Utilising domain knowledge in inductive knowledge discovery

1995 ◽  
Author(s):  
J. Mallen
Keyword(s):  
Knowledge Discovery ◽  
Domain Knowledge

scholarly journals Ontology-Based Knowledge Model for Multi-View KDD Process

2012 ◽  
Vol 4 (3) ◽  
pp. 21-33 ◽  
Author(s):  
EL Moukhtar Zemmouri ◽  
Hicham Behja ◽  
Abdelaziz Marzak ◽  
Brigitte Trousse
Keyword(s):  
Knowledge Discovery ◽  
Domain Knowledge ◽  
Knowledge Discovery In Databases ◽  
Knowledge Model ◽  
Interactive Process ◽  
Types Of Knowledge ◽  
Do So

Knowledge Discovery in Databases (KDD) is a highly complex, iterative and interactive process that involves several types of knowledge and expertise. In this paper the authors propose to support users of a multi-view analysis (a KDD process held by several experts who analyze the same data with different viewpoints). Their objective is to enhance both the reusability of the process and coordination between users. To do so, they propose a formalization of viewpoint in KDD and a Knowledge Model that structures domain knowledge involved in a multi-view analysis. The authors’ formalization, using OWL ontologies, of viewpoint notion is based on CRISP-DM standard through the identification of a set of generic criteria that characterize a viewpoint in KDD.

ONTO-KMS-TEC

2013 ◽  
pp. 226-249
Author(s):  
C. R. Rene Robin ◽  
D. Doreen Hepzibah Miriam ◽  
G. V. Uma
Keyword(s):  
Knowledge Management ◽  
Knowledge Discovery ◽  
Case Studies ◽  
Domain Knowledge ◽  
Faculty Members ◽  
Knowledge Flow ◽  
Educational Institutions ◽  
Management Tools ◽  
Teaching Methodologies ◽  
Knowledge Management Tools

Knowledge management tools have been used in higher educational institutions for years to improve the effectiveness of teaching methodologies. Knowledge management in pedagogical includes processes of knowledge discovery, capture, storage, retrieval, sharing, and understanding. According to Pundt and Bishr, knowledge management aims at facilitating knowledge flow and utilization across every beneficeiary, such as faculty members and students. An ontology can be used to support knowledge retrieval, store, and sharing domain knowledge. The framework and the case studies described in this chapter detail how the knowledge of an engineering subject can be effectively retrieved, stored, and shared among the teachers and the students.

scholarly journals Genetic programming as a model induction engine

2000 ◽  
Vol 2 (1) ◽  
pp. 35-60 ◽  
Author(s):  
Vladan Babovic ◽  
Maarten Keijzer
Keyword(s):  
Genetic Programming ◽  
Knowledge Discovery ◽  
Domain Knowledge ◽  
Scientific Discovery ◽  
Empirical Relationship ◽  
Physical Processes ◽  
Flexible Vegetation ◽  
Additional Resistance ◽  
Amount Of Knowledge

Present day instrumentation networks already provide immense quantities of data, very little of which provides any insights into the basic physical processes that are occurring in the measured medium. This is to say that the data by itself contributes little to the knowledge of such processes. Data mining and knowledge discovery aim to change this situation by providing technologies that will greatly facilitate the mining of data for knowledge. In this new setting the role of a human expert is to provide domain knowledge, interpret models suggested by the computer and devise further experiments that will provide even better data coverage. Clearly, there is an enormous amount of knowledge and understanding of physical processes that should not be just thrown away. Consequently, we strongly believe that the most appropriate way forward is to combine the best of the two approaches: theory-driven, understanding-rich with data-driven discovery process. This paper describes a particular knowledge discovery algorithm—Genetic Programming (GP). Additionally, an augmented version of GP—dimensionally aware GP—which is arguably more useful in the process of scientific discovery is described in great detail. Finally, the paper concludes with an application of dimensionally aware GP to a problem of induction of an empirical relationship describing the additional resistance to flow induced by flexible vegetation.

Using domain knowledge to guide database knowledge discovery

1996 ◽  
Vol 10 (2) ◽  
pp. 173-180 ◽  
Author(s):  
M.Mehdi Owrang O. ◽  
Fritz H. Grupe
Keyword(s):  
Knowledge Discovery ◽  
Domain Knowledge
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