1 edition of Handbook for Evaluating Knowledge-Based Systems found in the catalog.
Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful applications of knowledge-based systems, some applications have failed because they never received the corrective feedback that evaluation provides for keeping development focused on the users" needs in their actual working environment. This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users" and subject matter experts" evaluation of the usefulness of the system, and not on the developers" testing of the adequacy of the programming code. The handbook permits evaluators to systematically answer the following kinds of questions: Does the knowledge-based system meet the users" task requirements? Is the system easy to use? Is the knowledge base logically consistent? Does it meet the required level of expertise? Does the system improve performance? The authors have produced a handbook that will serve two audiences: a tool that can be used to create knowledge-based systems (practitioners, developers, and evaluators) and a framework that will stimulate more research in the area (academic researchers and students). To accomplish this, the handbook is built around a conceptual framework that integrates the different types of evaluations into the system of development process. The kinds of questions that can be answered, and the methods available for answering them, will change throughout the system development life cycle. And throughout this process, one needs to know what can be done, and what can"t. It is this dichotomy that addresses needs in both the practitioner and academic research audiences.
|Statement||by Leonard Adelman, Sharon L. Riedel|
|Contributions||Riedel, Sharon L.|
|LC Classifications||Q334-342, TJ210.2-211.495|
|The Physical Object|
|Format||[electronic resource] :|
|Pagination||1 online resource (xix, 392 p.)|
|Number of Pages||392|
|ISBN 10||146137829X, 146156171X|
|ISBN 10||9781461378297, 9781461561712|
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This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users' and subject matter experts' evaluation of the usefulness of the system, and not on the developers' testing of the adequacy of the programming code.
Get this from a library. Handbook for Evaluating Knowledge-Based Systems book for evaluating knowledge-based systems: conceptual framework and compendium of methods.
[Leonard Adelman; Sharon L Riedel] -- "Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful. Get this from a library. Handbook for Evaluating Knowledge-Based Systems: Conceptual Framework and Compendium of Methods.
[Leonard Adelman; Sharon L Riedel] -- Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use.
While there have been many successful. However a large portion of the book is dedicated to Artificial Intelligence (AI) methods and hybrid systems that are based on AI, which are better placed under the term Non Knowledge Based Systems (NKBS). This might be a little misleading for the content of the book under the specific title/5(2).
Abstract. The development of knowledge-based systems can be very complex, extending over a number of years and involving many people with different roles, a number of different design and development phases, and often different modules developed using different design Author: Leonard Adelman, Sharon L.
Riedel. 1 Introduction to Recommender Systems Handbook 27 early stage, and there is a need to characterize the nature of this “diversity”, i.e., whether we are looking for diversity among different.
For many years, the theory and practice of knowledge acquisition for knowledge-based systems tended to focus on how to elicit and represent knowledge in a context-free way. More recently, the evolution of the design of software agents has forced the focus to shift so that the context of the interaction between human and software agents has.
Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction.
A knowledge-based system (KBS) is a system that uses artificial intelligence techniques in problem-solving processes to support human decision-making, learning, and action.
Ideal for advanced-undergraduate and graduate students, as well as business professionals, this text is designed to help users develop an appreciation of KBS and their architecture and understand a broad variety of 5/5(1).
Abstract. The concepts of food safety and hygiene have intuitively been a concern to human kind since the dawn of history. In the last 2–3 decades, the world had seen major improvements in food safety management, although admittedly this progress and the lessons learned have been at the cost of many incidents, where people have been injured or have lost their lives.
Evaluating Financial and Application Prototyping Environments Customer Profiling for Financial Services Business Rule Systems Customer Data Quality: The Foundation for a One-to-One Customer Relationship A History of Knowledge-Based Systems in Financial Services The Unfolding Wireless Technology in the Financial Services Industry.
Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior.
Knowledge-Based Systems/Agents •Key components: –Knowledge base: a set of sentences expressed in some knowledge representation language –Inference/reasoning mechanisms to query what is known and to derive new information or make decisions.
•Natural candidate. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation.
This Knowledge Management Tools and Techniques Manual is the first release of a description of some of the key Knowledge Management (KM) methods, tools, technologies, and techniques to be considered for selection within a KM Implementation initiative, especially in small and medium-sized enterprises.
Knowledge-based Systems is an international and interdisciplinary journal in the field of artificial intelligence. The journal will publish original, innovative and creative research results in the field, and is designed to focus on research in knowledge-based and other artificial intelligence techniques-based.
A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item.
They are primarily used in commercial applications. Recommender systems are utilized in a variety of areas and are most commonly recognized as. 15 Knowledge-based Systems Peter Szoiovits Associate Professor, Department of Electrical Engineering and Computer Science Leader, LCS Clinical Decision Making Group Abstract Embedding knowledge is a popular and effective means of increasing the power of sophisticated computer applications.
While the intellectual roots of this method go back to. Praise for The Handbook ofKnowledge-Based Coaching "Definitive, with extensive references and a commitment to connecting theory to practice in every chapter, this important contribution is a delicious and wide-ranging exploration of the lineages that have shaped the modern practice of coaching."--Doug Silsbee, author, Presence-Based Coaching and The Mindful Coach/5.
Powerpoint-Slides for Recommender Systems - An Introduction Chapter 01 - Introduction ( KB) - PDF ( KB) Chapter 02 - Collaborative recommendation ( KB) - PDF ( KB). Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation.TMRF e-Book Advanced Knowledge Based Systems: Model, Applications & Research (Eds.
Sajja & Akerkar), Vol. 1, pp 1 – 11, Chapter 1 Knowledge-Based Systems for Development Priti Srinivas Sajja, Rajendra Akerkar INTRODUCTION Human brain can store several thousand folds of world’s knowledge.
Still it is said that human brain is.The REGTECH Book The Financial Technology Handbook for Investors, Entrepren Handbook for a Sustainable Economy; The Forensic Evaluation of Traumatic Brain Injury A Handbook for Clinicians Handbook for Culturally Competent Care; Handbook for Evaluating Knowledge-Based Systems Conceptual Framework and Co.