同步式關鍵字萃取方法應用於美妝評論

Extracting Product Features and Opinion Words Simultaneously from Cosmetic Customer Reviews

羅佳玲(Chia-Ling Lo)

指導教授 ： 邱昭彰

元智大學/資訊學院/資訊管理學系/碩士(2009年)

https://doi.org/10.6838/YZU.2009.00220

摘要

網路上有著豐富的產品或服務意見資訊，然而要消費者或廠商處理這些評論資訊會浪費許多時間與人力資源。本研究的目的是從網路消費者評論中擷取重要的資訊。本研究提出一個有效率的同步式關鍵字萃取方法應用於中文的美妝評論。同步式關鍵字萃取過程包含兩個階段：階段一，利用些許人工挑選的seed words產生其對應的樣式規則；階段二，使用樣式規則、反覆式關鍵字萃取流程與否定詞辨別方法自動地萃取評論的opinion unit。根據最後的實驗結果顯示同步式關鍵字萃取方法在擷取opinion unit有不錯的效果。

關鍵字

意見探勘 ； 樣式規則 ； 關鍵字萃取

並列摘要

Internet has become the source of almost everything, ranging from voluminous information to products and services. Sorting through the countless comments may be a waste of time on the part of the customers and on manufacturer’s human resources. We aim to mine the important information of product review from Internet customers. We propose an effective way to extract product features and opinion words simultaneously from cosmetic customer reviews in Chinese. The process consists of two parts. First, several seed words are used to generate pattern rules; second, pattern rules, iterative process, and negation words identification methods are employed to automatically extract opinion units that commented by users. Our experimental results indicate that our proposed techniques are highly effective.

並列關鍵字

Opinion Mining ； Pattern Rule ； Keyword Extraction

參考文獻

[1]Bruce, R. and Wiebe. J., 2000, "Recognizing Subjectivity: A Case Study in Manual Tagging," Natural Language Engineering, pp. 187-205.

[2]Cen, S., Mao, Y., Li, R. and Wang, X., 2008, "Credit Distribution: A Graph-Based Approach to Extract Product Description Words," International Symposium on Knowledge Acquisition and Modeling, IEEE, pp.398-402.

[4]Duan, H., Bao, S., and Yu, Y., 2007, "CCRM: An Effective Algorithm for Mining Commodity Information from Threaded Chinese Customer Reviews," Proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 473-480.

[11]Miao, Q., Li, Q., and Dai, R., 2009, "AMAZING: A Sentiment Mining and Retrieval System," Expert Systems with Applications: An International Journal, pp.7192-7198.

[16]Thet, T. T., Na, J-C., and Khoo, C., 2008, "Sentiment Classification of Movie Reviews Using Multiple Perspectives," Proceedings of International Conference on Asian Digital Libraries (ICADL), pp.184-193.