Research on Sentiment Classification of Texts Based on SVM
The key problem to solve in a sentiment analysis of texts is the sentiment polarity classifica-tion.Based on the analysis of various factors affecting sentiment classification of texts , it built the senti-ment lexicon , extracted affective characteristics , and weighted sentimental features .Then , it used sup-port vector machine ( SVM) classifier for emotion recognition and text classification .Finally, it performed the classification model with the corpus data sets on the single platform and the Spark distributed compu-ting platform to analyze its classification accuracy and time cost .The experimental results verify the effec-tiveness of the text sentimental polarity categorization model on the single platform and on the spark dis-tributed computing platform .
国家科技期刊平台
NSTL
万方数据
维普
