Research on Personalized Merchandise Information Filtering in Electronic Catalog Systems

• Main Authors: Ya-Wen Huang, 黃雅文
• Other Authors: Duen-Ren Liu
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/66490291050428020073

碩士 === 國立交通大學 === 資訊管理所 === 87 === With the rapid growth of Internet, virtual stores are increasing enormously. However, users may encounter an information over-flooding problem, which makes users spend most of their time searching and eliminating irrelevant merchandise information. Though e-catalog systems provide some search functions to search merchandise information, the result may still be too large. The aim of our study was to design information filtering functions in e-catalog systems that are able to eliminate irrelevant merchandise information automatically by taking into account of user profiles. A three-level merchandise metadata is used to describe the detail of a specific product and to construct the e-catalogs. Additionally, we use a three-level merchandise tree to categorize merchandise information into a tree structure based on the e-catalogs. A three-level user profile based on e-catalog systems is also proposed to describe a user's shopping interest in all kinds of product. Furthermore, an inverted index structure is also used to provide an alternative way to describe the merchandise information. Finally, we propose different matching algorithms to filter merchandise information according to the user profile. Experimental evaluations are conducted to compare the performance of various approaches.