出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The huge volume of online reviews makes it difficult for a human to process and extract all
significant information to make decisions. As a result, there has been a trend to develop systems
that can automatically summarize opinions from a set of reviews. In this respect, the automatic
classification and information extraction from users’ comments, also known as sentiment
analysis (SA) becomes vital to offer users the best responses to users’ queries, based on their
preferences. In this paper, a novel system hat offers personalized user experiences and solves
the semantic-pragmatic gap was presented. Having a system for forecasting sentiments might
allow us, to extract opinions from the internet and predict online user’s favorites, which could
determine valuable for commercial or marketing research. The data used belongs to the tagged
corpus positive and negative processed movie reviews introduced by Pang and Lee[1]. The
results show that even when a small sample is used, sentiment analysis can be done with high
accuracy if appropriate natural language processing algorithms applied.
关键词：Machine Learning; Big Data; Natural Language Processing; Sentiment Analysis
