yanan Du,
Qian Yang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022104
Subject(s) - purchasing , construct (python library) , preference , granularity , computer science , feature (linguistics) , order (exchange) , consumer behaviour , tree (set theory) , advertising , marketing , microeconomics , business , mathematics , economics , mathematical analysis , linguistics , philosophy , finance , programming language , operating system
In order to know the role of online reviews in predicting consumers’ automobile purchasing behavior in the social network environment, this paper uses online reviews to construct a consumer interest preference model to obtain consumers’ explicit feature preferences and implicit topic preferences. Based on the preferences of consumers, introduce the tree structure to construct hierarchical prediction model to predict consumers’ purchase behavior. Meanwhile, consider the effect of online interactive comment on consumers’ automobile purchases. Several results are obtained in this paper:(1) The proposed hierarchical model introducing more information could achieve multi-granularity purchase-decision predicting;(2) the predictive effect based on implicit topic preference is better than that based on explicit feature preference; (3) integrating online interactive comments have positive effect in analyzing and predicting consumers’ purchasing behavior.