A Two-Stage Learning Method for Response Prediction

Kuan Hsi Chen, Zih Yun Ting, Jia Ying Shen, Yuh-Jyh Hu, Tyne Liang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Social networks have become a popular and powerful communication platform as the mobile technology evolves. To evaluate the influence of a message on a social network, response prediction is crucial in modeling the message propagation and interaction among users. To predict whether a new message will receive responses, we propose a two-stage learning method using a new set of features derived from the messages, the users and theirresponding behaviors. This method first clusters the messages, and then learns the different prediction models from the clusters respectively. The central argument for this two-stage strategy is that the classifiers trained separately from the clustered data sets can focus on particular types of data, reduce the effects of noise, and consequently have an overall higher predictive performance than a single classifier trained from the entire data set. We tested the proposed two-stage learner on Plurk, and compared it withother classifiers. The experimental results show that the two-stage learner outperformed the gradient boosting decision tree learner, the logistic function learner, and the support vector machine for not only the predictive accuracy, but also for the efficiency.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
EditorsXindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1336-1341
Number of pages6
ISBN (Electronic)9781467384926
DOIs
StatePublished - 29 Jan 2016
Event15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
Duration: 14 Nov 201517 Nov 2015

Publication series

NameProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Conference

Conference15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
CountryUnited States
CityAtlantic City
Period14/11/1517/11/15

Keywords

  • Response prediction
  • social network

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