FASELOD: A Faceted Search Engine in Linked Open Datasets Using Voice Recognition

Commonly, web applications incorporate interfaces that are limited to data capture through traditional methods such as keyboard, mouse or touch screens, which makes interaction with these interfaces complicated and unnatural for less experienced users. For its part, the LOD (Linked Open Data) cloud covers a large number of domains including the medical domain, the information stored in the datasets of this domain have great high quality information related to drugs, dis-eases, studies, clinics, orphan drugs, to mention a few. On the other hand, the re-search of the NLP (Natural Language Processing) has presented great advances in the generation of artificially intelligent behaviors. This document presents the development of a faceted search engine on datasets that are part of the LOD cloud that provides a more natural and intuitive navigation through NLP. Through the use of facets, the user is provided with a list of results on which he performs an incremental refinement by selecting values of the facets of the data that become constraints on the dataset. FASELOD provides a mechanism based on Silk that allows obtaining other related results within other datasets that are part of the LOD cloud.

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