Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/28693
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ferreira, Diogo | pt_PT |
dc.contributor.author | Antunes, Mário | pt_PT |
dc.contributor.author | Gomes, Diogo | pt_PT |
dc.contributor.author | Aguiar, Rui L. | pt_PT |
dc.date.accessioned | 2020-06-15T20:46:06Z | - |
dc.date.available | 2020-06-15T20:46:06Z | - |
dc.date.issued | 2019-11-20 | - |
dc.identifier.issn | 2504-3900 | - |
dc.identifier.uri | http://hdl.handle.net/10773/28693 | - |
dc.description.abstract | 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. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.publisher | MDPI | pt_PT |
dc.relation | UID/EEA/50008/2019 | pt_PT |
dc.rights | openAccess | pt_PT |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Pervasive systems | pt_PT |
dc.subject | Context aware | pt_PT |
dc.subject | Suggestion systems | pt_PT |
dc.subject | Information retrieval | pt_PT |
dc.subject | Natural language processing | pt_PT |
dc.title | CLASSY: a conversational aware suggestion system | pt_PT |
dc.type | article | pt_PT |
dc.description.version | published | pt_PT |
dc.peerreviewed | yes | pt_PT |
ua.event.date | 2-5 dezembro, 2019 | pt_PT |
degois.publication.issue | 1 | pt_PT |
degois.publication.title | Proceedings: 13th International Conference on Ubiquitous Computing and Ambient Intelligence UCAmI 2019 | pt_PT |
degois.publication.volume | 31 | pt_PT |
dc.identifier.doi | 10.3390/proceedings2019031040 | pt_PT |
Appears in Collections: | DETI - Artigos IT - Artigos |
Files in This Item:
File | Description | Size | Format | |
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proceedings-31-00040.pdf | 647.97 kB | Adobe PDF | View/Open |
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