本文選題：情感分析　切入點：用戶評論　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：互聯(lián)網(wǎng)技術(shù)的不斷發(fā)展促進(jìn)了電子商務(wù)發(fā)展,網(wǎng)絡(luò)購物與人們的生活越來越密切,這種情況下便產(chǎn)生了大量針對各種商品和服務(wù)的用戶評論數(shù)據(jù),這些評論對用戶和商家來講都具有很重要的利用價值。但是互聯(lián)網(wǎng)信息變化很大很快,網(wǎng)絡(luò)上用戶評論信息數(shù)據(jù)量很大,同時也具有很強(qiáng)的隨意性,這導(dǎo)致大量的信息中有很多垃圾信息。如果通過人工的方式去處理會耗費大量的人力物力成本,效果也不理想。因此需要計算機(jī)來幫助用戶和商家獲取信息并進(jìn)行分析,文本情感分析技術(shù)則能夠很好的處理這項任務(wù)。本文以文本情感分析技術(shù)理論為指導(dǎo),通過對產(chǎn)品評論的情感分析方法進(jìn)行研究,設(shè)計出一套用戶評論情感分析系統(tǒng),該系統(tǒng)能夠根據(jù)用戶的需求自動的獲取網(wǎng)上的信息,并對網(wǎng)上的垃圾信息進(jìn)行過濾,然后使用情感分析技術(shù)對這些評論數(shù)據(jù)進(jìn)行分析處理,自動的識別出用戶對相關(guān)產(chǎn)品以及產(chǎn)品屬性的喜好程度,歸納出商品的正負(fù)向評論信息以及涉及到的產(chǎn)品屬性。最終通過可視化技術(shù)將結(jié)果展示給用戶和企業(yè)。主要研究內(nèi)容如下:(1)在雙向傳播算法的基礎(chǔ)上提出一種基于規(guī)則和基于統(tǒng)計相結(jié)合的產(chǎn)品屬性和用戶觀點抽取方法。根據(jù)中文語言詞語的特殊性,將中文語言中的依存句法關(guān)系這種規(guī)則與雙向傳播這種基于統(tǒng)計的算法結(jié)合起來,從而能夠提高抽取產(chǎn)品屬性和用戶觀點詞的準(zhǔn)確率,然后通過點互信息法對抽取信息進(jìn)行過濾,將冗余信息去除掉,最后形成產(chǎn)品屬性和用戶觀點詞的對應(yīng)關(guān)系;(2)設(shè)計一個改進(jìn)的詞典法,將機(jī)器學(xué)習(xí)中的支持向量機(jī)算法引入。首先手工制作出一套情感詞典,使用詞典法對整個文本的情感值進(jìn)行計算,這一步對整個文本進(jìn)行初步的篩選,然后利用支持向量機(jī)對文本進(jìn)行分類處理,經(jīng)過實驗分析將支持向量機(jī)引入情感極性識別中效果比較好。(3)設(shè)計出一套可視化展示方案,將文本情感分析的結(jié)果通過信息可視化的方式展示出來,根據(jù)不同的結(jié)果選擇不同的圖形進(jìn)行展示。并對效果進(jìn)行評估調(diào)查。(4)最后對整個系統(tǒng)的效果進(jìn)行評測,并結(jié)合可視化設(shè)計的效果進(jìn)行用戶體驗方面的滿意度調(diào)查,制作調(diào)查問卷,通過對調(diào)查問卷數(shù)據(jù)進(jìn)行分析總結(jié)。
[Abstract]:The continuous development of Internet technology has promoted the development of electronic commerce, and online shopping is becoming more and more close to people's life. In this case, a large number of user comments on a variety of goods and services have been generated. These comments are of great value to users and businesses. But the information on the Internet changes very quickly, and the amount of data that users comment on on the Internet is very large, and at the same time, it has a strong arbitrariness. This leads to a lot of junk information in a large amount of information. If it is handled manually, it will cost a lot of manpower and material resources, and the effect will not be satisfactory. Therefore, computers are needed to help users and businesses to obtain information and analyze it. The text emotion analysis technology can deal with this task very well. Under the guidance of the text emotion analysis technology theory, this paper designs a set of user comment emotion analysis system through the research on the emotion analysis method of product comment. The system can automatically obtain the information of the network according to the needs of the users, filter the garbage information on the network, and then use the emotion analysis technology to analyze and process these comments data. Automatically identify the user's preference for related products and product attributes, The positive and negative comment information of goods and the product attributes involved are summarized. Finally, the results are presented to users and enterprises through visualization technology. The main research contents are as follows: 1) A basis based on bidirectional propagation algorithm is proposed. Product attribute and user viewpoint extraction method based on rules and statistics. According to the particularity of Chinese language words, By combining the rule of dependency syntax in Chinese language with the statistical algorithm of bidirectional propagation, the accuracy of extracting product attributes and user view words can be improved. Then filter the extracted information through the point mutual information method, remove the redundant information, and finally form the corresponding relationship between product attributes and user opinion words. (2) Design an improved dictionary method. The support vector machine (SVM) algorithm in machine learning is introduced. Firstly, a set of emotion dictionary is made by hand, and the emotion value of the whole text is calculated by using the dictionary method. Then we use support vector machine to classify the text and introduce support vector machine into emotional polarity recognition through experimental analysis. A visual display scheme is designed. The result of text emotion analysis is displayed through information visualization, and different graphics are selected according to different results. Finally, the effect of the whole system is evaluated. Combined with the effect of visual design, the satisfaction survey of user experience is carried out, the questionnaire is made, and the data of the questionnaire is analyzed and summarized.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.52;TP391.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 胡龍茂;;中文在線評論中產(chǎn)品特征抽取研究[J];電腦知識與技術(shù);2014年33期

