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DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing
In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named D...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859726/ https://www.ncbi.nlm.nih.gov/pubmed/33558822 http://dx.doi.org/10.1007/s12559-021-09825-w |
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author | Distante, Damiano Faralli, Stefano Rittinghaus, Steve Rosso, Paolo Samsami, Nima |
author_facet | Distante, Damiano Faralli, Stefano Rittinghaus, Steve Rosso, Paolo Samsami, Nima |
author_sort | Distante, Damiano |
collection | PubMed |
description | In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named DomainSenticNet, and contribute an unsupervised methodology to support the development of domain-aware Sentic applications. We developed an unsupervised methodology that, for each concept in OntoSenticNet, mines semantically related concepts from WordNet and Probase knowledge bases and computes domain distributional information from the entire collection of Kickstarter domain-specific crowdfunding campaigns. Subsequently, we applied DomainSenticNet to a prototype tool for Kickstarter campaign authoring and success prediction, demonstrating an improvement in the interpretability of sentiment intensities. DomainSenticNet is an extension of the OntoSenticNet ontology that integrates each of the 100,000 concepts included in OntoSenticNet with a set of semantically related concepts and domain distributional information. The defined unsupervised methodology is highly replicable and can be easily adapted to build similar domain-aware resources from different domain corpora and external knowledge bases. Used in combination with OntoSenticNet, DomainSenticNet may favor the development of novel hybrid aspect-based sentiment analysis systems and support further research on sentic computing in domain-aware applications. |
format | Online Article Text |
id | pubmed-7859726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-78597262021-02-04 DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing Distante, Damiano Faralli, Stefano Rittinghaus, Steve Rosso, Paolo Samsami, Nima Cognit Comput Article In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named DomainSenticNet, and contribute an unsupervised methodology to support the development of domain-aware Sentic applications. We developed an unsupervised methodology that, for each concept in OntoSenticNet, mines semantically related concepts from WordNet and Probase knowledge bases and computes domain distributional information from the entire collection of Kickstarter domain-specific crowdfunding campaigns. Subsequently, we applied DomainSenticNet to a prototype tool for Kickstarter campaign authoring and success prediction, demonstrating an improvement in the interpretability of sentiment intensities. DomainSenticNet is an extension of the OntoSenticNet ontology that integrates each of the 100,000 concepts included in OntoSenticNet with a set of semantically related concepts and domain distributional information. The defined unsupervised methodology is highly replicable and can be easily adapted to build similar domain-aware resources from different domain corpora and external knowledge bases. Used in combination with OntoSenticNet, DomainSenticNet may favor the development of novel hybrid aspect-based sentiment analysis systems and support further research on sentic computing in domain-aware applications. Springer US 2021-02-04 2022 /pmc/articles/PMC7859726/ /pubmed/33558822 http://dx.doi.org/10.1007/s12559-021-09825-w Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Distante, Damiano Faralli, Stefano Rittinghaus, Steve Rosso, Paolo Samsami, Nima DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title | DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title_full | DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title_fullStr | DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title_full_unstemmed | DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title_short | DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing |
title_sort | domainsenticnet: an ontology and a methodology enabling domain-aware sentic computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859726/ https://www.ncbi.nlm.nih.gov/pubmed/33558822 http://dx.doi.org/10.1007/s12559-021-09825-w |
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