research-article

SIM: um modelo semântico-inferencialista para sistemas de linguagem natural

Authors:

Vládia Pinheiro,

Tarcisio Pequeno,

Thiago Assunção,

Emanoel FreitasAuthors Info & Claims

WebMedia '08: Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web

Pages 353 - 358

https://doi.org/10.1145/1809980.1810065

Published: 26 October 2008 Publication History

Abstract

One of the growing needs related to systems of Natural Language Processing (NLP) is that such systems must be able to perform enriched textual inferences. We argue that one reason for the current limitation of the inferences generated by these systems is that---for the most part---they are based on the characteristics of the things represented by names, and seek to draw inferences based on such characteristics. In this work, we propose the Semantic Inferentialism Model (SIM), which follows a natural path and represents a new paradigm: it seeks to express the inferential capacity of concepts and how these concepts, combined in sentence structures, contribute to the inferential power of sentences. We present a SIM-based Information Extraction System and a pre-evaluation of the results.

References

[1]

Liu, H. and Singh, P. (2004) ConceptNet: A Practical Commonsense Reasoning Toolkit. BT Technology Journal, Volume 22(4). Kluwer Academic Publishers.

Digital Library

[2]

Dummett, M. (1978) Truth and Other Enigmas. Duckworth, London.

[3]

Brandom, R. B. (2000) Articulating Reasons. In: An Introduction to Inferentialism. Harvard University Press, Cambridge.

[4]

Wittgenstein, L. (1953) Philosophical Investigations. Tradução G. E. M. Anscombe, Oxford: Basil Blackwell.

[5]

Fellbaum, C. (Ed.). (1998). WordNet: An electronic lexical database. MIT Press.

[6]

Lenat, D. B. (1995) CYC: A large-scale investment in knowledge infrastructure. Communications of the ACM, 38(11).

Digital Library

[7]

Cohen, K., Hunter, L. (2008) Getting staterd in text mining. PLoS Compt Biology, 4(1).

[8]

Java, A. et al. (2007). Using a Natural Language Understanding System to Generate Semantic Web Content. International Journal on Semantic Web and Information Systems. November.

[9]

Hirst, G., St-Onge, D. (1998). Lexical chains as representations of context for the detection and correction of malapropisms. In Fellbaum 1998, pp. 305--332.

[10]

Leacock, C., Chodorow, M. (1998). Combining local context and WordNet similarity for word sense identification. In Fellbaum 1998, pp. 265--283.

[11]

Resnik, P. (1995). Using information content to evaluate semantic similarity. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, pages 448--453, Montreal.

Digital Library

[12]

Jiang, J., Conrath, D. (1997). Semantic similarity based on corpus statistics and lexical taxonomy. In Proceedings of International Conference on Research in Computational Linguistics, Taiwan.

[13]

Lin, D. (1998). An information-theoretic definition of similarity. In Proceedings of the 15th International Conference on Machine Learning. Madison, WI.

Digital Library

[14]

De Paiva, V. et al. (2007) Textual Inference Logic: Take Two. Proceedings of the Workshop on Contexts and Ontologies, Representation and Reasoning, CONTEXT 2007

[15]

Saias, J e Quaresma, P. (2006). A proposal for an ontology supported news reader and question-answer system. Proceedings of the 2nd Workshop on Ontologies and their Applications.

[16]

Mellish, C e Pan, J, Z. (2008) Natural language directed inference from ontologies. Artificial IIntelligence, Volume 172, Issue 10 (Junnho 2008), pp. 1285--1315.

Digital Library

Cited By

Franco WAlves TViana HAlcântara J(2012)A description logic for inferencenet.brProceedings of the 10th international conference on Computational Processing of the Portuguese Language10.1007/978-3-642-28885-2_34(298-305)Online publication date: 17-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-28885-2_34
Pinheiro VFurtado VPequeno TNogueira D(2010)Natural Language Processing based on Semantic inferentialism for extracting crime information from text2010 IEEE International Conference on Intelligence and Security Informatics10.1109/ISI.2010.5484783(19-24)Online publication date: May-2010
https://doi.org/10.1109/ISI.2010.5484783
Pinheiro VPequeno TFurtado VFranco W(2010)InferenceNet.BrProceedings of the 9th international conference on Computational Processing of the Portuguese Language10.1007/978-3-642-12320-7_12(90-99)Online publication date: 27-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12320-7_12
Show More Cited By

Index Terms

SIM: um modelo semântico-inferencialista para sistemas de linguagem natural
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

Recommendations

NK-Sim: A Negotiation Simulator
SBSC-II '10: Proceedings of the 2010 Brazilian Symposium on Collaborative Systems II - Simpósio Brasileiro de Sistemas Colaborativos II

Atualmente, com o uso efetivo da tecnologia, a comunicação e interação entre as pessoas têm sido alteradas. Estas mudanças influenciam diferentes contextos e a negociação é um deles. Além do acesso à informação, o uso de ferramentas computacionais já é ...
Estágio Na Empresa Assec Sim Projeto de Design de Um Sistema de Gestão Para Hotéis
Modelação de Mundos Virtuais 3D: Análise Comparativa e Avaliação da Qualidade de Mundos Virtuais

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

WebMedia '08: Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web

October 2008

420 pages

ISBN:9788576691990

DOI:10.1145/1809980

Copyright © 2008 2008 Brazilian Computer Society.

Sponsors

SBC: Brazilian Computer Society

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2008

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

WebMedia08

Sponsor:

SBC

WebMedia08: 14th Brazilian Symposium on Multimedia and Web Systems

October 26 - 29, 2008

Espírito Santo, Vila Velha, Brazil

Acceptance Rates

Overall Acceptance Rate 270 of 873 submissions, 31%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
82
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 17 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Franco WAlves TViana HAlcântara J(2012)A description logic for inferencenet.brProceedings of the 10th international conference on Computational Processing of the Portuguese Language10.1007/978-3-642-28885-2_34(298-305)Online publication date: 17-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-28885-2_34
Pinheiro VFurtado VPequeno TNogueira D(2010)Natural Language Processing based on Semantic inferentialism for extracting crime information from text2010 IEEE International Conference on Intelligence and Security Informatics10.1109/ISI.2010.5484783(19-24)Online publication date: May-2010
https://doi.org/10.1109/ISI.2010.5484783
Pinheiro VPequeno TFurtado VFranco W(2010)InferenceNet.BrProceedings of the 9th international conference on Computational Processing of the Portuguese Language10.1007/978-3-642-12320-7_12(90-99)Online publication date: 27-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12320-7_12
Pinheiro VPequeno TFurtado VNogueira D(2009)Semantic Inferentialist AnalyserProceedings of the 2009 Seventh Brazilian Symposium in Information and Human Language Technology10.1109/STIL.2009.14(89-97)Online publication date: 8-Sep-2009
https://dl.acm.org/doi/10.1109/STIL.2009.14

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents