基於基因演算法之電子商務商品自動分類

Genetic-based Automatic Classification for E-Commerce Product

花琨詠(Kun-Yong Hua)

指導教授 ： 張榮貴

國立中正大學/工學院/資訊工程學系/碩士(2015年)

摘要

近年來隨著互聯網及電子商務的快速發展，在網路上買賣東西儼然成為一種嶄新且主流的消費方式。隨著客源一批批的增加，賣家所拿出的商品不只數量要更多、種類也要更豐富才能滿足消費者的口味；然而在這種情況下，如果在上架商品時還是以傳統購物網站的方式一件一件商品慢慢選擇所屬類別的話，在效率及時間上來說是不容易被接受的；再者，因為是由賣家方來選擇商品的類別，所以常常出現不屬於該類別的意外商品存在，這樣的情況不只讓買家無法順利且快速的找到需要的商品，也會令人感覺到購物網站的雜亂不章。基於這些原因，我們以基因演算法為基礎開發出了商品自動化分類，適應函數的設計、複製、交配、突變的機制皆在本文中有詳細的過程敘述，最後呈現出來的數據也讓我們的方法被證明是可以被使用在購物平台上的。如此，我們的方法讓賣家不需要花費多餘的時間在選擇分類上，而是可以將所省下來的時間專注於提供消費者更好的購物品質。再者，統一由我們系統方來做商品分類的話，也可以減少分類錯誤所造成買家搜尋該分類卻出現不相關商品的雜亂情況。根據這樣的理念，我們將商品自動化分類在我們的系統上實作出來，以提供消費者更好的服務品質。

關鍵字

電子商務 ； 基因演算法 ； 自動分類

並列摘要

In recent years, with the rapid development of the Internet and e-commerce, buying and selling things on the Internet has become a new and mainstream consumption. Along with more and more consumer, not only the number of sellers of products to come up with more and more abundant species, but also to satisfy consumers; however, if when products are ready to sell still use to traditional select category, it is not easy to be accepted in efficiency and time; furthermore, because of seller side to select the category of products, so there is often appear to not belong to the category. This case not only let the buyer was unable to successfully and quickly find the needed products, will cause feel cluttered shopping sites no chapter.
For these reasons, we developed genetic-based automatic classification. In this paper, we describe the process in detail, and the results prove our method can be used on the online shopping platform. Our method allows the seller not need to spend extra time in selecting category, they can focus on providing consumers with a better shopping quality. Moreover, We can unify by the system side to reduce category error rate. According to this concept, we implement our method in the online shopping platform to provide consumers with better service quality.

並列關鍵字

genetic algorithm ； automatic classification ； e-commerce

參考文獻

17. 陳信源、葉鎮源、林昕潔、黃明居、柯皓仁、楊維邦，” 結合支援向量機與詮釋資料之圖書自動分類方法”，In IJAIT,June,2009

9. James, M., Classification algorithms, John Wiley & Sons, Inc. 1985.

11. Dumais, S., Platt, J., Heckerman, D., and Sahami, M., “Inductive Learning Algorithms and Representation for Text Categorization,” In Proceedings of CIKM-98, pp. 148-155,1998.

12. Yang, Y., and Chute, C., “An Example-Based Mapping Method for Text Classification and Retrieval,” ACM Transactions on Information Systems, Vol. 12, No. 3, pp. 252-277,1994.

13. Cohen, W., “Text Categorization and Relational Learning,” In Proceedings of the 12th International Conference on Machine Learning, 1995.