近年來，網路口碑(Electronic Word-of-Mouth)已成為產品評價散播的管道以及企業內部改善的重要依據。然而，隨著網際網路普及，各種討論社群因應而生，卻也面臨口碑資訊量爆發性成長所造成資訊過載(Information Overload)的窘境。因此，如何協助企業有效地從大量口碑資訊中分析出有價值的決策依據，實為現今企業實施顧客關係管理重要的研究課題之一。
本研究目的在於研發一詞性組合輔助之中文網路口碑評價分析技術，以有效地協助企業快速且正確的暸解目前網路口碑評價的情況，進而作為企業與顧客關係改善的依據。針對上述目的，本研究主要研究項目包括: (i) 研究領域與相關技術探討，(ii) 詞性組合規則產生與主題字萃取方法設計，(iii) 口碑評價辨識方法設計以及(iv) 詞性組合輔助之中文網路口碑評價分析機制實作。

The main purpose of this study is to develop a technology for a Part-of-Speech (POS) combination-aided Chinese electronic Word-of-Mouth (eWOM) analysis. Using this technology to analyze a Chinese eWOM, we obtain eWOM sentences of the target product, and analyze eWOM polarities supplemented by POS combination rules, and constantly update analysis criteria to keep up with new network articles. Hope this technology can effectively help companies quickly and correctly understand the evaluation situation of the current eWOM, and further form a company basis for improving their relations with customers. This study mainly include: (1) Exploration of Research Domains and Related Technologies, (2) POS Combination Rules Generation and Topic Terms Extraction Method Design, (3) eWOM Identification Method Design, and (4) Implementation of POS Combination-Aided Chinese eWOM Analysis Mechanisms.

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