Search

This book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems. It also presents algorithmic approaches in the field of Web recommendations by extracting knowledge from Web logs, Web page content and hyperlinks. Recommender systems have been used in diverse applications, including query log mining, social networking, news recommendations and computational advertising, and with the explosive growth of Web content, Web recommendations have become a critical aspect of all search engines. The book discusses how to measure the effectiveness of recommender systems, illustrating the methods with practical case studies. It strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with valuable insights into Web recommender systems.

The present treatise spread in 103 contributions from the experts covers the following topics: " Information Processing and Pattern Recognitino " Computer Communication Networks " Hardware and Optimization " Data Mining " Software Engineering " Distributed Systems " Biomedical Informatics " Soft Computing

This book provides a systematic introduction to the fundamental concepts, major challenges, and effective solutions for Quality of Service in Wireless Sensor Networks (WSNs). Unlike other books on the topic, it focuses on the networking aspects of WSNs, discussing the most important networking issues, including network architecture design, medium access control, routing and data dissemination, node clustering, node localization, query processing, data aggregation, transport and quality of service, time synchronization, and network security. Featuring contributions from researchers, this book strikes a balance between fundamental concepts and new technologies, providing readers with unprecedented insights into WSNs from a networking perspective. It is essential reading for a broad audience, including academics, research engineers, and practitioners, particularly postgraduate/postdoctoral researchers and engineers in industry. It is also suitable as a textbook or supplementary reading for graduate computer engineering and computer science courses.

Features And Syntax Of Assembly Language Programming, 8086 Internal Architecture, Programming Features, And Instruction Set, Ibm Pc Architecture And Programming, Software Interrupts In Assembly And C Language, Exclusive Chapter On Advanced Processors Including The Pentium And P6, Wide Range Of Complete Programming Solutions In Assembly And C Language. 8087 Architecture, Instruction Set And Programming, Reference On Dos And Bios Interrupts. Numerous Programming Examples On Console1/O, Printer Output, File And Directory Operations Command Line Arguments, Disk, Device Drivers, Multi-Tasking Clock Data Conversion, Searching, Sorting, Matrix Operations, String Operations, Linked Lists, Stacks, Queues, And Trees

"A ready reference for the next-generation discovery techniques, this book presents advanced research findings on resource discovery, network navigability, and trust management on the Internet of Things (IoT) and Social Internet of Things (SIoT) ecosystems. It discusses the benefits of integrating social networking concepts into the Internet of Things to find the preferable, reliable, scalable, and near-optimal detection of things or services. It explores the concepts of the Social Internet of Things in different domains of IoT, such as the Internet of Vehicles and the Industrial Internet of Things. This book works to recognize and respond to user queries and improve service provisioning, find the optimal solution for the link selection in the SIoT structure, develop large-scale platforms, and provide a smart mechanism for trust evaluation. Covers the rapid advancements in low-cost sensor manufacturing, communication protocols, embedded systems, actuators, and hardware miniaturization that have contributed to the exponential growth of the IoT Presents the fundamentals of a search system for sensor search and resource discovery in an IoT ecosystem Includes the applicability of different search techniques across several application domains of the IoT under various use case scenarios Discusses the thrust areas in SIoT (service discovery and composition, network navigability, relationship management, and trustworthiness management) and presents several prerequisites, challenges, and use case scenarios Provides insights into current challenges in the domains of Internet of Things and Social Internet of Things This book will be helpful to researchers, scholars, and postgraduate students in Computer Science and Information Technology departments"--

The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.