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In web pages, the reviews are written in natural language and are unstructured-free-texts scheme. Online product reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. The task of manually scanning through large amounts of review one by one is computational burden and is not practically implemented with respect to businesses...
Most of the previous researches on sentiment analysis concentrate on the binary distinction of positive vs. negative. This paper presents the multi-class sentiment classification problem that attempt to mine the implied rating information from reviews. We use four machine learning methods and two feature selection methods to find out whether or not the multi-class sentiment classification problem...
Recommender System is one of the most important technologies in E-commerce, and the collaborative filtering algorithm is the most widely used technique. In this paper, we proposed an improved collaborative filtering algorithm based on bipartite network, degree of nodes and sort of nodes both have been taken into account. And we only need to calculate the top-N similar neighbors for each target item,...
Online reviews are one of the important information resources for people. This paper focuses on a specific domain-movie review and presents a new model for predicting semantic orientation of reviews, i.e., classifying positive reviews from those negative. Different from traditional algorithms for sentiment classifications, this model integrates grammatical knowledge and takes topic correlations into...
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