A Timeline Significance Based Method for Event Detection and Tracking of Online News

• Main Authors: Mu-Chieh Yang, 楊慕潔
• Other Authors: Cheng-Jye Luh
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/02218191763714742393

碩士 === 元智大學 === 資訊管理學系 === 94 === This study proposes a timeline significance based method for event detection and tracking of online news. This method calculates a term’s weight in a document by its number of occurrences and a χ2-statistic value dependent on the time interval in which the document occurs. Moreover, this method expands the feature terms of a document to include additional terms that frequently occur together with some of the original feature terms and raises the relevant terms’ weights by a timeline based term co-occurrence analysis. Experimental results on Chinese and English online news indicate that the proposed method significantly out-performed the traditional TFIDF method. The proposed method achieved an average improvement of 25.25% on the F1 measure with timeline significance only. With further term expansion, the proposed method achieved an additional average improvement of 4.26% on the F1 measure.