...describes an approach for eliciting ontology components by using knowledge maps. the knowledge contained in a particular
domain, any kind of text digital archive, is portrayed by assembling and displaying its ontology components.
...demand for formalized representa- tion of outcomes of research, we address the task of con- structing an ontology of data mining. the proposed on- tology, named ontodm, is based on a recent proposal of a general framework for data mining, and includes defini- tions of basic data mining entities, such as datatype and...
...the demand for formalized representation of outcomes
of data mining investigations, we address the task of constructing an ontology of data mining. our heavy-weight ontology,
named ontodm, is based on...allows us to cover much of the diversity in data
mining research, including recently developed approaches to mining structured data and constraint-based data mining. ontodm
is compliant to best...
...the induction of knowledge from a data set relies in the execution of multiple data mining actions: to apply filters to...an architecture to automatize the data mining process. the architecture assumes
that the data mining process can be seen from...
...this paper focuses on a domain-driven data mining outsourcing scenario whereby a data owner publishes data to an application service provider...for aiding users in a domain-driven data mining outsourcing scenario. the framework involves several components designed to anonymize data while preserving meaningful or actionable...
...its applications in logistics and specifically transportation are highlighted. even though data mining has been successful in becoming a major component of various business processes and applications...to date about the usefulness of applying data mining in transport related research. from the literature, the frameworks for carrying out knowledge discovery and data mining have been revised over the...
Published in 2011.
...that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and snp data, domain ontologies and health management data. the practical application of the methodology and the specific data mining techniques engaged are demonstrated on...
...miningtechniques that operate overan integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and snp data, domain,ontologies and health management,data. the practical application of the methodology,and the specific data mining techniques engaged are demonstrated on...
Published in 2008.
...an up-to-date snapshot of the current state of research and applications of data mining methods
in e-learning. the cross-fertilization of both areas is still in...criteria, firstly,
and from the data mining practitioner point of view, references are organized according to the type of modeling techniques
used, which include...