本文關(guān)鍵詞： 在線評論 文本挖掘 情感詞典 情感效應(yīng) 營銷效應(yīng)　出處：《統(tǒng)計與決策》2017年09期 　論文類型：期刊論文

【摘要】：大量的在線評論文本數(shù)據(jù),對汽車制造業(yè)的產(chǎn)品創(chuàng)新、精準(zhǔn)營銷具有重要的實用價值。傳統(tǒng)的文本挖掘多關(guān)注情感極性強度而忽視了情感營銷效應(yīng),挖掘結(jié)果與企業(yè)需求差異較大。文章利用大連理工、中國知網(wǎng)等情感詞典和豐富的汽車語料庫,采取了基于CRF機器學(xué)習(xí)的情感詞自動獲取方法,構(gòu)建了情感營銷效應(yīng)詞庫,并運用MATLAB對該詞庫情感營銷效應(yīng)進(jìn)行了全面的統(tǒng)計分析,分類優(yōu)化情感營銷效應(yīng)值,最后采用中科院ICTCLAS中文分詞技術(shù)進(jìn)行測試,結(jié)果表明,考慮情感營銷效應(yīng)的文本挖掘召回率達(dá)到80%以上,能較好地滿足汽車廠商的應(yīng)用需求。
[Abstract]:A large amount of online review text data is of great practical value for automotive manufacturing product innovation and precision marketing. Traditional text mining pays more attention to emotional polarity and neglects emotional marketing effect. The result of mining is quite different from the demand of enterprise. This paper adopts the automatic acquisition method of emotion words based on CRF machine learning and constructs the affective marketing effect lexicon by using the emotion dictionary such as Dalian Polytechnic Technology, China Zhiwang and the abundant automobile corpus, which is based on CRF machine learning. The effect of emotion marketing is analyzed by using MATLAB, and the effect of emotion marketing is classified and optimized. Finally, the Chinese word segmentation technology of Chinese Academy of Sciences (CAS) is used to test, the result shows that, The recall rate of text mining considering emotional marketing effect is more than 80%, which can meet the application needs of automobile manufacturers.
【作者單位】： 東華大學(xué)旭日工商管理學(xué)院;湖北汽車工業(yè)學(xué)院經(jīng)濟管理學(xué)院;北京理工大學(xué)網(wǎng)絡(luò)搜索與挖掘?qū)嶒炇?武漢工商學(xué)院;
【基金】：上海市自然科學(xué)基金資助項目(15ZR1401600) 湖北省教育廳人文社科指導(dǎo)項目(17G087);湖北省教育廳人文社科資助項目(14Y036) 湖北省高等學(xué)校優(yōu)秀中青年團隊計劃資助項目(T201411) 武漢工商學(xué)院博士啟動基金項目(D20160001)
【分類號】：F274;F426.471;H136
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本文編號：1497255