Medical Advertising Content Filtering System in Online Knowledge Sharing Service,ERICDATA高等教育知識庫
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篇名
Medical Advertising Content Filtering System in Online Knowledge Sharing Service
並列篇名
Medical Advertising Content Filtering System in Online Knowledge Sharing Service
作者 Yoosin KimTae Yun KimSang Hyun Choi
英文摘要
Online knowledge sharing service such as Q&A communities in the Web is a representative service as collective intelligence among people and a critical web service to entice online consumers as well. A huge volume of Q&A content is generated and shared in real time, however there are also uncertain information including not only valuable knowledge but also commercial data such as advertisements, marketing, and even wrong information. That commercial content is able to lead online-users to controversy. This study proposes a content filtering system in the knowledge sharing community to classify whether the information is commercial or not. The filtering system applies linguistic feature sets and employs a support vector machines algorithm in machine learning methods to classify whether the information in the knowledge sharing community is commercial or not. To build the algorithm and validate the system, we set the target domain within the healthcare content and gathered question and answer content about lung cancer of knowledge sharing service in a Korean web-portal site, Naver.com. As the result, the proposed system accomplished accuracy average 84.0% with the Ads words and the document length.
起訖頁 887-894
關鍵詞 Lung cancerQ&A communityMachine learningText mining
刊名 網際網路技術學刊  
期數 201805 (19:3期)
出版單位 台灣學術網路管理委員會
DOI 10.3966/160792642018051903024  複製DOI
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