Improving The Performance Of Hierarchical Hidden Markov Models On Information Extraction
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Improving The Performance Of Hierarchical Hidden Markov Models On Information Extraction
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Author : Lin-Yi Chou
language : en
Publisher:
Release Date : 2006
Improving The Performance Of Hierarchical Hidden Markov Models On Information Extraction written by Lin-Yi Chou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Markov processes categories.
Hidden Markov Models And Applications
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Author : Nizar Bouguila
language : en
Publisher: Springer Nature
Release Date : 2022-05-19
Hidden Markov Models And Applications written by Nizar Bouguila and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-19 with Technology & Engineering categories.
This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and applications that consider HMMs. The authors discuss challenging problems that exist when considering HMMs for a specific task or application, such as estimation or selection, etc. The goal of this volume is to summarize the recent advances and modern approaches related to these problems. The book also reports advances on classic but difficult problems in HMMs such as inference and feature selection and describes real-world applications of HMMs from several domains. The book pertains to researchers and graduate students, who will gain a clear view of recent developments related to HMMs and their applications.
The Semantic Web Research And Applications
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Author : York Sure
language : en
Publisher: Springer
Release Date : 2006-06-01
The Semantic Web Research And Applications written by York Sure and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-01 with Computers categories.
This book constitutes the refereed proceedings of the 3rd European Semantic Web Conference, ESWC 2006. The book presents 48 revised full papers with abstracts of 3 invited talks. The papers are organized in topical sections on ontology alignment, engineering, evaluation, evolution and learning, rules and reasoning, searching and querying, semantic annotation, semantic web mining and personalisation, semantic web services, semantic wiki and blogging, as well as trust and policies.
Knowledge Based Software Engineering
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Author : Maria Virvou
language : en
Publisher: IOS Press
Release Date : 2008
Knowledge Based Software Engineering written by Maria Virvou and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Addresses various topics in the context of knowledge-based software engineering, including challenges that have arisen in this area of research. This book includes topics such as knowledge-based requirements engineering, domain analysis and modeling; development processes for knowledge-based applications; and, knowledge acquisition.
Evolutionary Computation Machine Learning And Data Mining In Bioinformatics
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Author : Elena Marchiori
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-14
Evolutionary Computation Machine Learning And Data Mining In Bioinformatics written by Elena Marchiori and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-14 with Computers categories.
This book constitutes the refereed proceedings of the 6th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2008, held in Naples, Italy, in March 2008 colocated with the Evo* 2008 events. The 18 revised full papers were carefully reviewed and selected from 63 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.
Hidden Markov Models And Their Extensions For Proportional Sequential Data
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Author : Samr Ali
language : en
Publisher:
Release Date : 2021
Hidden Markov Models And Their Extensions For Proportional Sequential Data written by Samr Ali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
We are facing an all-time high in the worldwide generation of data. Machine learning techniques have proven successful in unveiling patterns within data to further human knowledge. This includes building systems with overall better prediction and accuracy levels. Nonetheless, many areas have yet to be studied which warrants further exploitation of these techniques. Hence, data modeling is one of the topics at the forefront of scientific research. A particularly interesting field of research is the appropriate choice of distribution that corresponds to the nature of the data. In this thesis, we focus on tackling challenges in the approximation of proportional Hidden Markov Models (HMM). We review the main concepts behind HMM; one of the cornerstone probabilistic graphical models for time series or sequential data. We also discuss various modern challenges that exist when training or using HMMs. Nonetheless, we primarily focus on the notorious model estimation process of HMMs as well as the appropriate choice of emission distribution based on the nature of the data. We have tackled these problems using variational inference and Maximum A Posteriori (MAP) approximation with the Dirichlet, the Generalized Dirichlet, and the Beta-Liouville (BL) distributions-based HMMs for proportional data. In this thesis, we develop frameworks for learning these proportional HMMs that have been proposed recently as an efficient way for modeling sequential proportional data. In contrast to the conventional Baum Welch algorithm, commonly used for learning HMMs, the proposed algorithms place priors for the learning of the desired parameters; hence, regularizing the estimation process. We also extend these models into infinity for a data-driven dynamically chosen structure of HMMs. Such a setup enables flexibility in the model structure with a lower computational cost for model selection. We also investigate the fusion of the trained classifiers and witness a consequent improved performance. Moreover, we incorporate a simultaneous feature selection paradigm as well as investigate online deployment. We present our recently proposed methodologies that address the aforementioned problems and discuss the achieved results across a variety of computer vision applications. We also present how a simple novel experimental setup can drastically improve the performance of HMMs in occupancy detection, and estimation by extension, in a smart building for an applied research contribution. Finally, we conclude and recommend potential future work.
Information Extraction Using Hidden Markov Models
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Author : Timothy Robert Leek
language : en
Publisher:
Release Date : 1997
Information Extraction Using Hidden Markov Models written by Timothy Robert Leek and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Information Retrieval Technology
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Author : Azizah Jaafar
language : en
Publisher: Springer
Release Date : 2014-11-21
Information Retrieval Technology written by Azizah Jaafar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-21 with Computers categories.
This book constitutes the refereed proceedings of the 10th Information Retrieval Societies Conference, AIRS 2014, held in Kuching, Malaysia, in December 2014. The 42 full papers were carefully reviewed and selected from 110 submissions. Seven tracks were the focus of the AIR 2014 and they were IR models and theories; IR evaluation, user study and interactive IR; web IR, scalability and IR in social media; multimedia IR; natural language processing for IR; machine learning and data mining for IR and IR applications.
Machine Learning Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2011-07-31
Machine Learning Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-31 with Computers categories.
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
A Hierarchical Bayesian Hidden Markov Model For Multi Dimensional Discrete Data
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Author : Shigeru Motoi
language : en
Publisher:
Release Date : 2008
A Hierarchical Bayesian Hidden Markov Model For Multi Dimensional Discrete Data written by Shigeru Motoi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
In this chapter, we have described an extended Bayesian HMM for multidimensional discrete data sequences including redundant components. For the extended model, we also described an implementation of Bayesian learning based on a Markov chain Monte Carlo scheme. We evaluated the performance of the extended model with this implementation using two example datasets. We also demonstrated its application to an event detection problem with 40-dimensional data sequences extracted from videos of actual soccer games.