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Topic: Knowledge engineering


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In the News (Fri 22 Mar 19)

  
  Knowledge engineering - Wikipedia, the free encyclopedia
Knowledge engineering is also related to mathematical logic and cognitive science as the knowledge is produced by cognitive systems (mainly humans) and is structured by our understanding of how human reasoning or logic works.
Knowledge engineers acknowledge that there are different types of knowledge, and that the right approach and technique should be used for the knowledge required.
Knowledge engineers acknowledge that there are different types of experts and expertise, such that methods should be chosen appropriately.
en.wikipedia.org /wiki/Knowledge_engineering   (339 words)

  
 Knowledge-Based Engineering - Wikipedia, the free encyclopedia
Knowledge-Based Engineering (KBE) is a discipline with roots in computer-aided design (CAD) and knowledge-based systems but has several definitions and roles depending upon the context.
Knowledge processing is a recent advance in computing.
Some approaches to knowledge are reductionistic, as well they ought to be given the pragmatic focus of knowledge modeling.
en.wikipedia.org /wiki/Knowledge-Based_Engineering   (1478 words)

  
 Knowledge Engineering: CGs, Knowledge Representation
Knowledge Engineering is the technique applied by knowledge engineers to build intelligent systems: Expert Systems, Knowledge Based Systems, Knowledge based Decision Support Systems, Expert Database Systems, etc. There are two main view to knowledge engineering.
In this view, the knowledge engineer attempts to model the knowledge and problem solving techniques of the domain expert into the artificial intelligent system.
The knowledge representation scheme studied is Conceptual Structure (Sowa, 1984), and the Knowledge Modelling techniques studied is the KADS (Schreiber, Wielinga, and Breuker, 1993).
pages.cpsc.ucalgary.ca /~kremer/courses/CG   (158 words)

  
 Knowledge and knowledge engineering
Knowledge engineering, used mainly with reference to computer science, has been defined by Feigenbaum (1980) as the process of reducing a large body of knowledge to a precise set of facts and rules.
Knowledge representation consists in the symbolic way the acquired knowledge is expressed and structured in order to be dealt in a meaningful way by the machine.
The knowledge acquired and represented is activated by a symbols manipulator known as the Inference Engine.
www.problemistics.org /learning/knowledge.engineering.html   (4677 words)

  
 The Knowledge Engineering Laboratory
Knowledge engineering is the process used in KEL to acquire and structure information about a subject.
Tools and techniques from engineering and computer science are needed to integrate the various elements of the knowledge base, so that it can be used in an efficient and effective manner.
Knowledge engineering is an activity that embraces a set of concepts and methodologies dealing with (i) acquisition of knowledge, (ii) analysis and synthesis of data and information [quantities], (iii) integration and interpretation of knowledge [quantities and qualities], and (iv) application of knowledge (Figure 2).
kelab.tamu.edu /standard/approach.html   (1189 words)

  
 AI Guide: Knowledge Engineering (2)
Knowledge engineering is a general term for the processes involved in building expert systems: planning, knowledge acquisition, system building, system installation, system maintenance.
The KE uses the data from the knowledge acquisition sessions to build a good model of the expertise that the DE is using to solve problems in the domain.
However, 'knowledge elicitation workben ches', or 'knowledge engineering environments', are commercially available (e.g KEE, KnAcqTools); their principle use is to simplify the task of converting a protocol into frames, rules, etc., and inserting these structures into an expert system shell as soon as they are formulated.
www.mdx.ac.uk /www/ai/samples/ke/51-know.htm   (668 words)

  
 Knowledge Management vs Knowledge Engineering.   (Site not responding. Last check: 2007-10-08)
The terms knowledge management and knowledge engineering seem to be used as interchangeably as the terms data and information used to be.
A brief examination of the terms management and engineering shows that to manage is to exercise executive, administrative and supervisory direction, where as, to engineer is to lay out, construct, or contrive or plan out, usually with more or less subtle skill and craft.
The knowledge engineers should also be establishing the processes by which knowledge requests are examined, information assembled, and knowledge returned to the requestor.
www.km-forum.org /kmvske.htm   (451 words)

  
 Managing knowledge through Wisdom™   (Site not responding. Last check: 2007-10-08)
Having identified the knowledge situation of the organisation, the next step is to evaluate the specific knowledge problems in the organisation, or in one of its departments, processes or activities.
Having access to knowledge only when its ‘owner’ has time to share it, or chancing to loose it completely if he or she leaves the organisation are problems which threaten the value of an organisation’s knowledge capital.
Although the knowledge described in the tables is still quite simplified and incomplete, the aim of the exercise is to show the possible representation of knowledge concerning requirement classification using Wisdom™.
sern.ucalgary.ca /KSI/KAW/KAW99/papers/Dignum1   (8209 words)

