FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4293657568> ?p ?o ?g. }

• W4293657568 endingPage "436" @default.
• W4293657568 startingPage "425" @default.
• W4293657568 abstract "AbstractModel Driven Engineering (MDE), where models are the core elements in the entire life cycle from the specification to maintenance phases, is one of the promising techniques to provide abstraction and automation. However, model management is another challenging issue due to the increasing number of models, their size, and their structural complexity. So that the available models should be organized by modelers to be reused and overcome the development of the new and more complex models with less cost and effort. In this direction, many studies are conducted to categorize models automatically. However, most of the studies focus either on the textual data or structural information in the intelligent model management, leading to less precision in the model management activities. Therefore, we utilized a model classification using baseline machine learning approaches on a dataset including 555 Ecore metamodels through hybrid feature vectors including both textual and structural information. In the proposed approach, first, the textual information of each model has been summarized in its elements through text processing as well as the ontology of synonyms within a specific domain. Then, the performances of machine learning classifiers were observed on two different variants of the datasets. The first variant includes only textual features (represented both in TF-IDF and word2vec representations), whereas the second variant consists of the determined structural features and textual features. It was finally concluded that each experimented machine learning algorithm gave more successful prediction performance on the variant containing structural features. The presented model yields promising results for the model classification task with a classification accuracy of 89.16%.KeywordsModel Driven EngineeringModel managementMetamodelText miningMachine learning" @default.
• W4293657568 created "2022-08-31" @default.
• W4293657568 creator A5005916463 @default.
• W4293657568 creator A5006565100 @default.
• W4293657568 creator A5022206451 @default.
• W4293657568 creator A5051281047 @default.
• W4293657568 date "2022-01-01" @default.
• W4293657568 modified "2023-09-29" @default.
• W4293657568 title "Machine Learning-Based Model Categorization Using Textual and Structural Features" @default.
• W4293657568 cites W2150874198 @default.
• W4293657568 cites W2158864412 @default.
• W4293657568 cites W2165612380 @default.
• W4293657568 cites W2463902528 @default.
• W4293657568 cites W2514429266 @default.
• W4293657568 cites W2541118606 @default.
• W4293657568 cites W2567819128 @default.
• W4293657568 cites W2793961873 @default.
• W4293657568 cites W2921408465 @default.
• W4293657568 cites W2965935205 @default.
• W4293657568 cites W2974245602 @default.
• W4293657568 cites W2990371862 @default.
• W4293657568 cites W3132422305 @default.
• W4293657568 cites W3155816843 @default.
• W4293657568 cites W4230097545 @default.
• W4293657568 cites W4239025696 @default.
• W4293657568 cites W4285244577 @default.
• W4293657568 doi "https://doi.org/10.1007/978-3-031-15743-1_39" @default.
• W4293657568 hasPublicationYear "2022" @default.
• W4293657568 type Work @default.
• W4293657568 citedByCount "0" @default.
• W4293657568 crossrefType "book-chapter" @default.
• W4293657568 hasAuthorship W4293657568A5005916463 @default.
• W4293657568 hasAuthorship W4293657568A5006565100 @default.
• W4293657568 hasAuthorship W4293657568A5022206451 @default.
• W4293657568 hasAuthorship W4293657568A5051281047 @default.
• W4293657568 hasConcept C108583219 @default.
• W4293657568 hasConcept C111472728 @default.
• W4293657568 hasConcept C115901376 @default.
• W4293657568 hasConcept C119857082 @default.
• W4293657568 hasConcept C124304363 @default.
• W4293657568 hasConcept C127413603 @default.
• W4293657568 hasConcept C134306372 @default.
• W4293657568 hasConcept C138885662 @default.
• W4293657568 hasConcept C154945302 @default.
• W4293657568 hasConcept C162324750 @default.
• W4293657568 hasConcept C187736073 @default.
• W4293657568 hasConcept C204321447 @default.
• W4293657568 hasConcept C25810664 @default.
• W4293657568 hasConcept C2776401178 @default.
• W4293657568 hasConcept C2776461190 @default.
• W4293657568 hasConcept C2778827112 @default.
• W4293657568 hasConcept C2780451532 @default.
• W4293657568 hasConcept C33923547 @default.
• W4293657568 hasConcept C36503486 @default.
• W4293657568 hasConcept C41008148 @default.
• W4293657568 hasConcept C41608201 @default.
• W4293657568 hasConcept C41895202 @default.
• W4293657568 hasConcept C78519656 @default.
• W4293657568 hasConcept C94124525 @default.
• W4293657568 hasConceptScore W4293657568C108583219 @default.
• W4293657568 hasConceptScore W4293657568C111472728 @default.
• W4293657568 hasConceptScore W4293657568C115901376 @default.
• W4293657568 hasConceptScore W4293657568C119857082 @default.
• W4293657568 hasConceptScore W4293657568C124304363 @default.
• W4293657568 hasConceptScore W4293657568C127413603 @default.
• W4293657568 hasConceptScore W4293657568C134306372 @default.
• W4293657568 hasConceptScore W4293657568C138885662 @default.
• W4293657568 hasConceptScore W4293657568C154945302 @default.
• W4293657568 hasConceptScore W4293657568C162324750 @default.
• W4293657568 hasConceptScore W4293657568C187736073 @default.
• W4293657568 hasConceptScore W4293657568C204321447 @default.
• W4293657568 hasConceptScore W4293657568C25810664 @default.
• W4293657568 hasConceptScore W4293657568C2776401178 @default.
• W4293657568 hasConceptScore W4293657568C2776461190 @default.
• W4293657568 hasConceptScore W4293657568C2778827112 @default.
• W4293657568 hasConceptScore W4293657568C2780451532 @default.
• W4293657568 hasConceptScore W4293657568C33923547 @default.
• W4293657568 hasConceptScore W4293657568C36503486 @default.
• W4293657568 hasConceptScore W4293657568C41008148 @default.
• W4293657568 hasConceptScore W4293657568C41608201 @default.
• W4293657568 hasConceptScore W4293657568C41895202 @default.
• W4293657568 hasConceptScore W4293657568C78519656 @default.
• W4293657568 hasConceptScore W4293657568C94124525 @default.
• W4293657568 hasLocation W42936575681 @default.
• W4293657568 hasOpenAccess W4293657568 @default.
• W4293657568 hasPrimaryLocation W42936575681 @default.
• W4293657568 hasRelatedWork W1559308966 @default.
• W4293657568 hasRelatedWork W199960160 @default.
• W4293657568 hasRelatedWork W2004575302 @default.
• W4293657568 hasRelatedWork W2362192218 @default.
• W4293657568 hasRelatedWork W262071733 @default.
• W4293657568 hasRelatedWork W2746217931 @default.
• W4293657568 hasRelatedWork W2773694660 @default.
• W4293657568 hasRelatedWork W3107474891 @default.
• W4293657568 hasRelatedWork W3200179079 @default.
• W4293657568 hasRelatedWork W2494682052 @default.
• W4293657568 isParatext "false" @default.
• W4293657568 isRetracted "false" @default.

• next