A Cognition-inspired Knowledge Representation Approach for Knowledge-based Interpretation Systems

2015 ◽  
Author(s):  
Joel Luis Carbonera ◽  
Mara Abel
Keyword(s):  
Knowledge Representation ◽  
Knowledge Based ◽  
Interpretation Systems

Biography as Scenario

2018 ◽  
pp. 261-269
Author(s):  
Maria Mandrik ◽  
Sergey Arustamov
Keyword(s):  
Knowledge Representation ◽  
Database Design ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Primary Key ◽  
Descriptive Knowledge ◽  
Data Scheme

Purely descriptive knowledge appears to have a structure that can be formalized using the newly developed tool of dynamic knowledge representation, the event bush. In its framework, a singular biography can be transformed into a knowledge-based system with an opportunity of creation of a database. However, the very approach to the database design may undergo quite a change thereafter. This change may concern the concept of primary key, composition of data scheme, and other fundamental issues of database design.

A GENERAL FRAMEWORK FOR KNOWLEDGE-BASED PATTERN RECOGNITION

1987 ◽  
Vol 01 (02) ◽  
pp. 189-205 ◽  
Author(s):  
F. BERGADANO ◽  
L. SAITTA
Keyword(s):  
Pattern Recognition ◽  
Expert System ◽  
Knowledge Representation ◽  
General Framework ◽  
Common Knowledge ◽  
Learning Module ◽  
Knowledge Based ◽  
Recognition Phase ◽  
Representation Scheme

This paper surveys a long term project, aimed at providing a general methodology for building up and maintaining an expert system oriented to Pattern Recognition problems. The methodology makes use of an integrated set of modules, performing different functions but sharing a common knowledge representation scheme. In particular, a learning module allows to acquire the knowledge automatically from a set of examples and another module performs sophisticated reasoning, on the basis of the available knowledge, during the recognition phase.

Knowledge-Based Production Planning Within the Reference Planning Process Supporting Manufacturing Change Management

2016 ◽  
Author(s):  
Benjamin Gernhardt ◽  
Tobias Vogel ◽  
Mohammad Givehchi ◽  
Lihui Wang ◽  
Matthias Hemmje
Keyword(s):  
Knowledge Representation ◽  
Change Management ◽  
Production Planning ◽  
Planning Process ◽  
Semantic Knowledge ◽  
Collaborative Manufacturing ◽  
Knowledge Based ◽  
Process Oriented ◽  
Machine Readable ◽  
Component Production

The manufacturing of a product takes place in several partial steps and these mostly in different locations to save tax or to use the best providers. Therefore, in the era of Internet of Things (IoT) and modern Intelligent Production Environments (IPE) are going to be inevitably based on a cloud-based repository and distributed architecture to make data and information accessible everywhere as well as development processes and knowledge available for worldwide cooperation. Semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient, and effective way. Thus, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required for e.g., Small and Medium Enterprises (SMEs). When such contributors work together on a product component production planning, they exchange component production and manufacturing change information between different planning subsystems which require, e.g., a standardized product-feature- and production-machine feature representation. These data exchanges are mostly based on applying the already established Standard for the Exchange of Product model data (STEP) for the computer-interpretable representation and exchange of product manufacturing information. Furthermore, the planning process can be supported by so-called Function Block (FB) based knowledge representation models, serving as a high-level planning-process knowledge-resource template. Web-based and at the same time Cloud-based tool suites, which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy the needs of representing such planning processes and their knowledge resources. In this way, WPIM can be used to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in Manufacturing Change Management (MCM) including Assembly-, Logistics and Layout Planning (ALLP). Therefore, also a collaborative planning and optimization for mass production in a machine readable and integrated representation is possible. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. To integrate all these functionalities, this paper introduces a new method, called Knowledge-based Production Planning (KPP) and outlines the advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM). In this way, an enabling basis for achieving ALLP interoperability in Distributed Collaborative Manufacturing and Logistics will be demonstrated.

scholarly journals Knowledge-Based Expert System Development and Validation with Petri Nets

2008 ◽  
Vol 07 (01) ◽  
pp. 37-46 ◽  
Author(s):  
Madjid Tavana
Keyword(s):  
Expert System ◽  
Knowledge Representation ◽  
Petri Nets ◽  
Decision Trees ◽  
System Development ◽  
Semantic Networks ◽  
Knowledge Based ◽  
Medical Diagnostic ◽  
High Level ◽  
Decision Tables

Expert systems (ESs) are complex information systems that are expensive to build and difficult to validate. Numerous knowledge representation strategies such as rules, semantic networks, frames, objects and logical expressions are developed to provide high-level abstraction of a system. Rules are the most commonly used form of knowledge representation and they are derived from popular techniques such as decision trees and decision tables. Despite their huge popularity, decision trees and decision tables are static and cannot model the dynamic requirements of a system. In this study, we propose Petri Nets (PNs) for dynamic system representation and rule derivation. PNs with their graphical and precise nature and their firm mathematical foundation are especially useful for building ESs that exhibit a variety of situations, including: sequential execution, conflict, concurrency, synchronisation, merging, confusion, or prioritisation. We demonstrate the application of our methodology in the design and development of a medical diagnostic expert system.

Ontology-Based Knowledge Representation for Mechanical Products

2012 ◽  
Vol 605-607 ◽  
pp. 365-370
Author(s):  
Jia Li ◽  
Yun Bin Yang ◽  
Li Fan Wei
Keyword(s):  
Knowledge Representation ◽  
Mechanical Design ◽  
Design Method ◽  
Design Knowledge ◽  
Configuration Design ◽  
Knowledge Based ◽  
Mechanical Products ◽  
Knowledge Based Engineering ◽  
General Ontology ◽  
Core Part

Knowledge Based Engineering (KBE) helps sharing and reusing knowledge in modern mechanical design field. As a core part of KBE, various methods of knowledge representation were studied. In order to reuse the mechanical design knowledge, the methodology of ontology-based knowledge representation was discussed. First, the concepts, formal description, specialties and languages of ontology were described. Then, three categories of ontology in the field of mechanical design, general ontology, domain ontology and product ontology, were discussed. The product ontology was analyzed by the configuration design method. Finally, an example of ontology-based knowledge representation for mechanical products was studied. The work about ontology-based knowledge representation methodology may support the application of KBE in mechanical design field.

Knowledge Representation for Computer-Aided Planning of Controlled Clinical Trials: the PATriCIa Project

1997 ◽  
Vol 36 (03) ◽  
pp. 172-178 ◽  
Author(s):  
U. Haag
Keyword(s):  
Clinical Trials ◽  
Knowledge Representation ◽  
Formal Representation ◽  
Controlled Clinical Trials ◽  
Knowledge Based ◽  
Study Protocols ◽  
Representation Method ◽  
Computer Aided Planning ◽  
Research Structure

The main thesis of the PATriCIa project is that a knowledge-based system can provide efficient and reliable support for biometricians as well as physicians involved in planning of controlled clinical trials, resulting in a higher quality of medical research. Structure and contents of study protocols are analyzed, and an object-oriented method for formally representing biometric knowledge is proposed. A study protocol can be generated from this formal representation. The programming language Prolog is used to realize the system based on a blackboard architecture. It is concluded that the knowledge representation method developed in the PATriCIa project is well suited for the purpose of generating study protocols for controlled clinical trials.

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