Abstract：At present, the cost of Chinese story link detection is high，since the miss rate and false rate are high. Concerning this problem, based on multi-vector space model, the paper joined elements (time, site, people, content) correlative word to represent the relevance of the different elements, integrated coherence similarity and cosine similarity with Support Vector Machine (SVM), and then proposed an algorithm which was based on the extraction of elements correlative word. The proposed algorithm complementally expressed the story and provided more evidence for detection; the detection cost was decreased by nearly 11%. Finally, the experimental results show the validity of the proposed algorithm.
陈智敏 蒙祖强 林啟锋. 基于要素提取关联词对的中文报道关系检测[J]. 计算机应用, 2013, 33(01): 182-185.
CHEN Zhimin MENG Zuqiang LIN Qifeng. Chinese story link detection based on extraction of elements correlative word. Journal of Computer Applications, 2013, 33(01): 182-185.
2013, Vol. 33 
