摘要近年来，网络购物已成为人们购物的重要途径之一，在使用产品之后顾客往往被要求填写商品评价以供他人参考。本项研究的目的就在于挖掘并且总结给定商品的所有用户评论，并以结构化的形式呈现，让顾客和生产商能够简单明了的获得需要的商品评价信息。不同于以往的文本总结，我们的总结方法是基于所挖掘出的商品特征的，只对评论中提到的商品特征进行总结并以结构化形式展现。工作流程划分如下：（1）挖掘那些受到顾客评价的商品特征；（2）识别出评论中的观点语句并且判定每个语句是肯定的还是否定的；（3）总结结果并以结构化形式展现。最后我们进行了实验，通过对网上商城的商品评论数据进行总结对比来验证我们的评价系统的有效性。60134

关键词  文本挖掘   情感分类   商品评论   特征抽取

毕业设计说明书（毕业论文）外文摘要

Title        Mining and Summarizing Customer Reviews   on the E-commerce Websites                            

Abstract

As e-commerce is becoming more and more popular recent years, people buying products on the Web are often asked to review the products that they have purchased for others to reference. In this research, we aim to mine and to summarize all the customer reviews of a product and show them in chats for merchants and customers to get the information of products easily. This summarization task is different from traditional text summarization because we only mine the features of the product on which the customers have expressed their opinions and we show the results in chats. Our task is performed in three steps: (1) mining product features that have been commented on by customers; (2) identifying opinion sentences in each review and deciding whether each opinion sentence is positive or negative; (3) summarizing the results. Finally, Our experimental results using reviews of a number of products sold online demonstrate the effectiveness of the techniques.

Keywords  Text mining, Sentiment classification, Products’ reviews, Feature extraction

1 概述 5

1.1 研究背景 5

1.2 研究目的 5

2 相关工作 6

2.1 主题类型分类 7

2.2 情感分类 7

2.3 文本总结 8

2.4 术语挖掘 9

3 系统设计与实现 9

3.1 获取评论 10

3.2 分句与词性标注（POS） 11

3.3 高频特征识别 12

3.3.1 高频率特征 12

3.3.2 Apriori算法 13

3.3.3 剪枝 15

3.4 观点词汇提取 面向电商评论的特征挖掘与观点总结技术:http://www.751com.cn/jisuanji/lunwen_65512.html