Expert System for Crop Disease based on Graph Pattern Matching: A proposal

Emmanuel Lasso Sambony | Bio
Universidad del Cauca
Juan Carlos Corrales | Bio
Universidad del Cauca

Abstract

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.

References

[1] Ministerio de Tecnologías de la Información y las Comunicaciones, MinTIC, “Plan nacional de ciencia, tecnología e innovación para el desarrollo de los sectores electrónica, tecnologías de la información y las comunicaciones (etic) en Colombia”, Resumen ejecutivo, 2013.

[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 references”, in The Semantic Web: Research and Applications, Berlin: Springer, 2009, pp. 461-475.

[4] C. C. Aggarwal & H. Wang, “An Introduction to Graph Data”, 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 analysis”, 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 Plants”, EPJ Web of Conferences, vol. 68, no. 24, pp. 1-4, 2014.

[8] J. R. Quinlan, “Generating Production Rules from Decision Trees”, 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 Case”, 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 network”, 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 industry”, 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 Diseases”, 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 Crops”, 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 diseases”, 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 crops”, 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 classifier”, 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 tribulations”, 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 algorithms”, 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 fusion”. 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 graphs”, 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 matching”, 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 Alignment”, 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 graphs”, 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 algorithm”, 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 isomorphism”, J. ACM JACM, vol. 23, no. 1, pp. 31-42, 1976.

[28] V. S. Pawar & M. A. Zaveri, “Graph based pattern matching”, 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 uncertainty”, 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 Patterns”, in Intelligent Control and Computer Engineering, Berlin: Springer, 2011, pp. 231-243.

[31] J. Mendivelso & Y. Pinzon, “A new approach to isomorphism in attributed graphs”, 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 constraints”, 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 maintenance”, 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 maintenance”, Comput. Ind., vol. 64, no. 8, pp. 998-1013, 2013.

[35] M. Chein, “Graph-Based Knowledge Representation and Reasoning”, 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 applications”, 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 execution”, 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 retrieval”, 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 time”, Proc. VLDB Endow., vol. 3, no. 1–2, pp. 264-275, 2010.
How to Cite
Lasso Sambony, E., & Corrales, J. C. (2015). Expert System for Crop Disease based on Graph Pattern Matching: A proposal. Revista Ingenierías Universidad De Medellín, 15(29), 81-98. https://doi.org/10.22395/rium.v15n29a5

Downloads

Download data is not yet available.

Send mail to Author


Send Cancel

We are indexed in