Expert System for Crop Disease based on Graph Pattern Matching: A proposal
DOI:
https://doi.org/10.22395/rium.v15n29a5Keywords:
expert system, graph, pattern matching, data mining, crop, disease, agricultureAbstract
For agroindustry, crop diseases constitute one of the most common problems that generate large economic losses and low production quality. On the other hand, from computer science, several tools have emerged in order to improve the prevention and treatment of these diseases. In this sense, recent research proposes the development of expert systems to solve this problem, making use of data mining and artificial intelligence techniques like rule-based inference, decision trees, Bayesian network, among others. Furthermore, graphs can be used for storage of different types of variables that are present in an environment of crops, allowing the application of graph data mining techniques like graph pattern matching. Therefore, in this paper we present an overview of the above issues and a proposal of an expert system for crop disease based on graph pattern matching.Downloads
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References
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[28] V. S. Pawar & M. A. Zaveri, “Graph based pattern matchingâ€, in 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Shangai, China, Jul. 26-28, 2011, vol. 2, pp. 1022-1026.
[29] W. E. Moustafa, A. Kimmig, A. Deshpande, & L. Getoor, “Subgraph pattern matching over uncertain graphs with identity linkage uncertaintyâ€, in 2014 ieee 30th International Conference on Data Engineering (icde), Chicago, USA, Mar. 31 - Apr. 4, 2014, pp. 904-915.
[30] H. Yamasaki, T. Yamada & T. Shoudai, “Graph Pattern Matching with Expressive Outerplanar Graph Patternsâ€, in Intelligent Control and Computer Engineering, Berlin: Springer, 2011, pp. 231-243.
[31] J. Mendivelso & Y. Pinzon, “A new approach to isomorphism in attributed graphsâ€, in 9th Computing Colombian Conference (9ccc), Pereira, Colombia, Sept. 3-5, 2014, pp. 231-239.
[32] J. F. Baget & M. L. Mugnier, “Extensions of simple conceptual graphs: the complexity of rules and constraintsâ€, J. Artif. Intell. Res., vol. 16, pp. 425-465, 2002.
[33] K. Higa & H. G. Lee, “A graph-based approach for rule integrity and maintainability in expert system maintenanceâ€, Inf. Manage., vol. 33, no. 6, pp. 273-285, 1998.
[34] B. Kamsu-Foguem & D. Noyes, “Graph-based reasoning in collaborative knowledge management for industrial maintenanceâ€, Comput. Ind., vol. 64, no. 8, pp. 998-1013, 2013.
[35] M. Chein, “Graph-Based Knowledge Representation and Reasoningâ€, in iceis’10: 12th International Conference on Enterprise Information Systems, Funchal, Madeira - Portugal, Jun. 8-12, 2010.
[36] P. Buche, V. Cucheval, A. Diattara, J. Fortin, & A. Gutiérrez, “Implementation of a knowledge representation and reasoning tool using default rules for a decision support system in agronomy applicationsâ€, in Graph Structures for Knowledge Representation and Reasoning, Berlin: Springer, 2014, pp. 1-12.
[37] T. Liu, C. Tian, F. Li, & H. Zhang, “Rule graph: Incorporate expert and statistical knowledge for rule executionâ€, in ieee/informs International Conference on Service Operations, Logistics and Informatics, soli’09, Chicago, USA, Jul. 22-24, 2009, pp. 573-578.
[38] S. Peter, F. Hoppner & M. R. Berthold, “Pattern graphs: A knowledge-based tool for multivariate temporal pattern retrievalâ€, in 6th ieee International Conference Intelligent Systems (IS), SOFIA, BULGARIA, SEP. 6-8, 2012, pp. 67-73.
[39] W. Fan, J. Li, S. Ma, N. Tang, Y. Wu, & Y. Wu, “Graph pattern matching: from intractable to polynomial timeâ€, Proc. VLDB Endow., vol. 3, no. 1–2, pp. 264-275, 2010.
[2] E. Turban & L. E. Frenzel, Expert systems and applied artificial intelligence, United States: Prentice Hall Professional Technical Reference, 1992.
[3] M. Rowe, “Applying semantic social graphs to disambiguate identity referencesâ€, in The Semantic Web: Research and Applications, Berlin: Springer, 2009, pp. 461-475.
[4] C. C. Aggarwal & H. Wang, “An Introduction to Graph Dataâ€, in Managing and Mining Graph Data, Berlin: Springer, 2010, pp. 1-11.
