Large Scale Hierarchical Classification: State of the Art, Azad Naik; Huzefa Rangwala

Автор: Wan, Cen
Название: Hierarchical feature selection for knowledge discovery
ISBN: 3319979183 ISBN-13(EAN): 9783319979182
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.

Автор: Catarina Silva; Bernadete Ribeiro
Название: Inductive Inference for Large Scale Text Classification
ISBN: 3642261345 ISBN-13(EAN): 9783642261343
Издательство: Springer
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Цена: 113180.00 T
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Описание: This book explains and illustrates key methods in inductive inference in large scale text classification, especially kernel approaches. It covers a series of new techniques to enhance, scale and distribute text classification tasks.

Автор: Juan A. Fern?ndez; Javier Gonz?lez
Название: Multi-Hierarchical Representation of Large-Scale Space
ISBN: 9048158613 ISBN-13(EAN): 9789048158614
Издательство: Springer
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Цена: 130590.00 T
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Описание: It has been stated in psychology that human brain arranges information in a way that improves efficiency in performing common tasks, for example, information about our spatial environment is conveniently structured for efficient route finding.

Автор: Joanna Ko?odziej
Название: Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems
ISBN: 3642436617 ISBN-13(EAN): 9783642436611
Издательство: Springer
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Цена: 104480.00 T
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Описание: This book explores hot topics in the design, administration and management of dynamic grid environments. The emphasis is on preferences and autonomous decisions of system users, secure access to processed data and services and the use of green technologies.

Автор: Jens Spehr
Название: On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
ISBN: 3319358626 ISBN-13(EAN): 9783319358628
Издательство: Springer
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Цена: 95770.00 T
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Описание: In many computer vision applications, objects have to be learned and recognized in images or image sequences.

Автор: Hing Kai Chan; Xiaojun Wang
Название: Fuzzy Hierarchical Model for Risk Assessment
ISBN: 1447150422 ISBN-13(EAN): 9781447150428
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book offers a fuzzy-based hierarchical approach to risk management problems, tackling imprecise information with qualitative and quantitative criteria. Uses case studies from the food, fashion and electronics sectors on supply chain management and more.

Автор: Daniel Vasquez; Rainer Gruhn; Wolfgang Minker
Название: Hierarchical Neural Network Structures for Phoneme Recognition
ISBN: 3642432107 ISBN-13(EAN): 9783642432101
Издательство: Springer
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Цена: 104480.00 T
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Описание: The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language.

Автор: Daniel Vasquez; Rainer Gruhn; Wolfgang Minker
Название: Hierarchical Neural Network Structures for Phoneme Recognition
ISBN: 3642344240 ISBN-13(EAN): 9783642344244
Издательство: Springer
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Цена: 121890.00 T
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Описание: The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language.

Автор: Arindam Chaudhuri
Название: Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks
ISBN: 9811374732 ISBN-13(EAN): 9789811374739
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.

Автор: Daniela Sanchez; Patricia Melin
Название: Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
ISBN: 331928861X ISBN-13(EAN): 9783319288611
Издательство: Springer
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Цена: 60940.00 T
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Описание: The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;

Автор: Leticia Cervantes; Oscar Castillo
Название: Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers
ISBN: 3319266705 ISBN-13(EAN): 9783319266701
Издательство: Springer
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Цена: 69870.00 T
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Описание: Whenfuzzy logic is used it make it easy to performed the simulations, these fuzzysystems help to model the behavior of a real systems, using the fuzzysystems fuzzy rules are generated and with this can generate the behavior ofany variable depending on the inputs and linguistic value.

Автор: Eduard Cerny; Bachir Berkane; Pierre Girodias; Kar
Название: Hierarchical Annotated Action Diagrams
ISBN: 146137569X ISBN-13(EAN): 9781461375692
Издательство: Springer
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Цена: 93160.00 T
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Описание: Standardization of hardware description languages and the availability of synthesis tools has brought about a remarkable increase in the productivity of hardware designers.