Supervised Learning Approaches for Rating Customer Reviews
نویسندگان
چکیده
منابع مشابه
Supervised Learning Approaches for Rating Customer Reviews
Social media has become highly popular in recent years that people are expressing their views, thoughts about any product, movie through reviews. Reviews are having a great influence on people and decisions made by them. This has led researchers and market analyzers to analyze the opinions of users in reviews and model their preferences. Sometimes reviews are also scored in terms of satisfactio...
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This paper proposes a new approach to aspect-based sentiment analysis. The goal of our algorithm is to obtain a summary of the most positive and the most negative aspects of a specific product, given a collection of free-text customer reviews. Our approach starts by matching handcrafted dependency paths in individual sentences to find opinions expressed towards candidate aspects. Then, it clust...
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In this paper, we address the problem of identifying relevant product aspects in a collection of online customer reviews. Being able to detect such aspects represents an important subtask of aspect-based review mining systems, which aim at automatically generating structured summaries of customer opinions. We cast the task as a terminology extraction problem and examine the utility of varying t...
متن کاملWeakly-Supervised Deep Learning for Customer Review Sentiment Classification
Sentiment analysis is one of the key challenges for mining online user generated content. In this work, we focus on customer reviews which are an important form of opinionated content. The goal is to identify each sentence’s semantic orientation (e.g. positive or negative) of a review. Traditional sentiment classification methods often involve substantial human efforts, e.g. lexicon constructio...
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We investigate the problem of personalized reviewbased rating prediction which aims at predicting users’ ratings for items that they have not evaluated by using their historical reviews and ratings. Most of existing methods solve this problem by integrating topic model and latent factor model to learn interpretable user and items factors. However, these methods cannot utilize word local context...
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ژورنال
عنوان ژورنال: Journal of Intelligent Systems
سال: 2010
ISSN: 2191-026X,0334-1860
DOI: 10.1515/jisys.2010.19.1.79