Identification of item features in microblogging data

Shih Ting Huang, Pei Shu Li, Hung-Yu Kao

研究成果: Conference contribution

摘要

In recent years, microblogging services have become very popular. The larger volume of real-time information generated by millions of users, more important to extract useful information from the microblogging services will be. In this work, we want to use opinion mining to find the relevant and significant features of items from the microblogging services, like Twitter. We construct a sentiment-based framework to identify the relevant features in microblogging. Our method consists of two stages. First, the data process stage processes the raw data from microblogging services. Then, in second stage we extract the relevant features by the sentiment characteristics from these messages and utilize these extracted features to construct the relevant feature network and group them according their concepts relations. Therefore, our system could be applied for knowing the characteristics of a product quickly and explicitly. In our experiments, our system can identify the popular item features in different domains effectively and the same concept features can cluster together in small groups.

原文English
主出版物標題TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
發行者Institute of Electrical and Electronics Engineers Inc.
頁面396-403
頁數8
ISBN(電子)9781467396066
DOIs
出版狀態Published - 2016 二月 12
事件Conference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan
持續時間: 2015 十一月 202015 十一月 22

出版系列

名字TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence

Other

OtherConference on Technologies and Applications of Artificial Intelligence, TAAI 2015
國家Taiwan
城市Tainan
期間15-11-2015-11-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

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