由於”衝動型購買行為消費者”之購物決策過程十分短暫與快速，往往都在當 下 情 境 的 渲 染 就 馬 上 做 下 決 定 。 有 鑑 於 此 ， 本 研 究 將 區 塊 相 鄰 圖 (Region Adjacency Graph, RAG)、自我組織映射圖網路(Self-Organizing Maps, SOM)、智 慧型代理人(Intelligent Agent, IA)、以及多文件自動摘要技術(Multiple Document Summarization, MDS)結合在資訊系統上，提供即時之商品評鑑服務。當使用者在 購物衝動時，可以利用各種行動設備進行存取遠端的商品評鑑服務，其中包括 3G 手機和個人數位助理器(PDA)，經由無線行動通訊網路(如：GPRS/UMTS/LTE 或 IEEE 802.11)，透過應用程式或網頁瀏覽器等存取資訊系統中相關服務。
因 此 ， 提 出 一 套 提 三 層 次 (3-tier) 架 構 之 行 動 式 商 品 評 鑑 平 台 (Mobile Merchandise Evaluation Platform, MMEP)，包括即時商品辨識子系統(Real-time Merchandise Identification Subsystem, RMIS)、商品評論建議子系統(Merchandise Evaluation Subsystem, MES) 、 以 及 商 品 比 價 推 薦 子 系 統 (Merchandise Recommendation Subsystem, MRS)。其中，即時商品辨識子系統(RMIS)利用區塊 相鄰圖(RAG)和自我組織映射圖網路(SOM)學習各個商品影像特徵，並有效進行 分類，影像辨識正確率可達 81.25%。商品評論建議子系統(MES)結合多文件自動 摘要技術(Multiple Document Summarization, MDS)和化妝品評論詞彙本體論 (Merchandise Comment Term Ontology, MCTO)，取得商品評論摘要，並經領域專 家評論摘要語句比對後，正確率可達 78%。讓使用者可以直接用手機拍攝商品，
辨識的正確率。同時也將應用擴展到其他的商品項目，例如說 3C 產品的資料等。
系統的準確率和效率則是透過使用其他資訊檢索技術以及考慮更多的有可能影 響的因子加入演算法。
參考文獻
[1] C. N. Chang, S. Y. Chen, J. Y. Yeh, M. J. Hwang, H. R. Ke, and W. P.Yang, “A Concept Extraction Approach for Document Clustering”, Proceedings of 2008 International Conference on Advanced Information Technologies, Taiwan, 2008.
[2] C. J. Cobb, W. D. Hoyer, “Planned versus impulse purchase behavior”, Journal of Retailing, Vol. 62, No.4, pp. 384-409, 1986.
[3] G. Erkan and D. R. Radev, “LexPageRank: Prestige in Multi-Document Text Summarization”, Proceedings of EMNLP 2004, Barcelona, Spain, PP. 365-371, 2004.
[4] J. Han and M. Kamber, “Data mining: concepts and techniques, second edition”, Morgan Kaufmann Publishers, 2005.
[5] K. Haris, S. Efstratiadis, N. Maglaveras, and A. Katsaggelos, “Hybrid image segmentation using watersheds and fast region merging”, IEEE Transactions on Image Process. Vol. 7, No. 12, pp. 1684-1699, 1998.
[6] S. E. Hernandez, K. E. Barner, and Y. Yuan, “Region merging using homogeneity and edge integrity for watershed-based image segmentation”, Optical Engineering, Vol. 44, No. 1, pp. 1-14, 2005.
[7] Y. L. Huang, J. P. Lee, G. L. Chen, Z. Z. Lee, M. P. Chang, X. J. Huang, “Image Retrieval by Using Region Adjacency Relations”, Tunghai Science, Vol. 6, pp.
17-41, 2004.
[8] K. Kaikhah, “Text Summarization Using Neural Networks”, WSEAS Transactions on Systems, Vol. 3, No. 2, pp. 960-963, 2004.
[9] Z. Li, and X. Tang, “Using Support Vector Machines to Enhance the Performance of Bayesian Face Recognition”, IEEE Transactions on Information Forensics and Security, Vol. 2, No. 2, pp. 174-180, 2007.
[10] G. A. Miller, “WordNet: A Lexical Database for English”, Communications of the ACM, Vol. 38, No. 11, pp. 39-41, 1995.
[11] S. H. Myaeng, and D. Jang, “Development and Evaluation of a Statistically Based Document System”, In I. Mani and M. May bury (eds), Advances in Automated Text Summarization, MIT Press, pp. 61-70, 1999.
[12] V. Perlibakas, “Distance measures for PCA-based face recognition”, Pattern Recognition Letters, Vol.25, No. 6, pp.711-724, 2004.
[13] D. R. Radev, A. Winkel, and M. Topper, “Multi Document Centroid-based Text Summarization”, Processing of ACL 2002, Philadelphia, PA, 2002.
[14] D. R. Radev, H. Jing, and M. Budzikowska, “Centroid-based summarization of multiple documents”, Information Processing and Management, Vol. 40, No. 6, pp. 919-938, 2004.
[15] D. R. Radev, T. Allison, S. Blair-Goldensohn, J. Blitzer, A.C. elebi, S. Dimitrov, E. Drabek, A. Hakim, W. Lam, D. Liu, J. Otterbacher, H. Qi, H. Saggion, S.
Teufel, M. Topper, A. Winkel, and Z. Zhu, “MEAD - a platform for multidocument multilingual text summarization”, Proceedings of LREC 2004, Lisbon, Portugal, May 2004.
[16] D. W. Rook, “The buying impulse”, Journal of Consumer Research, Vol. 14, No.2, pp.189-199, 1987
[17] M. R. Solomon, “Consumer Behavior: Buying, Having, and Being, 5th edition”, NJ: Prentice Hall, 2007.
[18] H. Stern, “The Significance of Impulse Buying Today”, Journal of Marketing, Vol. 26, No. 2, pp. 59-62, 1962.
[19] K. Toutanova and C. D. Manning, “Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger”, Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000), Hong Kong, 2000.
[20] H. C. Wang, C. T. Liu, T. H. Huang, “A Concept-Level Ontology Construction Method for Automatic Summarization”, Journal of Internet Technology, Vol. 8, No. 4, pp. 381-387, 2007.
[21] P. Weinberg, W. Gottwald, “Impulsive consumer buying as a result of emotions”, Journal of Business Research, Vol. 10, No. 1, pp. 43-57, 1982.
[22] C. W. Wu and C. L. Liu, “Ontology-based text summarization for business news articles”, ISCA 18th International Conference on Computers and Their Applications, pp. 389–392, 2003.
[23] J. Yang, D. Zhang, A.F. Frangi, and J.Y. Yang, “Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 1, pp.
131-137, 2004.
[24] J. Y. Yeh, “A study on automated text summarization and its application on Chinese documents”. MS Thesis, Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan, 2002.
[25] J. Y. Yeh, H. R. Ke, W. P. Yang, and I. H. Meng, “Text Summarization Using a Trainable Summarizer and Latent Semantic Analysis”, Information Processing and Management, Vol. 41, No. 1, pp. 75-95, 2005.
[26] 陳志華，「一個無所不在的情境感知式健康照護系統之設計與實作」，國立交 通大學資訊管理研究所，碩士論文，2009。
[27] 羅濟群、陳志華、高湘婷、程鼎元、呂志健，「智慧型行動式商品評鑑平台 之設計與實作」，工商管理學刊，第五卷，第一期，第 33-42 頁，2009。