Sentiment Analysis of Tourism Reviews Based on Semantic Lexicon and Machine Learning
WANG Xinyu
Abstract：This paper provides an approach for sentiment analysis of tourism reviews through Internet service by combi‐ning semantic lexicon with machine learning . The approach expresses tourism reviews by adopting Vector Space Model (VSM ) .It reduces dimension of feature space by semantic lexicon .The weights are calculated by term frequency‐inverse document frequency (TF‐IDF) .The tourism reviews are classified by Support Vector Machine (SVM ) .Experimental results show that the proposed approach can make sentiment classification for plenty of tourism reviews efficiently .
Keywords：machine learningsemantic lexiconsentiment analysis
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 578-582,766 )