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The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches. More precisely, the ultimate goal has been to collect new knowledge representation, processing and computing paradigms which could be useful to practitioners involved in the area of discussion. To this end, contributions covering both theoretical aspects and practical solutions were preferred.
This is the first book to focus on the people side of knowledge management--what it takes to get employees to contribute to a knowledge system. Robert Buckman explains how to orchestrate this culture change, drawing from the lessons learned by Buckman Laboratories--the leader and pioneer in knowledge management--in implementing award-winning knowledge systems. His book is a practical primer on how organizations can move from "hoarding" knowledge to "sharing" it, building a global strategy that allows them to respond faster than the competition to any customer's need on a global basis. Buckman reveals how to: Combat the biggest problem with implementing knowledge management--creating the culture that supports it Increase the speed of innovation globally across an organization Resolve technical problems quickly Make immediate, informed decisions to help solve customer issues Create new products based on customer input and demand
The art of building knowledge systems is multidisciplinary, incorporating computer science theory, programming practice and psychology. This book incorporates these varied fields covering topics ranging from algorithms and representations to techniques for acquiring the task specific knowledge.
As organizations, businesses, and other institutions work to move forward during a new era of ubiquitous modern technology, new computing and technology implementation strategies are necessary to harness the shared knowledge of individuals to advance their organizations as a whole. Intelligent and Knowledge-Based Computing for Business and Organizational Advancements examines the emerging computing paradigm of Collective Intelligence (CI). The global contributions contained in this publication will prove to be essential to both researchers and practitioners in the computer and information science communities as these populations move toward a new period of fully technology-integrated business.
Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.
The main aim of this research book is to report a sample of the most recent advances in the field of intelligent interactive systems in knowledge-based environment. The contents of this book include: Introduction to intelligent interactive systems Affective bi-modal intelligent tutoring system Estimation of development costs in intelligent systems Narrative interactive learning Knowledge acquisition for configurable products and services Interaction modalities in mobile contexts Face images classification for human-computer interactions Users modelling for distance learning Group adaptation and group modelling A personalized news aggregator on the web. This book would prove useful to the researchers, professors, research students and practitioners as it reports novel research work on innovative topics in the area of intelligent interactive systems.
This volume presents selected papers from KBCS '89, which is the second in a series of annual conferences hosted by the Knowledge Based Computer Systems Project funded by the Government of India with United Nations assistance. The papers are grouped into sections including: - AI applications - computer architecture and parallel processing - expert systems - intelligent tutoring systems - knowledge representation - logic programming - natural language understanding - pattern recognition - reasoning - search - activities at the KBCS Nodal Centres.
Provides detailed methodology for digitizing project knowledge by bridging the gap between Waterfall and Agile Methodologies.
One of the major limitations of the Ambient Intelligent Systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the specific activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. As an added value, this system should be sufficiently simple and flexible to be managed by non-expert users, and thus, facilitate the transfer of research to industry. To do this, we develop graphical models to represent human behaviour in Smart Spaces, in order to provide them with more usability in the final application. As a result, human behaviour recognition can help assisting people with special needs such as independent elders, in remote rehabilitation monitoring, industrial process guidelines, and many other cases.