A Unified Model Representation of Machine Learning Knowledge

Authors

  • J. G. Enríquez Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain
  • A. Martínez-Rojas Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain
  • D. Lizcano Universidad a distancia de Madrid. Carretera de La Coruña, KM.38,500, vía de Servicio, no 15, 28400, Collado Villalba, Madrid. Spain
  • A Jiménez-Ramírez Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain

DOI:

https://doi.org/10.13052/jwe1540-9589.1929

Keywords:

Machine Learning, Automated Machine Learning, Knowledge Representation, Model-Driven Engineering

Abstract

Nowadays, Machine Learning (ML) algorithms are being widely applied in virtually all possible scenarios. However, developing a ML project entails the effort of many ML experts who have to select and configure the appropriate algorithm to process the data to learn from, between other things. Since there exist thousands of algorithms, it becomes a time-consuming and challenging task. To this end, recently, AutoML emerged to provide mechanisms to automate parts of this process. However, most of the efforts focus on applying brute force procedures to try different algorithms or configuration and select the one which gives better results. To make a smarter and more efficient selection, a repository of knowledge is necessary. To this end, this paper proposes (1) an approach towards a common language to consolidate the current distributed knowledge sources related the algorithm selection in ML, and (2) a method to join the knowledge gathered through this language in a unified store that can be exploited later on, and (3) a traceability links maintenance. The preliminary evaluations of this approach allow to create a unified store collecting the knowledge of 13 different sources and to identify a bunch of research lines to conduct.

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Author Biographies

J. G. Enríquez, Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain

J. G. Enríquez is Ph.D. in Computer Science at the University of Seville since 2017. He is a Lecturer with the Department of Computing Languages and Systems, University of Seville. He has been part of the organizing committee of different international conferences. He has collaborated with many universities in different countries such as: Southampton, Cuba or Berkeley among others. In 2015, he received the Innovation Award for its innovative activity in the field of research and development of the Platform for Dynamic Data Integration Andalusian Historical Heritage by Fujitsu Laboratories of Europe.

A. Martínez-Rojas, Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain

A. Martínez-Rojas is a senior computer engineering student at the University of Seville. He has a great interest in research, intends to pursue his doctoral studies. He already has several high impact publications. His main areas of interest are RPA and Machine Learning.

D. Lizcano, Universidad a distancia de Madrid. Carretera de La Coruña, KM.38,500, vía de Servicio, no 15, 28400, Collado Villalba, Madrid. Spain

D. Lizcano holds a Ph.D. in Computer Science from the UPM (2010), and a M.Sc. degree in Research in Complex Software Development (2008) also from UPM. He held a research grant from the European Social Fund under their Research Personnel Training program, the Extraordinary Graduation Prize for best academic record UPM and the National Accenture Prize for the Best Final-Year Computing Project. He is Professor and Senior Researcher at the Madrid Open University (UDIMA). He is currently involved in several national and European funded projects related to EUP, Web Engineering, Paradigms of Programming and HCI. He has published more than 25 papers in prestigious international journals and attended more than 70 international conferences.

A Jiménez-Ramírez, Computer Languages and Systems Department. Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n, 41012, Sevilla. Spain

A. Jiménez-Ramírez is lecturer and researcher at the University of Seville, Spain. In 2014 he obtained his Ph.D degree in Computer Science. His research focuses on intelligent techniques for Business Process Management and Flexible Business Processes, hereby combining different disciplines, among which Constraint Programming, Imperative and Declarative Business Process Modeling, and Planning and Scheduling. His current research interests are related to Decision Support Systems applied to Flexible Business Processes. Andrés has published his research at international journals and conferences like Data and Knowledge Engineering, Information and Software Technology, Journal of Web Engineering or CAiSE.

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Published

2020-06-03

How to Cite

Enríquez, J. G., Martínez-Rojas, A., Lizcano, D., & Jiménez-Ramírez, A. (2020). A Unified Model Representation of Machine Learning Knowledge. Journal of Web Engineering, 19(2), 319–340. https://doi.org/10.13052/jwe1540-9589.1929

Issue

Section

SPECIAL ISSUE: Advanced Practices in Web Engineering 2020