In previous work [14], we modify the hidden Markov model (HMM) framework to incorporate a global parametric variation in the output probabilities of the states of the HMM. Develop...
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
A Focused crawler must use information gleaned from previously crawled page sequences to estimate the relevance of a newly seen URL. Therefore, good performance depends on powerfu...
Hongyu Liu, Evangelos E. Milios, Jeannette Janssen
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James