[5] D. J. Cook & L. B. Holder, Mining graph data. Hoboken, NJ, USA: John Wiley & Sons, 2006.
[6] X. Wang, “Graph pattern matching on social network analysisâ€, PhD thesis, University of Edinburgh, Edinburgh, Scotland, 2013. Available: http://hdl.handle.net/1842/8277
[7] S. Dewanto & J. Lukas, “Expert System For Diagnosis Pest And Disease In Fruit Plantsâ€, EPJ Web of Conferences, vol. 68, no. 24, pp. 1-4, 2014.
[8] J. R. Quinlan, “Generating Production Rules from Decision Treesâ€, in ijcai’87 Proceedings of the 10th international joint conference on Artificial intelligence, Milan, Italy, Aug. 23-29, 1987, pp. 304-307.
[9] R. A. Hanneman & M. Riddle, Introduction to social network methods. Riverside, California: University of California, 2005. Available: http://faculty.ucr.edu/~hanneman/nettext/
[10] G. Erétéo et al., “Semantic Social Network Analysis: A Concrete Caseâ€, Handbook of research on methods and techniques for studying virtual communities: paradigms and phenomena, vol. 1, pp. 122-156, 2011.
[11] E. G. Lasso-Sambony, S. M. Ortega-Ponce, & J. C. Corrales, “Semantic enrichment and inference of relationships in an online social networkâ€, Ing. Univ., vol. 17, no. 2, pp. 355-373, 2013.
[12] G. Mansingh, H. Reichgelt, & K. M. O. Bryson, “CPEST: An expert system for the management of pests and diseases in the Jamaican coffee industryâ€, Expert Syst. Appl., vol. 32, No. 1, pp. 184-192, 2007.
[13] W. A. Derwin Suhartono, M. Lestari, & M. Yasin, “Expert System in Detecting Coffee Plant Diseasesâ€, Int. J. Electr. Energy, vol. 1, No. 3, pp. 156-162, 2013.
[14] V. Rossi, P. Meriggi, T. Caffi, S. Giosué, & T. Bettati, “A Web-based Decision Support System for Managing Durum Wheat Cropsâ€, in Decision Support Systems, Advances in, G. Devlin, Ed., Vukovar, Croatia: Intech, 2010. Available: http://www.intechopen.com/books/decisionsupport-systems-advances-in/a-web-based-decision-support-system-for-managing-durumwheat-crops
[15] R. F. Chevalier, G. Hoogenboom, R. W. McClendon, & J. O. Paz, “A web-based fuzzy expert system for frost warnings in horticultural crops,†Environ. Model. Softw., vol. 35, pp. 84-91, 2012.
[16] R. Jain et al., “Machine learning for forewarning crop diseasesâ€, J Ind Soc Agril Stat., vol. 63, no. 1, pp. 97-107, 2009.
[17] M. E. Cintra, C. A. A. Meira, M. C. Monard, H. A. Camargo & L. H. A. Rodrigues, “The use of fuzzy decision trees for coffee rust warning in Brazilian cropsâ€, in 11th International Conference on Intelligent Systems Design and Applications (isda) Cordoba, Spain, Nov, 22-24, 2011, pp. 1347–1352.
[18] M. Omid, “Design of an expert system for sorting pistachio nuts through decision tree and fuzzy logic classifierâ€, Expert Syst. Appl., vol. 38, no. 4, pp. 4339-4347, 2011.
[19] J. Molineros, E. De Wolf, L. Francl, L. Madden, & P. Lipps, “Modeling epidemics of fusarium head blight: trials and tribulationsâ€, Phytopathology, vol. 95, no. 6, 2005.
[20] K. Ogaard, H. Roy, S. Kase, R. Nagi, K. Sambhoos, & M. Sudit, “Discovering patterns in social networks with graph matching algorithmsâ€, in Social Computing, Behavioral-Cultural Modeling and Prediction, Berlin: Springer, 2013, pp. 341-349.
[21] K. P. Sambhoos, “Graph matching applications in high level information fusionâ€. Dissertation, State University of New York at Buffalo, ProQuest Dissertations Publishing, 2007.
[22] Y. Bai, C. Wang, Y. Ning, H. Wu, & H. Wang, “G-path: flexible path pattern query on large graphsâ€, in Proceedings of the 22nd international conference on World Wide Web companion, Rio de Janeiro, Brazil, May 13-17, 2013, pp. 333–336.
[23] G. Kollias, M. Sathe, O. Schenk, & A. Grama, “Fast parallel algorithms for graph similarity and matchingâ€, J. Parallel Distrib. Comput., vol. 74, no. 5, pp. 2400-2410, 2014.
