Editors

Dr Reda Mohamed Hamou, GeCoDe Laboratory, Department of Computer Science, University Dr Tahar Moulay Of Saïda Algeria
 

Call for Chapters

Proposals Submission Deadline: December 15, 2016
Full Chapters Due: March 15, 2017
Submission Date: July 30, 2017
 

Introduction

Information retrieval (IR) is an established technology that provides solutions to users in over three decades but is still an active area of research. This suggests that although much work has been done in this area, much remains to be done. In terms of scope, this paradigm has experienced a growth well beyond its first text indexing and search tasks relevant documents in a collection. Today, research in IR includes modeling, web search, text classification, systems architecture, user interfaces, data visualization, filtering, multilingual search, clustering, and search multimedia information. IR is directly related to multidisciplinary and interdisciplinary applications. The result is that, as long as the information exists, information retrieval is pervasive. 
Many applications that manage the information on the web would be totally insufficient without the support of IR technology. How can we find information on the web if there were no search engines? How can we manage our email without spam filtering? How can we protect our homes and shops, remotely through the web without video surveillance systems? All these details have spawned several solutions that we undertake in this book, and which concern the search for web information. 
Several terms are more or less related to knowledge management (KM) as management skills, intellectual capital management, learning organization, and decision aid. Knowledge management is an interdisciplinary field called cognitive science, expert systems, cognitive engineering, semantic networks, databases ... 
The aim of knowledge management is to ensure that informational capital are easily accessible and be preserved, shared and developed. 
The algorithms are important in many real applications, with the objective to obtain solutions probably best compared to the runtime environment. In recent years, engineers and decision makers are confronted daily with complex problems (NP-hard) that generally affect all sectors. Since always, researchers have tried to solve these problems in the most efficient manner. For this, the research was oriented to proposal of exact algorithms for particularly polynomial. The appearance of heuristics has allowed finding solutions generally adequate but often for small instances. This is why it is necessary and vital to find new type of algorithms that can lead to a major breakthrough for the practical resolution of these problems. 
Today, a huge success is achieved through modeling of biological intelligence, and naturally resulting in what is called "computational intelligence algorithms". These algorithms include artificial neural networks, evolutionary computations, collective intelligence, artificial immune systems, human organ systems and fuzzy systems, form a part of the field of meta-heuristic and biomimicry. They demonstrated their forces face the various complex problems where they are still trying to find the optimal solution from a finite number of existing solutions and provide high performance results in experimental studies and it is often difficult to understand why they are performing in a particular context. Another important advantage, these algorithms can often be applied without much knowledge about the problem, which makes them very suitable for various applications. 
Nature is a powerful inspiration to solve complex problems in computer science, since it provides extremely diverse phenomena, dynamic, robust, complex and fascinating. She always finds a solution to his problem, and maintains the perfect balance between its components. Living beings have managed to survive on earth in the last four billion years. The main reason for this success is certainly their ability to adapt to changing adverse environments. They have amazing abilities to learn unfamiliar situations, adapt their behavior and forms of environmental change, self-replication while maintaining a kind of the most useful features, and self repair without outside intervention. 
Biomimicry is the use of biological processes such as metaphor, inspiration, or natural phenomena in the development of new information technologies and new algorithms for information retrieval and knowledge management. This field of study loosely knitted a set of sub-areas related to topics of connectionism, social behavior and emergence. The real beauty of biomimicry is that they get only its inspiration from nature. However, the use of algorithms directly imitating the behavior of natural organisms and characteristics of living things is a recent development and these algorithms have proven to significantly more robust and scalable than traditional algorithms.
 

Objective

Twenty research articles grouped in a volume entitled "Handbook of Research on Biomimicry in Information Retrieval and Knowledge Management." Will be included. We ask researchers in the field to present their work and results engendered by biomimetic techniques in the field of research information and knowledge management. It will also include conclusions on new methods derived from nature that have been solutions to the tool boards of problems in the field. We expect researchers, contributions important and real, to solve problems and ambiguities that exist in web mining, semantics related to knowledge and its representation, and his exploitation.
 

Target Audience

The target audience of this book will be composed of professionals from the engineering knowledge, academic researchers working in the field of information retrieval, bioinformatics, including doctoral students and the 2nd and 3rd university cycle. The book can also serve as a supplementary handbook for advanced courses in the field of bio-inspiration, multidisciplinary courses for students, graduates and doctoral research students in the field of knowledge engineering. This book is a reference book for academic purposes in various public libraries, scientific, and university. The book also aims to guide researchers in the field to establish a true state of the art of biomimicry in solving problems related to information retrieval and knowledge management.
 

Recommended Topics

Bio-inspired systems algorithm 
Biologically-inspired computation 
Biologically-inspired engineering 
Machine learning, data mining,bioinformatics,data security, Information Retrieval, Chaotic systems 
Fuzzy Data Mining, Fuzzy Biomedical Systems, Pattern Recognition, Fuzzy Clustering 
Advanced Evolutionary Computation 
Advanced theory of computational intelligence 
Advanced biologically-inspired computational intelligence 
Advanced neural systems and human-like agents 
Advanced statistical learning theory 
Computational intelligence in knowledge discovery 
Foraging, Genetic, immune, mimetic, Swarm-based algorithms 
Swarming behaviors 
Artificial life, molecular computing and emergent computation techniques. 
Models of living-system’s behavior and social organization 
Model-based metaheuristics (matheuristics) 
Modeling and analysis of metaheuristic computing 
Very large scale metaheuristics 
Particle Swarm, Random, simulation Optimizations 
Parallel metaheuristics, new metaheuristic approaches/operators 
Automated reasoning and logic programming 
Case studies and real-world applications with bio-inspired algorithm 
Applications associated with bio-inspired methodologies, e.g. bioinformatics, etc… 
Artificial Intelligence (incl. Robotics) 
Bioinformatics
 

Submission Procedure

Researchers, Phd Students and practitioners are invited to submit on or before December 15, 2016, a chapter proposal of 1 to 2 pages clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by January 15, 2017 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by March 15, 2017. All submitted chapters will be reviewed on a double-blind review basis.
 

Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. For additional information regarding the publisher, please visit www.igi-global.com. This publication is anticipated to be released in 2017.
 

Important Dates

December 15, 2016: Proposal Submission Deadline 
January 15, 2017: Notification of Acceptance 
March 15, 2017: Full Chapter Submission 
May 15, 2017: Review Results Returned 
July 15, 2017: Final Acceptance Notification 
July 30, 2017: Final Chapter Submission
 

Inquiries

Dr Reda Mohamed Hamou, GeCoDe Laboratory, Department of Computer Science, University Dr Tahar Moulay Of Saïda Algeria 

E-mail : hamoureda@yahoo.fr
hamoureda@gmail.com
 

Propose a chapter for this book