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Networks: Emerging Topics in Computer Science
Networks: Emerging Topics in Computer Science

Editor: Igor Bilogrevic, Arshin Rezazadeh and Ladan Momeni
ISBN: 978-1-461098-713
Click rate: 34554

Networks - Emerging Topics in Computer Science is suitable for advanced undergraduate students and postgraduate students who are searching for research topics related to networks or requiring brainstormings against network applications. It discusses various aspects related to networks, from large-scale/geo-scale networks to micro-scale networks such as network-on-chip (NoC). The contents of this book is designed in the way such that it tries to make a good balance among different major topics in networks (e.g., network models, network theories, network infrastructures and network applications), so that it suits people from different backgrounds, especially those who are strong in one area but are not familiar with other areas. This book is an invaluable companion for students from their first encounter with the subject to more advanced studies, while the high quality artworks are designed to present the key concepts with simplicity, clarity and consistency.

Pattern Recognition: Methods and Applications
Pattern Recognition: Methods and Applications

Editor: Khalid Hosny and Jorge de la Calleja
ISBN: 978-1-477554-821
Click rate: 18836

Pattern recognition – Methods and Applications includes contributions from university educators and active research experts. This book is intended to serve as a basic reference on pattern recognition, especially on the topics related to image and graphics processing, shape analysis, text processing, and bioinformatics analysis.

Image and Video Processing: An Introductory Guide
Image and Video Processing: An Introductory Guide

Editor: Akshaya Mishra, Zafar Nawaz and Zafar Shahid
ISBN: 978-1-477554-838
Click rate: 20474

In today's world, countless number of images are collected using various image acquisition devices. The course of actions taken to enhance the acquired image quality, to extract meaningful information from the acquired image, and to represent these information in a compact fashion is known as image processing. Digital image processing is the use of computer algorithms to perform image processing on digital images. A digital image is a numeric representation of a two-dimensional image. Depending on whether the image resolution is fixed, it may be of vector or raster type. The term "digital image" usually refers to raster images, also called bitmap images. With the fast computers and signal processors available since 2000, digital image processing has become the most common and cheapest form of image processing.

Artificial Intelligence and Hybrid Systems
Artificial Intelligence and Hybrid Systems

Editor: Claudio Rocha, Fernando Akune and Ahmed El-Shafie
ISBN: 978-1-477554-739
Click rate: 23227

The use of artificial intelligence and hybrid systems has increased dramatically due to their ability in handling real world problems involving uncertainty, vagueness and high complexity. The development of these systems has attracted the interest of the Artificial Intelligence community and established as a promising field of research. In order to present the ideas and practices of the hybridization process of intelligent systems, in this book, we included some recent and interesting studies on this topic.

Exploratory Analysis in Dynamic Social Networks: Theoretical and Practical Applications
Exploratory Analysis in Dynamic Social Networks: Theoretical and Practical Applications

Editor: Carlos Andre Pinheiro and Markus Helfert
ISBN: 978-1-461098-737
Click rate: 19578

Social interactions within networks comprise an increasing event nowadays. Different aspects of societies and competitive markets, such as Social Medias through the Internet and Telecommunications environments hold a high correlation with the social network analysis methodology. By understanding these social structures and its interactions might be possible to realize how individuals and consumers relate each other and hence predict further social structures in the future. However, most of the current social network analysis projects are in relation to static structures, not considering how the social network evolves over the time. The dynamic approach can points out new perspectives in terms of social network analysis, including prediction and simulations scenarios. In order to perceive the social network relations over the time is crucial to collect the distinct snapshots of the social structure, understanding not just how the social members relate each other but in addition to that how this relationships evolves over the time. Measures in relation to social network describe nodes and links by static metrics, depicting its strength, its overall distances to the other related nodes, and its amounts of connections, among others. This dynamic approach makes possible to create a historical data, quite usual for predictive modeling. As such, new social network measures and algorithms should be created in order to describe dynamic features assigned to social structures over the time.

Information Extraction from the Internet
Information Extraction from the Internet

Editor: Nan Tang
ISBN: 978-1-463743-994
Click rate: 20990

As the Internet continues to become part of our lives, there now exists an overabundance of reliable information sources on this medium. The temporal and cognitive resources of human beings, however, do not change. “Information Extraction from the Internet” provides methods and tools for Web information extraction and retrieval. Success in this area will greatly enhance business processes and provide information seekers new tools that allow them to reduce their searching time and cost involvement. This book focuses on the latest approaches for Web content extraction, and analyzes the limitations of existing technology and solutions. “Information Extraction from the Internet” includes several interesting and popular topics that are being widely discussed in the area of information extraction: data spasity and field-associated knowledge (Chapters 1 - 2), Web agent design and mining components (Chapters 3 - 4), extraction skills on various documents (Chapters 5 - 7), duplicate detection for music documents (Chapter 8), name disambiguation in digital libraries using Web information (Chapter 9), Web personalization and user-behavior issues (Chapters 10 - 11), and information retrieval case studies (Chapters 12 - 14).

Introduction to the Semantic Web: Concepts, Technologies and Applications
Introduction to the Semantic Web: Concepts, Technologies and Applications

Editor: Gabriel Fung
ISBN: 978-1-453636-404
Click rate: 21134

According to W3C, the Semantic Web is a “web of data” that enables machines to understand the meaning (semantics) of the data/information presented in the World Wide Web. It extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other, enabling automated agents to access the Web more intelligently and perform tasks on behalf of users. With more research about semantic web in research organizations and in industry, the Semantic Web is quickly emerging as a well-recognized and important area of computer science. This book, Introduction to the Semantic Web: Concepts, Technologies and Applications, provides a quick review and discussion on some key problems in the semantic web. Specifically, this book focuses on the following emerging areas/questions: how we can make use of the semantic web and its technologies to improve searching (Chapter 1 to Chapter 3), what is the relationship between web services and the semantic web (Chapter 4 and Chapter 5), how we can develop social semantic web via social tagging (Chapter 6), how we can improve work collaboration and resources allocation by using semantic web (Chapter 7 and Chapter 9), what are the major privacy concerns in the semantic web (Chapter 10 and Chapter 11), and how to semantic web via data mining, Semantic Web Constraint Language and Web Ontology Language (Chapter 12 to Chapter 14).

Forecasting Models: Methods & Applications
Forecasting Models: Methods & Applications

Editor: Jia Zhu
ISBN: 978-1-451564-563
Click rate: 25692

Forecasting is the process of making statements about events whose actual outcomes have not yet been observed. A more general term of forecasting is prediction. Prediction plays a very important role in our daily life. Its scope is extremely wide: weather forecasting, stock market prediction, supply-demand prediction, population forecasting, traffic prediction, protein-protein interaction prediction, etc. In order to facilitate our discussion, we can only include some topics that are widely being discussed and can reflect the interest of most people. Specifically, this book presents how forecasting models are being used and why they are important.