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題名 Sentiment Classification for Web Search Results 作者 楊亨利
Yang, Heng-Li
Huang, Hung-Chang貢獻者 資管系 關鍵詞 Opinion mining ; Sentiment analysis ; Sentiment classification ; Web opinions ; Google search 日期 2019-03 上傳時間 2-九月-2020 09:16:40 (UTC+8) 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. 關聯 Journal of Internet Technology, Vol.20, No.7, pp.2043-2053 資料類型 article dc.contributor 資管系 dc.creator (作者) 楊亨利 dc.creator (作者) Yang, Heng-Li dc.creator (作者) Huang, Hung-Chang dc.date (日期) 2019-03 dc.date.accessioned 2-九月-2020 09:16:40 (UTC+8) - dc.date.available 2-九月-2020 09:16:40 (UTC+8) - dc.date.issued (上傳時間) 2-九月-2020 09:16:40 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/131416 - dc.description.abstract (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. dc.format.extent 863538 bytes - dc.format.mimetype application/pdf - dc.relation (關聯) Journal of Internet Technology, Vol.20, No.7, pp.2043-2053 dc.subject (關鍵詞) Opinion mining ; Sentiment analysis ; Sentiment classification ; Web opinions ; Google search dc.title (題名) Sentiment Classification for Web Search Results dc.type (資料類型) article
