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
In this paper, an efficient fair e-cash system is presented. Based on the improved Brands’ e-cash scheme, it is expanded by adding two roles, government and judges. The user can keep unconditionally anonymous in norm...In this paper, an efficient fair e-cash system is presented. Based on the improved Brands’ e-cash scheme, it is expanded by adding two roles, government and judges. The user can keep unconditionally anonymous in normal transactions. Authorized by the judges, the government can remove the identity of an illegal user with the help of the bank. So such misuse as blackmailing or money laundering can be prevented. Therefore, this scheme is more efficient, more suitable for adopting pre-processing and post-processing and more practical. In the paper, the details of the scheme are described, its security is proved, and its efficiency is analyzed.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In this paper, an efficient fair e-cash system is presented. Based on the improved Brands’ e-cash scheme, it is expanded by adding two roles, government and judges. The user can keep unconditionally anonymous in normal transactions. Authorized by the judges, the government can remove the identity of an illegal user with the help of the bank. So such misuse as blackmailing or money laundering can be prevented. Therefore, this scheme is more efficient, more suitable for adopting pre-processing and post-processing and more practical. In the paper, the details of the scheme are described, its security is proved, and its efficiency is analyzed.
