|Statement||edited by Sandra Marcus.|
|Series||SECS ;, 92, Kluwer international series in engineering and computer science ;, SECS 92.|
|LC Classifications||QA76.76.E95 K5545 1990|
|The Physical Object|
|Pagination||148 p. :|
|Number of Pages||148|
|LC Control Number||89048643|
In my humble opinion, and based on 10+ years in technical developer support, the "knowledge acquisition bottleneck" is the (empirically slow) process involved with 'programming' knowledge. This is due to a number of factors- mostly human but also. Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge . knowledge transfer and knowledge acquisition. A s Argote (, p) emphasizes based on Szulanski () research, “One of the facto rs fo und to Author: Constantin Bratianu. Knowledge acquisition as modeling. New York: Wiley, ©(OCoLC) Material Type: Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Kenneth M Ford; Jeffrey M Bradshaw.
Knowledge Acquisition: Past, Present and Future Brian R. Gaines University of Calgary & University of Victoria [email protected], [email protected] Abstract: As we celebrate the fiftieth knowledge acquisition conference this year it is appropriate to review progress in knowledge acquisition techniques not only over the quarter century since theFile Size: 3MB. Knowledge acquisition typically details how people experience new information, how that information is stored in the brain, and how that information can be recalled for later use. One of the primary components of knowledge acquisition is the supposition that people are born without knowledge, and that it is gained during a person’s lifetime. Yi Shang, in The Electrical Engineering Handbook, Knowledge Acquisition. Knowledge acquisition refers to the process of extracting, structuring, and organizing domain knowledge from domain experts into a program. A knowledge engineer is an expert in AI language and knowledge representation who investigates a particular problem domain, determines important concepts, . Readings in Knowledge Acquisition and Learning collects the best of the artificial intelligence literature from the fields of machine learning and knowledge acquisition. This book brings together the perspectives on constructing knowledge-based systems from these two historically separate subfields of artificial intelligence.
The knowledge-engineering process includes five major activities: 1. Knowledge dge acquisition involves the acquisition of knowl-edge from human experts, books, documents, sensors, or computer files. The knowledge may be specific to the problem domain or to the problem-solving pro-File Size: KB. This book constitutes the proceedings of the 14th International Workshop on Knowledge Management and Acquisition for Intelligent Systems, PKAW , held in Phuket, Thailand, in August The 16 full papers and 5 short papers included in this volume were carefully reviewed and selected from 61 initial submissions. Read the latest articles of Knowledge Acquisition at , Elsevier’s leading platform of peer-reviewed scholarly literature. Purchase Knowledge Acquisition and Machine Learning - 1st Edition. Print Book & E-Book. ISBN , Book Edition: 1.