Introduction
In our daily lives, the use of applications specifically designed to be run on mobile devices is becoming more and more frequent. While these applications provide useful services, there are many examples of scenarios where tadding semantic technologies could improve the quality of services and user experience. For example, in applications recommending means of transport, a reasoner could infer that a tram is a type of public transport and that a taxi is a type of private transport, so that the most appropriate option (according to the context of the user) can be selected.
On the one hand, the use of semantic information and semantic reasoning to infer new implicit knowledge poses sewveral challenges when the hardware is a mobile device, with limitations in terms of processing capacity, memory, battery and connectivity, among others. On the other hand, many real-world applications require imprecise knowledge management (for example, that a means of transport is very expensive or that its location is quite distant). The management of this type of knowledge on mobile devices is an open problem.
The objective of this project is to create an intelligent platform for semantic reasoning in mobile devices. This platform must adapt to the resources of the device, deciding at run time where to process the data, if on the mobile device itself, on an external server, or through a mixed approach, by adapting reasoning to the resources of the mobile device. This requires automatic learning techniques to predict the cost according to different criteria such as time or battery consumption. Furthermore, the platform must allow the management of imprecise knowledge associated with semantic information. This requires the efficient use of fuzzy logic techniques, making it possible to use them even under the limited resources of mobile devices.
Team members
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Fernando Bobillo (Main researcher) |
Eduardo Mena | Jorge Bernad | Jorge Gracia | Lacramioara Dranca | Carlos Bobed | Ignacio Huitzil |
Related publications
I. Huitzil, U. Straccia, C. Bobed, E. Mena, F. Bobillo. The Serializable and Incremental Semantic Reasoner fuzzyDL. Proceedings of the 29th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020). IEEE Press, Glasgow (United Kingdom), July 2020.
I. Huitzil, F. Alegre, F.Bobillo. GimmeHop: A Recommender System for Mobile Devices using Ontology Reasoners and Fuzzy Logic. Fuzzy Sets and Systems, 2020.- I. Huitzil, J. Bernad, F. Bobillo. Algorithms for Instance Retrieval and Realization in Fuzzy Ontologies. Mathematics 8(2), 154:1-16, 2020.
I. Huitzil, F. Bobillo, E. Mena, C. Bobed, J. Bermúdez. Evaluating some Heuristics to Find Hyponyms between Ontologies. ICEIS 2019 - Revised Selected Papers. Lecture Notes in Business Information Processing 378. Springer, 2020.- I. Huitzil, F. Bobillo, E. Mena, C. Bobed, J. Bermúdez. Some Reflections on the Discovery of Hyponyms between Ontologies. Proceedings of the 21st International Conference on Enterprise Information Systems (ICEIS 2019), Vol. 2, pp. 130-140, 2019.