We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...
As a vast number of services have been flooding into the Internet, it is more likely for the Internet resources to be exposed to various hacking activities such as Code Red and SQL...
It is indispensable that the users surfing on the Internet could have web pages classified into a given topic as correct as possible. Toward this ends, this paper presents a topic-...
Sanguk Noh, Youngsoo Choi, Haesung Seo, Kyunghee C...
AURA (Advanced Uncertain Reasoning Architecture) is a parallel pattern matching technology intended for high-speed approximate search and match operations on large unstructured dat...
A Gaussian mixture model (GMM) estimates a probability density function using the expectation-maximization algorithm. However, it may lead to a poor performance or inconsistency. T...
This paper defines a constrained Artificial Neural Network (ANN) that can be employed for highly-dependable roles in safety critical applications. The derived model is based upon t...
Abstract. One of the objectives of intelligent data engineering and automated learning is to develop algorithms that learn the environment, generate rules, and take possible course...
The main aim of this paper is to extend the single-agent policy gradient method for multiagent domains where all agents share the same utility function. We formulate these team pro...
This paper presents an effective core-promoter prediction system on human DNA sequence. The system, named PromSearch, employs a hybrid approach which combines search-by-content met...
Recently, it seems to be interested in the conversational agent as an effective and familiar information provider. Most of conversational agents reply to user’s queries based on ...