AMAZING: A sentiment mining and retrieval system

AMAZING: A sentiment mining and retrieval system
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令人惊叹:情感挖掘和检索系统

DOI:
10.1016/j.eswa.2008.09.035
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发表时间:
2009-04
影响因子:
8.5
通讯作者:
Li, Qiudan
Li, Qiudan
中科院分区:
计算机科学1区
文献类型:
--
作者:
Dai, Ruwei;Miao, Qingliang;Li, Qiudan

文献摘要

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随着电子商务的快速发展,电子商务网站上出现了大量的客户评论。一般来说,潜在客户通常涉水通过大量的在线评论,以作出明智的决定.然而,检索情感信息相关的客户的兴趣仍然是具有挑战性的。开发一个情感挖掘和检索系统是克服客户评论中信息过载问题的一个很好的方法。在本文中,我们提出了一个情感挖掘和检索系统,挖掘有用的知识,从消费者的产品评论,利用数据挖掘和信息检索技术。为满足用户的信息需求,提出了一种综合考虑时间观点质量(TOQ)和相关性的排序机制。此外,该系统还能直观地显示用户评价的趋势变化和正负评价的比较。在真实数据集上的实验结果表明了该系统的可行性和有效性。
With the rapid growth of e-commerce, there are a great number of customer reviews on the e-commerce websites. Generally, potential customers usually wade through a lot of on-line reviews in order to make an informed decision. However, retrieving sentiment information relevant to customer’s interest still remains challenging. Developing a sentiment mining and retrieval system is a good way to overcome the problem of overloaded information in customer reviews. In this paper, we propose a sentiment mining and retrieval system which mines useful knowledge from consumer product reviews by utilizing data mining and information retrieval technology. A novel ranking mechanism taking temporal opinion quality (TOQ) and relevance into account is developed to meet customers’ information need. Besides the trend movement of customer reviews and the comparison between positive and negative evaluation are presented visually in the system. Experimental results on a real-world data set show the system is feasible and effective.
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