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Preprocessing and Feature Selection Approach for Efficient Sentiment Analysis on Product Reviews

机译:产品评论高效情感分析的预处理和特征选择方法

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In the recent years opinion mining plays an important role by business analyst before launching a product. Opinion mining mainly concerns about detecting and extracting the feature from various opinion rich resources like review sites, discussion forum, blogs and news corpora so on. The data obtained from those are highly unstructured in nature and very large in volume, therefore data preprocessing plays an essential role in sentiment analysis. Researchers are trying to develop newer algorithm. This research paper attempts to develop a better opinion mining algorithm and the performance has been worked out.
机译:在近年来,矿业在推出产品之前,挖掘在商业分析师发挥重要作用。 意见挖掘主要涉及检测和提取来自各种意见丰富资源的特征,如审查网站,讨论论坛,博客和新闻语料库等等。 从那些获得的数据本质上是高度非结构化的,体积非常大,因此数据预处理在情感分析中起着重要作用。 研究人员正试图开发较新的算法。 本研究论文试图制定更好的意见采矿算法,并且效果已经解决了。

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