A domain-independent process for automatic ontology population from text

Faria, Carla Gomes de; Serra, Ivo; Girardi, Rosario

doi:10.1016/j.scico.2013.12.005

Cited by 42 publications

(22 citation statements)

References 3 publications

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“…Ontologies can model interaction systems between users and their environment, since to its property to manage complex knowledge in reusable formal representations. Formally, ontology can be defined such as (Faria et al, 2014):…”

Section: Ontology Learningmentioning

confidence: 99%

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A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

Alemán¹,

Somodevilla²,

Vilariño³

2018

CIS

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The knowledge bases of the Web are fundamentally organized in ontologies in order to answer queries based on semantics. The ontologies learning process comprises three fundamental steps: creation of classes and relationships, population and evaluation. In this paper the focus includes the classes creation, by introducing a class validation proposal using clustering analysis. As case of study was selected a pedagogical domain, where a corpus was semi-automatically built, from articles written in Spanish published in Social Sciences. Moreover, a dictionary containing classes, concepts and synonyms was included in the experiments. Clustering analysis allowed to verify the concepts that the experts considered as the most important for the domain. For the case of study selected, the cluster analysis step reports clusters with the same instances that the clusters defined by the experts.

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Section: Ontology Learningmentioning

confidence: 99%

“…The input is an ontology and a corpus where the candidate instances are identified. Using a classifier, the instances are labeled with a class and finally, the output is the ontology populated (Faria et al, 2014).…”

Section: Ontology Learningmentioning

confidence: 99%

A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

Alemán¹,

Somodevilla²,

Vilariño³

2018

CIS

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“…The fourth paper [9] proposes an automatic process for ontology population from a corpus of texts. The proposed process is independent from the domain of discourse and aims to enrich the initial ontology with non taxonomic relations and ontology class properties instances.…”

Section: Related Workmentioning

confidence: 99%

A Domain Independent Approach for Ontology Semantic Enrichment

Guerram¹,

Mellal²

2018

Computer Science &Amp; Information Technology

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“…Domain ontologies are the cornerstone of informatics systems [6,7]. In this work, the ontology mainly serves as a classification system (or a taxonomy) and assists in performing semantic expansion.…”

Section: B Domain Ontologiesmentioning

confidence: 99%

A Centralized System for Managing, Archiving and Serving Scientific Data in Ecohydrological Research

Huang¹,

Tian²

2015

Proceedings of the 2nd International Conference on Intelligent Computing and Cognitive Informatics

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Abstract-Transboundary and cross-catchment access to ecohydrological data is the key to designing successful environmental policies and activities. Access to and visual representation of scientific information for the public is essential for attracting greater awareness of ecosystem matters. This requires a centralized system to bring together diverse data so that they can be integrated and analyzed in a single environment. This paper presents the efforts of combining web services and ontologies to address these challenges. In this study, a centralized system for managing, archiving and serving scientific data in ecohydrological research was designed and developed. The system enables to mash-up both observations and modeling results together. The applicability of the system is demonstrated through a case study in the Heihe River Basin located in northwestern China.

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A domain-independent process for automatic ontology population from text

Cited by 42 publications

References 3 publications

A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

A Class Validation Proposal of a Pedagogic Domain Ontology based on Clustering Analysis

A Domain Independent Approach for Ontology Semantic Enrichment

A Centralized System for Managing, Archiving and Serving Scientific Data in Ecohydrological Research

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