@article {546,
	title = {Expert system for crop disease based on graph pattern matching: a proposal},
	journal = {Revista Ingenier{\'\i}as },
	volume = {15},
	year = {2016},
	publisher = {Universidad de Medell{\'\i}n},
	chapter = {81-98},
	abstract = {<p class="rtejustify"><span style="font-family: verdana, arial; font-size: 12.7962px; text-align: start;">For agroindustry, crop diseases constitute one of the most common prob lems that generate great economic losses and low production quality. On the other hand, from the field of computer science, several tools have emerged that may 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 to store different types of variables present in a crop environment, allowing the application of graph data mining techniques like graph pattern matching. In this paper, we present an overview of the above issues and the proposal of an expert system for crop disease based on graph pattern matching.</span></p>
},
	keywords = {expert system; graph pattern matching; data mining; crop; disease; agriculture},
	issn = {1692-3324},
	doi = {http://dx.doi.org/10.22395/rium.v15n29a5 },
	url = {http://www.scielo.org.co/scielo.php?pid=S1692-33242016000200081\&script=sci_arttext\&tlng=en},
	author = {Lasso, E. and Corrales, J. C.}
}
