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| Registros recuperados : 25 | |
| 6. |  | PRADO, H. A. do; MAGALHÃES, A. R.; FERNEDA, E. Reasoning about external environment from web sources. In: Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II. 5712 348-355 (Lecture Notes in Computer Science -LNCS, volume 5712).| Biblioteca(s): Embrapa Unidades Centrais. |
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| 8. | | OLIVEIRA, S. R. de M.; CABRAL, M. I. C.; FERNEDA, E.; BRASILEIRO, M. A. G. ALLOS: a tool to solve markovian models. In: INTERNATIONAL CONFERENCE APPLIED MODELLING, SIMULATION AND OPTIMIZATION, 1995, Cancun, Mexico. Proceedings... Anaheim, CA: IASTED-Acta Press, 1995. p. 53-57.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 13. | | PRADO, H. A. do; FERNEDA, E.; MORAIS, L. C. R.; LUIZ, A. J. B.; MATSURA, E. On the effectiveness of candlestick chart analysis for the Brazilian stock market. Procedia Computer Science, Valmiera, v. 22, p. 1136-1145, 2013. Edição de Proceedings of XVII International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Kitakyushu, 2013.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 14. | | PRADO, H. A. do; FERNEDA, E.; ANQUETIL, N.; TEIXEIRA, E. D'A. Counselor, a data mining based time estimation for software maintenance. In: In: VELÁSQUEZ, J. D.; RÍOS, S. A.; HOWLETT, R. J.; JAIN, L., C. (Ed.). Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II. 5712 p. 364-371 (Lecture Notes in Computer Science - LNCS, 5712).| Biblioteca(s): Embrapa Unidades Centrais. |
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| 15. | | OLIVEIRA, S. R. de M.; CABRAL, M. I. C.; FERNEDA, E.; BRASILEIRO, M. A. G. Conception and development of a tool to model and solve markovian models. In: INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY, 15., 1995, Arica, Chile. Proceedings... Santiago: Sociedad Chilena de Ciencia de la Computacion, 1995. p. 351-360. Editado por Nivio Ziviani, Jose Piquer, Berthier Ribeiro e Ricardo Baeza-Yates.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 16. | | CASTILHO, W. F.; LUCENA FILHO, G. J.; PRADO, H. A. do; FERNEDA, E.; AXT, M. A conceptual model for guiding the clustering analysis. In: INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, 12., 2008, Zagreb, Croatia. Proceedings. New York: Springer-Verlag Berlin Heidelberg, 2008. (Lecture notes in computer science, 5178). pt. 2, p. 483-490.| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
|
Data corrente: |
11/06/2010 |
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Data da última atualização: |
23/09/2019 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
PRADO, H. A. do; FERNEDA, E.; ANQUETIL, N.; TEIXEIRA, E. D'A. |
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Afiliação: |
HERCULES ANTONIO DO PRADO, SGE; EDILSON FERNEDA, Universidade Católica de Brasília; NICOLAS ANQUETIL, Universidade Católica de Brasília; ELIZABETH D'ARROCHELLA, Universidade Católica de Brasília. |
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Título: |
Counselor, a data mining based time estimation for software maintenance. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: In: VELÁSQUEZ, J. D.; RÍOS, S. A.; HOWLETT, R. J.; JAIN, L., C. (Ed.). Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II. |
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Volume: |
5712 |
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Páginas: |
p. 364-371 |
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Série: |
(Lecture Notes in Computer Science - LNCS, 5712). |
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DOI: |
10.1007/978-3-642-04592-9_46 |
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Idioma: |
Inglês |
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Conteúdo: |
Measuring and estimating are fundamental activities for the success of any project. In the software maintenance realm the lack of maturity, or even a low level of interest in adopting effective maintenance techniques and related metrics, have been pointed out as an important cause for the high costs involved. In this paper data mining techniques are applied to provide a sound estimation for the time required to accomplish a maintenance task. Based on real world data regarding maintenance requests, some regression models are built to predict the time required for each maintenance. Data on the team skill and the maintenance characteristics are mapped into values that predict better time estimations in comparison to the one predicted by the human expert. A particular finding from this research is that the time prediction provided by a human expert works as an inductive bias that improves the overall prediction accuracy. |
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Palavras-Chave: |
Data mining; Informal reasoning; Software maintenance. |
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Categoria do assunto: |
-- |
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Marc: |
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245 $aCounselor, a data mining based time estimation for software maintenance.$h[electronic resource]
260 $aIn: In: VELÁSQUEZ, J. D.; RÍOS, S. A.; HOWLETT, R. J.; JAIN, L., C. (Ed.). Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II.$c2009
300 $ap. 364-371 5712
490 $a(Lecture Notes in Computer Science - LNCS, 5712).$v5712
520 $aMeasuring and estimating are fundamental activities for the success of any project. In the software maintenance realm the lack of maturity, or even a low level of interest in adopting effective maintenance techniques and related metrics, have been pointed out as an important cause for the high costs involved. In this paper data mining techniques are applied to provide a sound estimation for the time required to accomplish a maintenance task. Based on real world data regarding maintenance requests, some regression models are built to predict the time required for each maintenance. Data on the team skill and the maintenance characteristics are mapped into values that predict better time estimations in comparison to the one predicted by the human expert. A particular finding from this research is that the time prediction provided by a human expert works as an inductive bias that improves the overall prediction accuracy.
653 $aData mining
653 $aInformal reasoning
653 $aSoftware maintenance
700 1 $aFERNEDA, E.
700 1 $aANQUETIL, N.
700 1 $aTEIXEIRA, E. D'A.
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