【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的不斷發(fā)展，電子商務(wù)的不斷興起，BBS、博客、微博的不斷涌現(xiàn)，商家與購(gòu)買者的網(wǎng)上交互日趨頻繁。越來(lái)越多的購(gòu)買者在使用產(chǎn)品后，將產(chǎn)品的評(píng)論發(fā)表在網(wǎng)上，評(píng)論的數(shù)量與日俱增，評(píng)論的本身口語(yǔ)化較多并呈非結(jié)構(gòu)化。商家在決策市場(chǎng)供求關(guān)系、潛在購(gòu)買者在購(gòu)買產(chǎn)品時(shí)，若從海量的產(chǎn)品評(píng)論中人工的挑選出自己關(guān)心的信息，是耗時(shí)和費(fèi)力的，并帶有片面性和滯后性。因此搜索引擎在當(dāng)今互聯(lián)網(wǎng)中扮演著重要的角色，，像百度、谷歌這樣強(qiáng)大的搜索引擎是針對(duì)不同領(lǐng)域、不同種類的通用搜索引擎。在特定的產(chǎn)品評(píng)論領(lǐng)域中，卻顯得力不從心。所以，在這樣的背景下，一款具有情感分類的產(chǎn)品評(píng)論垂直搜索引擎的研究與開發(fā)是很有必要的。 在國(guó)內(nèi)外研究現(xiàn)狀的基礎(chǔ)上，針對(duì)中文產(chǎn)品評(píng)論文本中評(píng)價(jià)對(duì)象的識(shí)別、評(píng)價(jià)短語(yǔ)的識(shí)別、評(píng)價(jià)對(duì)象與評(píng)價(jià)短語(yǔ)的搭配識(shí)別及評(píng)價(jià)短語(yǔ)的情感傾向性分析，做了進(jìn)一步研究。主要工作如下： （1）在識(shí)別評(píng)價(jià)對(duì)象方法上，利用詞性序列獲取評(píng)價(jià)對(duì)象候選集，并提出了評(píng)價(jià)對(duì)象的完整性和穩(wěn)定性的概念及算法，用來(lái)過(guò)濾評(píng)價(jià)對(duì)象的噪聲。利用評(píng)價(jià)對(duì)象與評(píng)價(jià)短語(yǔ)的同現(xiàn)規(guī)則及評(píng)價(jià)對(duì)象在整篇評(píng)論文本中或整個(gè)語(yǔ)料集中出現(xiàn)的頻率，進(jìn)行評(píng)價(jià)對(duì)象的置信度排序，最終抽取出評(píng)價(jià)對(duì)象。 （2）對(duì)連詞詞典、情感詞詞典、程度詞詞典及否定詞詞典進(jìn)行了完善，用以識(shí)別評(píng)價(jià)短語(yǔ)及分析評(píng)價(jià)短語(yǔ)的情感傾向性。并通過(guò)評(píng)價(jià)對(duì)象與評(píng)價(jià)短語(yǔ)之間關(guān)系的8個(gè)特征，利用支持向量機(jī)來(lái)識(shí)別評(píng)價(jià)對(duì)象與評(píng)價(jià)短語(yǔ)的搭配關(guān)系，最終判斷整篇評(píng)論文本的情感傾向性。 （3）以中文產(chǎn)品評(píng)論文本的情感傾向?yàn)榛A(chǔ)，利用目前流行的SSH框架、mysql數(shù)據(jù)庫(kù)及開源軟件包lucene，構(gòu)建了一個(gè)垂直搜索引擎，用戶可以方便、快捷的查詢自己感興趣的相關(guān)信息。 通過(guò)上述的研究所構(gòu)建的具有情感分類的垂直搜索引擎，使得商家和潛在客戶可以從浩如煙海的評(píng)論文章中快速而準(zhǔn)確的找到對(duì)自己有用的信息，具有一定的商業(yè)價(jià)值。提出的中文文本情感分類的研究方法，具有一定的學(xué)術(shù)價(jià)值。
[Abstract]:With the continuous development of Internet technology and the rising of e-commerce, BBSs, blogs, Weibo constantly emerge, the online interaction between merchants and buyers is becoming more and more frequent. More and more buyers post product reviews on the Internet after using the products, the number of comments is increasing, the comments themselves are more colloquial and unstructured. It is time-consuming and laborious for potential buyers to pick out the information they care about from a large number of product reviews when they make decisions on the supply and demand relationship in the market, and it is one-sided and lagging. So search engines play an important role in the Internet today. Powerful search engines like Baidu and Google are aimed at different fields and different kinds of general search engines. In a particular area of product review, however, appears to be inadequate. Therefore, it is necessary to research and develop a vertical search engine with emotion classification for product reviews. Based on the current research situation at home and abroad, this paper makes a further study on the identification of evaluation objects, the identification of evaluation phrases, the collocation identification between evaluation objects and evaluation phrases, and the emotional orientation of evaluation phrases in Chinese product review texts. The main work is as follows: (1) the candidate set of evaluation object is obtained by using part of speech sequence in the method of identifying evaluation object, and the concept and algorithm of integrity and stability of evaluation object are put forward to filter the noise of evaluation object. Using the cooccurrence rule of evaluation object and evaluation phrase and the frequency of the evaluation object appearing in the whole comment text or the whole corpus, the confidence degree of the evaluation object is sorted, and the evaluation object is extracted. (2) the conjunctive dictionary is selected. The dictionary of affective words, the dictionary of degree words and the dictionary of negative words are perfected to identify the evaluation phrases and analyze the affective tendency of the evaluation phrases. Through the eight features of the relationship between the evaluation object and the evaluation phrase, support vector machine is used to identify the collocation relationship between the evaluation object and the evaluation phrase. Finally, the emotional tendency of the whole review text is judged. (3) based on the emotional tendency of the Chinese product review text, a vertical search engine is constructed by using the popular SSH framework MySQL database and open source software package Lucene. Users can easily and quickly query their own interested information. A vertical search engine with emotion classification is constructed through the above research, which enables merchants and potential customers to quickly and accurately find useful information for themselves from a vast number of review articles, which has certain commercial value. The research method of emotion classification of Chinese text has certain academic value.
【學(xué)位授予單位】：湖南工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP391.3

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