  
 Class 1: Knowledge Engineering   (Site not responding. Last check: 2007-10-08)
The area of Knowledge Engineering is concerned with the use of logics to represent knowledge, and then reason using the constructed knowledge base.
It is important to encode knowledge at the most abstract level possible since this allows one to generalize to new situations, yet, one shouldn't lose the ability to represent specific instances.
The knowledge engineering task begins with knowledge acquisition-the knowledge engineer has to interview the experts in the domain in order to ascertain what is important, and what needs to be represented in the KR.
www.mines.edu /Academic/courses/math_cs/macs404/node30.html   (274 words)

  
 Mastery InSight Institute Workshop: NLP & Knowledge Engineering
A Knowledge Engineer writes the rules that enable an expert system to make decisions, and while Cyberspace may be an overused word, its interesting to think of having a dataspace to represent the matrix of information you construct to build your model.
The integration of Knowledge Engineering strategies with NLP tools and patterns provides a rational framework for a variety of possible shifts in thought patterns, even for dealing with kinesthetic experience (which many people attempt to logically, verbally explain).
Knowledge Engineering Cancellation/Refund Policy: We provide a full refund to anyone needing to cancel registration to a Knowledge Engineering seminar at any time prior to the start of the seminar.
www.altfeld.com /mastery/seminars/desc-knowledge.html   (3406 words)

  
 Knowledge Sharing Papers
Principal obstacles to all current work in knowledge sharing involve the difficulties of achieving consensus regarding what knowledge representations mean, of enumerating the context features and background knowledge required to ascribe meaning to a particular knowledge representation, and of describing knowledge independent of specific interpreters or inference engines.
Much current work on knowledge acquisition for intelligent systems concentrates on the use of predefined models of problem-solving methods to define the roles in which domain knowledge is used to solve particular application tasks.
Knowledge engineers extend this model of problem solving with domain knowledge to define models of relevant application areas.
www-ksl.stanford.edu /knowledge-sharing/papers/README.html   (4800 words)

  
 Barnes & Noble.com - Knowledge Engineering and Management: The CommonKADS Methodology - Guus T. Schreiber ...
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.
btobsearch.barnesandnoble.com /textbooks/booksearch/isbnInquiry.asp?userid=2UZ3V9GE5A&btob=Y&isbn=0262193000&TXT=Y&itm=1   (285 words)

  
 Process Life Cycle Engineering
In this sense, the Articulator's knowledge representation ontology represents a resource-based theory of organizational processes, which in turn is in line with one of the principal basis for strategic planning and business management (cf.
However, such intimate knowledge of the setting (and participants) where process redesign is being considered is likely to be among the most influential variables that determine the success or failure of a business process redesign effort.
Thus, our approach is focusing on codifying the most reusable knowledge across common business process application domains, while relying on the active engagement and participation of the people who perform the process, as well as have a stake in its redesigned outcome, to select among process redesign alternatives which can be identified and further engineered.
www.usc.edu /dept/ATRIUM/Papers/Process_Life_Cycle.html   (8943 words)

  
 AKRI : Research : Knowledge Engineering
Knowledge Engineering is a complex job that is generally accepted to be the elicitation, codification and sometimes activation of knowledge using computer systems.
Software that is both useful for general Knowledge Engineering and also supports the CommonKads methodology is PC Pack.
Whatever methodology is chosen or even if a Knowledge Engineer devises his or her own for particular applications, PC Pack may still be a useful tool.
www.akri.org /research/engineer.htm   (186 words)

  
 Amazon.com: Ontological Engineering : with examples from the areas of Knowledge Management, e-Commerce and the Semantic ...   (Site not responding. Last check: 2007-10-08)
Ontologies are now widely used in knowledge engineering, artificial intelligence and computer science; in applications related to areas such as knowledge management, natural language processing, e-commerce, intelligent information integration, bio-informatics, education; and in new emerging fields like the semantic web.
Engineers and scientists typically view philosophical musings on any topic as being impractical, and indulging oneself in these musings will cause one to lose sight of the topic or problem at hand.
Knowledge at the linguistic level is described in linguistic terms, while at the conceptual level in terms of concepts and the relations between them.
www.amazon.com /exec/obidos/tg/detail/-/1852335513?v=glance   (1999 words)

  
 Engineering
Knowledge based engineering (KBE) has been with us since the 1980s and large companies such as Boeing, BAE Systems and NASA, along with car giants Jaguar and Lotus Engineering, have bought into it.
But before these molecules were crafted into modern engines, virtual facsimiles of them were subjected to vivid, lifelike simulations of these actions, the whole shebang conjured by an artificial intelligence as sophisticated as anything conceived of in The Matrix.
Structural engineering is defined as a field which encompasses design, fabrication, construction and maintenance of buildings, bridges, towers, dams and other similar structures.
www.aaai.org /AITopics/html/engin.html   (3703 words)

