Combining Artificial Intelligence, Ontology, and Frequency-based Approaches to Recommend Activities in Scientific Workflows

dc.contributorCAPESen-US
dc.creatorKhouri, Adilson Lopes
dc.creatorDigiampietri, Luciano Antonio
dc.date2018-02-18
dc.date.accessioned2018-11-07T21:09:50Z
dc.date.available2018-11-07T21:09:50Z
dc.identifierhttps://seer.ufrgs.br/rita/article/view/RITA_VOL25_NR1_39
dc.identifier10.22456/2175-2745.75048
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2187567
dc.descriptionThe number of activities provided by scientific workflow management systems is large, which requires scientists to know many of them to take advantage of the reusability of these systems. To minimize this problem, the literature presents some techniques to recommend activities during the scientific workflow construction. In this paper we specified and developed a hybrid activity recommendation system considering information on frequency, input and outputs of activities and ontological annotations. Additionally, this paper presents a modeling of activities recommendation as a classification problem, tested using 5 classifiers; 5 regressors; and a composite approach which uses a Support Vector Machine (SVM) classifier, combining the results of other classifiers and regressors to recommend; and Rotation Forest, an ensemble of classifiers. The proposed technique was compared to related techniques and to classifiers and regressors, using 10-fold-cross-validation, achieving a Mean Reciprocal Rank (MRR) at least 70% greater than those obtained by classical techniques.en-US
dc.formatapplication/pdf
dc.languageeng
dc.publisherInstituto de Informática - Universidade Federal do Rio Grande do Sulen-US
dc.relationhttps://seer.ufrgs.br/rita/article/view/RITA_VOL25_NR1_39/pdf_1
dc.rightsDireitos autorais 2018 Adilson Lopes Khouri, Luciano Antonio Digiampietript-BR
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0pt-BR
dc.sourceRevista de Informática Teórica e Aplicada; v. 25, n. 1 (2018); 39-47en-US
dc.sourceRevista de Informática Teórica e Aplicada; v. 25, n. 1 (2018); 39-47pt-BR
dc.source21752745
dc.source01034308
dc.subjectcomputer science, artificial intelligenceen-US
dc.subjectrecommendation system, scientific workflows, artificial intelligence, ontologyen-US
dc.titleCombining Artificial Intelligence, Ontology, and Frequency-based Approaches to Recommend Activities in Scientific Workflowsen-US
dc.typeArtículos de revistas
dc.typeArtículos de revistas


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