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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2007 |
| 形態種別 | 研究論文（国際会議プロシーディングス） |
| 査読 | 査読あり |
| 標題 | Fair news reader: Recommending news articles with different sentiments based on user preference |
| 執筆形態 | その他 |
| 掲載誌名 | KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT I, PROCEEDINGS |
| 出版社・発行元 | SPRINGER-VERLAG BERLIN |
| 巻・号・頁 | 4692,pp.612-+ |
| 著者・共著者 | Yukiko Kawai,Tadahiko Kumamoto,Katsurni Tanaka |
| 概要 | We have developed a news portal site called Fair News Reader (FNR) that recommends news articles with different sentiments for a user in each of the topics in which the user is interested. FNR can detect various sentiments of news articles, and determine the sentimetal preferences of a user based on the sentiments of previously read articles by the user. While there are many news portal sites on the Web, such as GoogleNews, Yahoo!, and MSN News, they can not recommend and present news articles based on the sentiments they are likely to create since they simply select articles based on whether they contain users-pecified keywords. FNR collects and recommends news articles based on the topics in which the user is interested and the sentiments the articles are likely to create. Eight of the sentiments each article is likely to create are represented by an "article vector" with four elements. Each element corresponds to a measure consisting of two symmetrical sentiments. The sentiments of the articles previously read with respect to a topic are then extracted and represented as a "user vector". Finally, based on a comparison between the user and article vectors in each topic, FNR. recommends articles that have symmetric sentiments against the sentiments of read articles by the user for fair reading about the topic. Evaluation of FNR using two experiments showed that the user vectors can be determined by FNR based on the sentiments of the read articles about a topic and that it can provide a unique interface with categories containing the recommended articles. |
| DOI | 10.1007/978-3-540-74819-9_76 |
| ISSN | 0302-9743 |
| DBLP ID | conf/kes/KawaiKT07 |
| PermalinkURL | http://dblp.uni-trier.de/db/conf/kes/kes2007-1.html#conf/kes/KawaiKT07 |