This paper describes a novel approach using Hidden Markov Models (HMM) to detect complex Internet attacks. These attacks consist of several steps that may occur over an extended pe...
Dirk Ourston, Sara Matzner, William Stump, Bryan H...
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 ...
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Technical support procedures are typically very complex. Users often have trouble following printed instructions describing how to perform these procedures, and these instructions...
Tessa A. Lau, Lawrence D. Bergman, Vittorio Castel...
In this paper, the proposed LIPED (LIfe Profile based Event Detection) employs the concept of life profiles to predict the activeness of event for effective event detection. A gro...
An intrusion detection system (IDS) usually has to analyse Giga-bytes of audit information. In the case of anomaly IDS, the information is used to build a user profile characteris...
In the “query-by-humming” problem, we attempt to retrieve a specific song from a target set based on a sung query. Recent evaluations of query-by-humming systems show that th...
The use of HMM (Hidden Markov Models) for speech recognition has been successful for various applications in the past decades. However, the use of continuous HMM (CHMM) for melody...
Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidd...
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...