This paper presents an architecture of a hybrid recommender system in E-commerce environment. The goal of the system is to make special improvements in giving precisely personalized recommendation through some effecti...This paper presents an architecture of a hybrid recommender system in E-commerce environment. The goal of the system is to make special improvements in giving precisely personalized recommendation through some effective measures. Based on the study on the existing recommendation methods of both the conventional similarity function and the conventional feedback function, several improvement algorithms are developed to enhance the precision of recommendation, which include three improved similarity functions, four improved feedback functions, and adoption of both explicit and implicit preferences in individual user profile. Among them, issues and countermeasures of a new user, prominent preferences and long-term preferences are nicely addressed to gain better recommendation. The users preferences is so designed to be precisely captured by a user-side agent, and can make self-adjustment with explicit or implicit feedback.展开更多
According to demand and function of the e-commerce recommendation system demand, this paper analyze and design e-commerce and personalized recommendation, design and complete different system functions in different sy...According to demand and function of the e-commerce recommendation system demand, this paper analyze and design e-commerce and personalized recommendation, design and complete different system functions in different system level; then design in detail system process from the front and back office systems, and in detail descript the key data in the database and several tables. Finally, the paper respectively tests several main modules of onstage system and the backstage system. The paper designed electronic commerce recommendation based on personalized recommendation system, it can complete the basic function of the electronic commerce system, also can be personalized commodity recommendation for different users, the user data information and the user＇ s shopping records.展开更多
This paper describes in detail the web data mining technology, analyzes the relationship between the data on the web site to the tourism electronic commerce （including the server log, tourism commodity database, user...This paper describes in detail the web data mining technology, analyzes the relationship between the data on the web site to the tourism electronic commerce （including the server log, tourism commodity database, user database, the shopping cart）, access to relevant user preference information for tourism commodity. Based on these models, the paper presents recommended strategies for the site registered users, and has had the corresponding formulas for calculating the current user of certain items recommended values and the corresponding recommendation algorithm, and the system can get a recommendation for user.展开更多
In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of...In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of user behavior patterns based on Web log data, well suited to this problem. As an important field of Web usage mining, mining user navigation patterns is the fundamental approach for generating recommendations. In this paper, we propose an ant colony approach for navigation patterns. We use the ant theory as a metaphor to guide user＇s choice in the Web site.展开更多
文摘This paper presents an architecture of a hybrid recommender system in E-commerce environment. The goal of the system is to make special improvements in giving precisely personalized recommendation through some effective measures. Based on the study on the existing recommendation methods of both the conventional similarity function and the conventional feedback function, several improvement algorithms are developed to enhance the precision of recommendation, which include three improved similarity functions, four improved feedback functions, and adoption of both explicit and implicit preferences in individual user profile. Among them, issues and countermeasures of a new user, prominent preferences and long-term preferences are nicely addressed to gain better recommendation. The users preferences is so designed to be precisely captured by a user-side agent, and can make self-adjustment with explicit or implicit feedback.
文摘According to demand and function of the e-commerce recommendation system demand, this paper analyze and design e-commerce and personalized recommendation, design and complete different system functions in different system level; then design in detail system process from the front and back office systems, and in detail descript the key data in the database and several tables. Finally, the paper respectively tests several main modules of onstage system and the backstage system. The paper designed electronic commerce recommendation based on personalized recommendation system, it can complete the basic function of the electronic commerce system, also can be personalized commodity recommendation for different users, the user data information and the user＇ s shopping records.
文摘This paper describes in detail the web data mining technology, analyzes the relationship between the data on the web site to the tourism electronic commerce （including the server log, tourism commodity database, user database, the shopping cart）, access to relevant user preference information for tourism commodity. Based on these models, the paper presents recommended strategies for the site registered users, and has had the corresponding formulas for calculating the current user of certain items recommended values and the corresponding recommendation algorithm, and the system can get a recommendation for user.
基金This research is supported by National Natural Science Foundation of China （70471046）, and Doctoral Fund of State Education Ministry（20040359010）.
文摘In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of user behavior patterns based on Web log data, well suited to this problem. As an important field of Web usage mining, mining user navigation patterns is the fundamental approach for generating recommendations. In this paper, we propose an ant colony approach for navigation patterns. We use the ant theory as a metaphor to guide user＇s choice in the Web site.