[24] G. Kollias, S. Mohammadi, & A. Grama, “Network Similarity Decomposition (NSD): A Fast and Scalable Approach to Network Alignmentâ€, IEEE Trans. Knowl. Data Eng., vol. 24, no. 12, pp. 2232-2243, Dec. 2012.
[25] L. P. Cordella, P. Foggia, C. Sansone, & M. Vento, “A (sub) graph isomorphism algorithm for matching large graphsâ€, Pattern Anal. Mach. Intell. IEEE Trans. On, vol. 26, no. 10, pp. 1367-1372, 2004.
[26] L. P. Cordella, P. Foggia, C. Sansone, & M. Vento, “Performance evaluation of the VF graph matching algorithmâ€, in Proceedings 1999 10th International Conference on Image Analysis and Processing, Venice, Italy, Sep. 27-29, 1999, pp. 1172-1177.
[27] J. R. Ullmann, “An algorithm for subgraph isomorphismâ€, J. ACM JACM, vol. 23, no. 1, pp. 31-42, 1976.
[28] V. S. Pawar & M. A. Zaveri, “Graph based pattern matchingâ€, in 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Shangai, China, Jul. 26-28, 2011, vol. 2, pp. 1022-1026.
[29] W. E. Moustafa, A. Kimmig, A. Deshpande, & L. Getoor, “Subgraph pattern matching over uncertain graphs with identity linkage uncertaintyâ€, in 2014 ieee 30th International Conference on Data Engineering (icde), Chicago, USA, Mar. 31 - Apr. 4, 2014, pp. 904-915.
[30] H. Yamasaki, T. Yamada & T. Shoudai, “Graph Pattern Matching with Expressive Outerplanar Graph Patternsâ€, in Intelligent Control and Computer Engineering, Berlin: Springer, 2011, pp. 231-243.
[31] J. Mendivelso & Y. Pinzon, “A new approach to isomorphism in attributed graphsâ€, in 9th Computing Colombian Conference (9ccc), Pereira, Colombia, Sept. 3-5, 2014, pp. 231-239.
[32] J. F. Baget & M. L. Mugnier, “Extensions of simple conceptual graphs: the complexity of rules and constraintsâ€, J. Artif. Intell. Res., vol. 16, pp. 425-465, 2002.
[33] K. Higa & H. G. Lee, “A graph-based approach for rule integrity and maintainability in expert system maintenanceâ€, Inf. Manage., vol. 33, no. 6, pp. 273-285, 1998.
[34] B. Kamsu-Foguem & D. Noyes, “Graph-based reasoning in collaborative knowledge management for industrial maintenanceâ€, Comput. Ind., vol. 64, no. 8, pp. 998-1013, 2013.
[35] M. Chein, “Graph-Based Knowledge Representation and Reasoningâ€, in iceis’10: 12th International Conference on Enterprise Information Systems, Funchal, Madeira - Portugal, Jun. 8-12, 2010.
[36] P. Buche, V. Cucheval, A. Diattara, J. Fortin, & A. Gutiérrez, “Implementation of a knowledge representation and reasoning tool using default rules for a decision support system in agronomy applicationsâ€, in Graph Structures for Knowledge Representation and Reasoning, Berlin: Springer, 2014, pp. 1-12.
[37] T. Liu, C. Tian, F. Li, & H. Zhang, “Rule graph: Incorporate expert and statistical knowledge for rule executionâ€, in ieee/informs International Conference on Service Operations, Logistics and Informatics, soli’09, Chicago, USA, Jul. 22-24, 2009, pp. 573-578.
[38] S. Peter, F. Hoppner & M. R. Berthold, “Pattern graphs: A knowledge-based tool for multivariate temporal pattern retrievalâ€, in 6th ieee International Conference Intelligent Systems (IS), SOFIA, BULGARIA, SEP. 6-8, 2012, pp. 67-73.
[39] W. Fan, J. Li, S. Ma, N. Tang, Y. Wu, & Y. Wu, “Graph pattern matching: from intractable to polynomial timeâ€, Proc. VLDB Endow., vol. 3, no. 1–2, pp. 264-275, 2010.
Published
2015-11-07
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Lasso Sambony, E., & Corrales, J. C. (2015). Expert System for Crop Disease based on Graph Pattern Matching: A proposal. Revista IngenierÃas Universidad De MedellÃn, 15(29), 81–98. https://doi.org/10.22395/rium.v15n29a5
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