LS-SVM:effective algorithm of news topic tracking
Xianfei Zhang · Jisuanji yingyong yanjiu · 2008
Topic tracking is to track news trend which someone is interested in it.Its advantages lie in dynamic tracking based on text model and understanding,so it involves in more text express and semantic understanding.LS-SVM first analyzed text using LSI(latent semantic indexing),which achieved semantic-based character reduction and text express,then combined SVM to complete semantic-based topic tracking.The result of experiment shows,compared to conventional methods,LS-SVM can improve performance of topic tracking effectively and reduce fault and fail rate of topic tracking.