2004, Vol.9, No.2

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

pISSN : 1598-849X / eISSN : 2383-9945
https://journal.kci.go.kr/jksci

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy conditional probability and trapezoidal. we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition. Our goal of study is make an intelligent automatic navigation agent model.

It requires that user have to verify and conform with user authentication protocol on non-meet face to face internet services offered by mobile terminal which user make known user's own intention, and user be using the normal. It is more operation time authentication protocol than Access control protocol. That is what need to be user authentication protocol have verified security, non-reputation, and improved high-performance in operation time for mobile terminal. In order to solve the above demand, in this paper, we would design for mobile terminal of TCP User Authentication ECC Algorithm Protocol with a performance test. Algorithm has 160 bit key and designed IPv4 & IPv6 frame architecture. We should conclude that the proposed protocol have more verified security, non-reputation, confidentiality, and improved high-performance in operation time of mobile terminal from 1 to 17 times than before.

This paper proposes ACA (Adaptive Component Analysis) as a method for feature extraction and analysis of the content-based image retrieval system. For satisfactory retrieval, the features extracted from images should be appropriately applied according to the image domains and for this, retrieval measurement is proposed in this study. Retrieval measurement is a standard indicating how important the value of a relevant feature is to image retrieval. ACA is a middle stage for content-based image retrieval and it purposes to improve the retrieval speed and performance.