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User reviews data analysis using opinion mining on web

机译:用户使用网络上的意见挖掘来审查数据分析

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摘要

The web world is thriving with e-commerce these days and the need for online reviews has become crucial. The product reviews guide the customers and help them in making decisions regarding various available products which otherwise would bemuse them. But, one issue hampering this decision making problem is to sift through the huge jumbled piles of reviews available on the vast web. This makes the automatic extraction, summarization, and tracking of the available opinions very beneficial for the customers looking to buy a product. The automatic summarization and classification is different for different domains and varies with the testing situations. Through this paper, we are discussing usefulness of mining the customer opinions (i.e. opinion mining) and experimenting its viability in the mobile domain. Our implementation in mobile domain will be based on three main steps: 1) Applying Part-of-speech Tagging (POST), 2) Rule-Mining and identifying opinion words, 3) Summarizing and displaying the end results.
机译:如今,随着电子商务的兴起,网络世界蓬勃发展,对在线评论的需求变得至关重要。产品评论可指导客户,并帮助他们做出有关各种可用产品的决定,否则这些产品将对他们造成困扰。但是,阻碍这一决策问题的一个问题是筛查庞大的网络上堆积如山的评论。这使得对可用意见的自动提取,汇总和跟踪对于希望购买产品的客户而言非常有益。自动汇总和分类对于不同的域是不同的,并随测试情况而变化。通过本文,我们正在讨论挖掘客户意见(即意见挖掘)的有用性并在移动领域中试验其可行性。我们在移动领域的实现将基于三个主要步骤:1)应用词性标记(POST),2)规则挖掘和识别意见词,3)汇总和显示最终结果。

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