Analysis of decomposition parameters of green manure in the brazilian northeast with association rules networks (2017)
- Authors:
- USP affiliated author: REZENDE, SOLANGE OLIVEIRA - ICMC
- School: ICMC
- Subjects: MINERAÇÃO DE DADOS; COMPUTAÇÃO APLICADA; AGRICULTURA DE PRECISÃO
- Language: Inglês
- Imprenta:
- Publisher: Universidad de la República
- Place of publication: Montevideo
- Date published: 2017
- Source:
- Título do periódico: Proceedings
- ISSN: 9789974015142
- Conference title: International Conference on Agro Big Data and Decision Support Systems in Agriculture - BigDSSAgro
-
ABNT
CALÇADA, Dario Brito e REZENDE, Solange Oliveira e TEODORO, Mauro Sergio. Analysis of decomposition parameters of green manure in the brazilian northeast with association rules networks. 2017, Anais.. Montevideo: Universidad de la República, 2017. Disponível em: http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf. Acesso em: 05 jul. 2022. -
APA
Calçada, D. B., Rezende, S. O., & Teodoro, M. S. (2017). Analysis of decomposition parameters of green manure in the brazilian northeast with association rules networks. In Proceedings. Montevideo: Universidad de la República. Recuperado de http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf -
NLM
Calçada DB, Rezende SO, Teodoro MS. Analysis of decomposition parameters of green manure in the brazilian northeast with association rules networks [Internet]. Proceedings. 2017 ;[citado 2022 jul. 05 ] Available from: http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf -
Vancouver
Calçada DB, Rezende SO, Teodoro MS. Analysis of decomposition parameters of green manure in the brazilian northeast with association rules networks [Internet]. Proceedings. 2017 ;[citado 2022 jul. 05 ] Available from: http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf - A methodology for identifying interesting association rules by combining objective and subjective measures
- Transforming geo-referenced data in contextual information for context-aware recommender systems
- Solving the problem of selecting suitable objective measures by clustering association rules through the measures themselves
- Using topic hierarchies with privileged information to improve context-aware recommender systems
- Named entities as privileged information for hierarchical text clustering
- Fuzzy cluster descriptor extraction for flexible organization of documents
- Selecting Candidate Labels For Hierarchical Document Clusters Using Association Rules
- Latent association rule cluster based model to extract topics for classification and recommendation applications
- Cross-domain aspect extraction for sentiment analysis: a transductive learning approach
- Implementação de taxomanias para regras de associação em um ambiente de pós-processamento. (CDROM)
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