HaMA

Author:

Saighi Asma1,Philippe Roose2,Ghoualmi Nassira1,Laborie Sébastien2,Laboudi Zakaria3

Affiliation:

1. Badji Mokhtar University, Department of Computer Science, LRS Laboratory, Annaba, Algeria

2. Liuppa, Univ Pau & Pays Adour, Anglet, France

3. University of Constantine 2, Department of Computer Science, MISC Laboratory, Constantine, Algeria

Abstract

Nowadays, multimedia documents are omnipresent at any time from and to any devices. However, mobile devices heterogeneity and the various contexts of the user require their adaptation. In this context, the existing systems transform contents to comply with the target constraints. Nevertheless, the current solutions do not exploit the profile semantic benefits to reason upon the context for assisting the adaptation. Furthermore, there is no work that care of adapting HTML pages containing CSS and changing in time, where time specification is declarative (e.g. by means of timesheets). This paper provides an adaptation approach called “Handicap-based Multimedia Adaptation” (HaMA), in which each context constraint corresponds to handicap types in order to discover adaptation services. Thus, a generic ontology is introduced to reason upon the context and then deduces the corresponding handicap in order to infer the suitable adaptation guideline. Also, we propose a method for selecting appropriate services with respect to quality criteria. To validate HaMA, scenarios were implemented.

Publisher

IGI Global

Reference43 articles.

1. A survey on ontology reasoners and comparison.;S.Abburu;International Journal of Computers and Applications,2012

2. A survey of multimedia content adaptation for mobile devices

3. Alti, A., Laborie, S., & Roose, P. (2013, June). Automatic Adaptation of Multimedia Documents. Proceedings of theInternational Symposium on Frontiers in Ambient and Mobile Systems (FAMS-2013) in conjunction with the 4th International Conference on Ambient Systems, Networks and Technologies (ANT). Elsevier.

4. Alti, A., Laborie, S., & Roose, P. (2014). Enrich the Expressiveness of Multimedia Document Adaptation Processes. In Semantic Multimedia Analysis and Processing (pp. 185-217).

5. A Community-Based Semantic Social Context-Aware Driven Adaptation for Multimedia Documents

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