2 楊震;賴英旭;段立娟;李玉擰;;基于上下文重構(gòu)的短文本情感極性判別研究[J];自動化學(xué)報;2012年01期

3 張輝;白長虹;李儲鳳;;消費者網(wǎng)絡(luò)購物意向分析——理性行為理論與計劃行為理論的比較[J];軟科學(xué);2011年09期

4 王衛(wèi)平;孟翠翠;;基于句法分析與依存分析的評價對象抽取[J];計算機(jī)系統(tǒng)應(yīng)用;2011年08期

5 李慶艷;金鐸;張文安;張濤;;移動電子商務(wù)發(fā)展趨勢探討[J];電信科學(xué);2011年06期

6 趙妍妍;秦兵;劉挺;;文本情感分析[J];軟件學(xué)報;2010年08期

7 孫立偉;何國輝;吳禮發(fā);;網(wǎng)絡(luò)爬蟲技術(shù)的研究[J];電腦知識與技術(shù);2010年15期

8 劉鴻宇;趙妍妍;秦兵;劉挺;;評價對象抽取及其傾向性分析[J];中文信息學(xué)報;2010年01期

9 樊娜;蔡皖東;趙煜;李慧賢;;中文文本情感主題句分析與提取研究[J];計算機(jī)應(yīng)用;2009年04期

10 徐軍;丁宇新;王曉龍;;使用機(jī)器學(xué)習(xí)方法進(jìn)行新聞的情感自動分類[J];中文信息學(xué)報;2007年06期

相關(guān)博士學(xué)位論文 前2條

1 劉倩;觀點挖掘中評價對象抽取方法的研究[D];東南大學(xué);2016年

2 郝媛媛;在線評論對消費者感知與購買行為影響的實證研究[D];哈爾濱工業(yè)大學(xué);2010年

相關(guān)碩士學(xué)位論文 前2條

1 王沛;文本傾向性分析中的評價對象抽取與消歧研究[D];哈爾濱工業(yè)大學(xué);2013年

2 譚倩霞;在線評論對消費者購買意愿的影響研究[D];湖南大學(xué);2013年

，

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