Data repository of mobile applications for people with disabilities in the area of communication and language using data mining techniques

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Abstract

According to National Council of Disabilities (CONADIS) currently 425877 persons live in Ecuador with some form of disability. From this group, approximately 1.32% (5,621) people present language difficulties. However, although exist several technological developments, several Ecuadorian centers of special education/rehabilitation there is a lack of adequate support tools based on Information and Communication Technologies (ICT) and intelligent systems. This situation becomes more complicated in the area of speech-language therapy due this area was historically overlooked. For these reasons, in this paper we propose a system to generate a new repository of mobile applications for people with disabilities and language and communication disorders. To achieve this a process that allows mobile applications to automatically collect and through the natural language processing and vector space models generated a degree of belonging to issue search and generate the first mobile application repository will be generated. Our proposal relies on data mining techniques and allows educators as well therapists determining the best apps to support the intervention process of patients with disabilities. To this aim we have developed metrics to compare mobile apps from Google Play Store and IOS. Our proposal was validated with an analysis performed on 6700 mobile apps and the results are encouraging.

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Quisi-Peralta, D., Robles-Bykbaev, V., Saquicela-Galarza, V., Bernal-Merchan, E., Suquilanda-Cuesta, P., & Lopez-Nores, M. (2018). Data repository of mobile applications for people with disabilities in the area of communication and language using data mining techniques. In 2018 28th International Conference on Electronics, Communications and Computers, CONIELECOMP 2018 (Vol. 2018-January, pp. 225–231). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/CONIELECOMP.2018.8327203

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