CLASSY: A Conversational Aware Suggestion System†
1
DETI, Universidade de Aveiro, 3810-193 Aveiro, Portugal
2
Instituto de Telecomunicações, Universidade de Aveiro, 3810-193 Aveiro, Portugal
*
Author to whom correspondence should be addressed.
†
Presented at the 13th International Conference on Ubiquitous Computing and Ambient Intelligence UCAmI 2019, Toledo, Spain, 2–5 December 2019.
Proceedings 2019, 31(1), 40; https://doi.org/10.3390/proceedings2019031040
Published: 20 November 2019
(This article belongs to the Proceedings of 13th International Conference on Ubiquitous Computing and Ambient Intelligence UCAmI 2019)
Over the last few years, pervasive systems have seen some interesting development. Nevertheless, human–human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this work, we have developed a pervasive system – named CLASSY – that is aware of the conversational context and suggests documents potentially useful to the users based on an Information Retrieval system, and proposed a new scoring approach that uses semantics and distance based on proximity data in order to classify the relationship between tokens.
Keywords:
pervasive systems; context aware; suggestion systems; information retrieval; natural language processing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Ferreira, D.; Antunes, M.; Gomes, D.; Aguiar, R.L. CLASSY: A Conversational Aware Suggestion System. Proceedings 2019, 31, 40. https://doi.org/10.3390/proceedings2019031040
AMA Style
Ferreira D, Antunes M, Gomes D, Aguiar RL. CLASSY: A Conversational Aware Suggestion System. Proceedings. 2019; 31(1):40. https://doi.org/10.3390/proceedings2019031040
Chicago/Turabian StyleFerreira, Diogo; Antunes, Mário; Gomes, Diogo; Aguiar, Rui L. 2019. "CLASSY: A Conversational Aware Suggestion System" Proceedings 31, no. 1: 40. https://doi.org/10.3390/proceedings2019031040
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