Mining User Consumption Intention from Social Media Using Domain Adaptive Convolutional Neural Network

Social media platforms are often used by people to express their needs and desires. Such data offer great opportunities to identify users’ consumption intention from user-generated contents, so that better tailored products or services can be recommended. However, there have been few efforts on mining commercial intents from social media contents. In this paper, we investigate the use of social media data to identify consumption intentions for individuals. We develop a Consumption Intention Mining Model (CIMM) based on convolutional neural network (CNN), for identifying whether the user has a consumption intention. The task is domain-dependent, and learning CNN requires a large number of annotated instances, which can be available only in some domains. Hence, we investigate the possibility of transferring the CNN mid-level sentence representation learned from one domain to another by adding an adaptation layer. To demonstrate the effectiveness of CIMM, we conduct experiments on two ...

• Type: Journal
• Year: 2015
• Where: AAAI
• Authors: Xiao Ding, Ting Liu, Junwen Duan, Jian-Yun Nie
• Keywords: AAAI 2015, Intelligent Agents