Representing Entities in the OntoDM Data Mining Ontology

Towards an Ontology of Data Mining Investigations

Motivated by the need for unification of the domain of data mining and the demand for formalized representation of outcomes of data mining investigations, we address the task of constructing an ontology of data mining. In this paper we present an updated version of the OntoDM ontology, that is based on a recent proposal of a general framework for data mining and it is aligned with the ontology ...

OntoDM: Towards an Ontology of Data Mining

Ontology-based Domain Modeling of Multi-Agent Systems

Ontologies are knowledge representation structures especially useful for the specification of high-level reusable software, like domain models and frameworks. This work describes GRAMO, an ontology-based technique for the specification of domain models in Multi-Agent Domain Engineering. ONTODM, an ontology-based tool supporting GRAMO is also introduced. ONTODM represents the knowledge of GRAMO....

Presenting a method for extracting structured domain-dependent information from Farsi Web pages

Extracting structured information about entities from web texts is an important task in web mining, natural language processing, and information extraction. Information extraction is useful in many applications including search engines, question-answering systems, recommender systems, machine translation, etc. An information extraction system aims to identify the entities from the text and extr...

Development of a Combined System Based on Data Mining and Semantic Web for the Diagnosis of Autism

Introduction: Autism is a nervous system disorder, and since there is no direct diagnosis for it, data mining can help diagnose the disease. Ontology as a backbone of the semantic web, a knowledge database with shareability and reusability, can be a confirmation of the correctness of disease diagnosis systems. This study aimed to provide a system for diagnosing autistic children with a combinat...