  
 Handbook of Software Engineering and Knowledge Engineering
The Handbook of Software Engineering and Knowledge Engineering is the first comprehensive handbook covering these two important areas that have become interwoven in recent years.
Each chapter is written in a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information.
It covers: a) essential concepts of software engineering, b) fundamental concepts of knowledge engineering, c) applications of software engineering to knowledge engineering, d) applications of knowledge engineering to software engineering, and e) emerging technologies in software engineering and knowledge engineering.
www.ksi.edu /seke/hand.html   (2014 words)

  
 Software Engineering Body of Knowledge Version 1.0, A
Software engineering, both as a discipline and as a profession, is at a pivotal point in its evolution.
The lack of consensus regarding software engineering practice and the requisite competencies creates confusion and has serious consequences for the evaluation, acquisition, and application of software engineering knowledge.
This body of knowledge can assist organizations in defining and improving the software engineering competencies of their workforces; it can help educational institutions in defining software engineering curricula; it can provide a basis for classifying academic and industrial research and development efforts; and it can improve the understanding and practice of software engineering.
www.sei.cmu.edu /publications/documents/99.reports/99tr004/99tr004abstract.html   (201 words)

  
 "Knowledge Engineering / Modeling" Home Study Course
In such a project, core software development team members would be tasked with acquiring knowledge from the experts, and then encoding that knowledge in a fashion that allows computers to reproduce the expert's behavior consistently and fast!
This event will also be useful for professional Knowledge Engineers who wish to understand more how others think, so as to know more effectively how to trim out less-relevant decision criteria.
In a more prepared state of mind, we can then utilize the modified knowledge engineering tools to rapidly model the expertise of others and then apply it.
www.altfeld.com /mastery/products/ke-nlp.html   (1520 words)

  
 International Journal of Software Eng. & Knowledge Eng.
The International Journal of Software Engineering and Knowledge Engineering is published quarterly, March, June, September and December of each year.
It is intended to serve as a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of software engineering and knowledge engineering.
A central theme of this journal is the interplay between software engineering and knowledge engineering: how knowledge engineering methods can be applied to software engineering, and vice versa.
www.ksi.edu /ijsk.html   (1308 words)

  
 ICAPS 2005 Competition on Knowledge Engineering   (Site not responding. Last check: 2007-10-08)
No matter how efficient or powerful Planning and Scheduling (PandS) engines are, they are only as good as the application knowledge that they use.
The aims of the Knowledge Engineering (KE) Competition are to
Hence, knowledge engineering processes support the planning process: they comprise all of the off-line, knowledge-based aspects of planning that are to do with the application being built, and any on-line processes that
scom.hud.ac.uk /scomtlm/competition   (231 words)

  
 Elsevier.com - Data & Knowledge Engineering   (Site not responding. Last check: 2007-10-08)
Data and Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest.
The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
DKE achieves this aim by publishing original research results, technical advances and news items concerning data engineering, knowledge engineering, and the interface of these two fields.
www.elsevier.com /inca/publications/store/5/0/5/6/0/8   (359 words)

  
 Knowledge Engineering: (ResearchIndex)   (Site not responding. Last check: 2007-10-08)
Abstract: Knowledge engineering for AI planning is the process that deals with the acquisition, validation and maintenance of planning domain models, and the selection and optimization of appropriate planning machinery to work on them.
Evidence from the growing body of experience in applying planning technology suggests that knowledge engineering issues are crucial to an application 's success.
The Knowledge Engineering Technical Co-ordination Unit of PLANET has been active for several years now...
citeseer.ist.psu.edu /549557.html   (197 words)

  
 HANDBOOK OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING   (Site not responding. Last check: 2007-10-08)
This is the first handbook to cover comprehensively both software engineering and knowledge engineering — two important fields that have become interwoven in recent years.
Each chapter has been written in such a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information.
Volume Two will cover the basic principles and applications of visual and multimedia software engineering, knowledge engineering, data mining for software knowledge, and emerging topics in software engineering and knowledge engineering.
www.worldscibooks.com /compsci/4603.html   (465 words)

  
 Knowledge Engineering   (Site not responding. Last check: 2007-10-08)
Here are some examples of additional knowledge engineering topics you could learn about in these sources.
Graphical knowledge representation devices such as flow charts, decision trees and decision tables are often useful in capturing or refining expertise before it is converted into the format required by the knowledge base.
These knowledge representations should be verified by the expert to assure that the knowledge has been accurately captured.
www.expertise2go.com /webesie/tutorials/KnowEng/summary.htm   (282 words)

  
 Amazon.com: Knowledge Engineering : Unifying Knowledge Base and Database Design (Artificial Intelligence): Books: John ...   (Site not responding. Last check: 2007-10-08)
The knowledge can be implemented either in a programming language or in an expert systems shell.
The methodology has two special features: It is unified, i.e., it represents the data, information, and knowledge in a homogeneous manner, as well as the relationships between them.
A special benefit of the book is its thorough treatment of constraints for knowledge and for knowledge-based systems.
www.amazon.com /exec/obidos/tg/detail/-/3540637656?v=glance   (570 words)

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