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篇名 |
Sentiment Classification for Web Search Results
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並列篇名 | Sentiment Classification for Web Search Results |
作者 | Heng-Li Yang、Hung-Chang Huang |
英文摘要 | This study proposes an approach to display Google search results with different classes of sentimental orientations: (1) positive, negative, or neutral, (2) positive or negative, (3) positive or non-positive, and (4) negative or non-negative. A prototype, called as GSCS was also constructed to retrieve the search results of smartphones, tablets, and notebooks from Google. With a single click, the GSCS would help users easily get the opinions that they want to meet their different needs. For classifying documents, we suggest a two-level sentiment classification approach. At the sentence level, sentences are first classified into positive, negative, or neutral, and then the sentiment labels of the sentences were used in the classification of documents. We also demonstrated that our two-level sentiment classification (first sentence level and then document level) outperformed the document-level-only sentiment classification. |
起訖頁 | 2043-2053 |
關鍵詞 | Opinion mining、Sentiment analysis、Sentiment classification、Web opinions、Google search |
刊名 | 網際網路技術學刊 |
期數 | 201912 (20:7期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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