Contribution to Knowledge-based Methodology for Collaborative Process Definition: Knowledge Extraction from 6napse Platform

2008 ◽  
pp. 437-449
Author(s):  
V. Rajsiri ◽  
A -M. Barthe ◽  
F. Bénaben ◽  
J -P. Lorré ◽  
H. Pingaud
2000 ◽  
Vol 33 (20) ◽  
pp. 101-103
Author(s):  
N.N. Katerinochkina ◽  
V.V. Ryazanov ◽  
O.V. Senco ◽  
A.P. Vinogradov ◽  
V.A. Voronchihin ◽  
...  

2010 ◽  
Vol 61 (2) ◽  
pp. 161-175 ◽  
Author(s):  
Vatcharaphun Rajsiri ◽  
Jean-Pierre Lorré ◽  
Fréderick Bénaben ◽  
Hervé Pingaud

2008 ◽  
Vol 05 (02) ◽  
pp. 181-187 ◽  
Author(s):  
NAZAR ELFADIL

In this paper, the author presents an approach for automated knowledge extraction from rise time auto-correlated patterns by using self-organizing maps and k-means clustering. The extracted knowledge in terms of rules will be used as knowledge base for an expert system. Rise-time auto-correlated data patterns are used as a learning data set. The produced knowledge based was verified by using a conventional expert system.


Author(s):  
Vatcharaphun Rajsiri ◽  
Jean-Pierre Lorré ◽  
Fréderick Bénaben ◽  
Hervé Pingaud

Author(s):  
BURKHARD PEUSCHEL ◽  
WILHELM SCHAFER ◽  
STEFAN WOLF

The subject of this paper is the description of a process-centered software development environment called MERLIN which monitors and guides teams of software developers and managers in producing software objects. Software objects (or objects for short) include all sorts of documents like requirements analysis, design, code, user manuals, contracts etc. For each user, MERLIN automatically displays a specific working context which contains information like objects, their relations, their current development state, and corresponding tools. This information is filtered according to the (access) rights and duties a particular user has in a particular project, i.e. the working context depends on the user's role (e.g. programmer, designer, manager). Internally, the computation of the information to be contained in a working context, is based on a rulelike definition of a software process and a flexible interpretation mechanism to enact such a process definition. The main feature of the interpreter is an alternating use of backward and forward chaining for the interpretation of rules. In addition, our implementation enables a persistent storage and incremental update during runtime of all process information expressed in facts within the MERLIN knowledge base.


2018 ◽  
Vol 26 ◽  
pp. 140 ◽  
Author(s):  
Rodolfo García Galván ◽  
Mayer R. Cabrera Flores ◽  
Lewis S. McAnally Salas

In a knowledge-based economy, it is imperative to understand the collaborative process between universities and their surroundings. Therefore, the aim of this study is to identify the key characteristics of UABC’s collaboration process within its social, productive and governmental environment. The research is based on a case study in which the data collection method was a semi-structured interview applied to researchers of AUBC’s Institutes. Among the main findings was the normative ambiguity regarding collaboration activities, which have brought significant cognitive impact on researchers; also, the management and organization of the University do not reflect institutional efforts to build professional skills for outreaching activities based on the knowledge, which, correspondingly, does not favor the consolidation of this important university function.


2011 ◽  
Vol 8 (2) ◽  
pp. 299-315 ◽  
Author(s):  
Miroslav Líska ◽  
Pavol Navrat

The Guide to the Software Engineering Body of Knowledge (SWEBOK) provides a consensually validated characterization of the bounds of the software engineering discipline and to provide a topical access to the Body of Knowledge supporting that discipline. The topic ?Notation for Process Definition? references selected notations appropriate for software process definition. However all of them have weakly defined semantics, thus is not possible to use formal techniques for process model creation, validation etc. In this work we present created Software and Systems Process Engineering Meta-Model (SPEM) Ontology that improves the lack of mentioned process notations. The SPEM Ontology constitutes a semantic notation that provides concepts for knowledge based software process engineering. The work also discusses utilization of such semantic notation in other selected SWEBOK topics, the Software Project Planning, the Software Project Enactment, and the Verification and Validation.


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