Knowledge Management And Engineering With Decisional Dna

This is the first book on experience-based knowledge representation and knowledge management using the unique Decisional DNA (DDNA) technology. The DDNA concept is roughly a decade old, and is rapidly attracting increasing attention and interest among researchers and practitioners. This comprehensive book provides guidelines to help readers develop experience-based tools and approaches for smart engineering of knowledge, data and information. It does not attempt to offer ultimate answers, but instead presents ideas and a number of real-world case studies to explore and exemplify the complexities and challenges of modern knowledge engineering issues. It also increases readers’ awareness of the multifaceted interdisciplinary character of such issues to enable them to consider – in different ways – developing, evaluating, and supporting smart knowledge engineering systems that use DDNA technology based on experience.

Experience has made species to survive and cultures to prevail, as experience makes organizations to succeed. Thus, capturing the experience of every decision taken in an explicit representation form is highlighted as the utmost importance in knowledge engineering presented in this book. Decisional DNA knowledge representation allows building the experiential fingerprints of an organization by implementing a model for transforming information into knowledge. The Smart Knowledge Management System (SKMS) is a self-learning and intelligent knowledge management hybrid platform developed to help decision makers in their daily operation. Technologies such as expert systems, simulation, statistical tools, knowledge-based systems, and multiple AI technologies are integrated into the SKMS allowing the combination of different perspectives for acquiring the required explicit decisional experiential knowledge by the means of Decisional DNA. The presented tools offer useful insights to professionals, students and researchers interested in knowledge engineering and knowledge management, but more generally, in the artificial intelligence and information systems fields.

New approaches are needed that could move us towards developing effective systems for problem solving and decision making, systems that can deal with complex and ill-structured situations, systems that can function in information rich environments, systems that can cope with imprecise information, systems that can rely on their knowledge and learn from experience - i.e. intelligent systems. One of the main efforts in intelligent systems development is focused on knowledge and information management which is regarded as the crucial issue in smart decision making support. The 13 Chapters of this book represent a sample of such effort. The overall aim of this book is to provide guidelines to develop tools for smart processing of knowledge and information. Still, the guide does not presume to give ultimate answers. Rather, it poses ideas and case studies to explore and the complexities and challenges of modern knowledge management issues. It also encourages its reader to become aware of the multifaceted interdisciplinary character of such issues. The premise of this book is that its reader will leave it with a heightened ability to think - in different ways - about developing, evaluating, and supporting intelligent knowledge and information management systems in real life based environment.

The four-volume set LNAI 6881-LNAI 6884 constitutes the refereed proceedings of the 15th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2011, held in Kaiserslautern, Germany, in September 2011. Part 2: The total of 244 high-quality papers presented were carefully reviewed and selected from numerous submissions. The 70 papers of Part 2 are organized in topical sections on web intelligence, text and multimedia mining and retrieval, intelligent tutoring systems and e-learning environments, other / misc. intelligent systems topics, methods and techniques of artificial and computational intelligence in economics, finance and decision making, workshop on seamless integration of semantic technologies in computer-supported office work (sistcow), innovations in chance discovery, advanced knowledge-based systems, recent trends in knowledge engineering, smart systems, and their applications.

The four-volume set LNAI 6276--6279 constitutes the refereed proceedings of the 14th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2010, held in Cardiff, UK, in September 2010. The 272 revised papers presented were carefully reviewed and selected from 360 submissions. They present the results of high-quality research on a broad range of intelligent systems topics.

The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges.

Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enh