Zobrazeno 1 - 10
of 90
pro vyhledávání: '"DSC - Data Science"'
0-Shot System - The simple exact matching performs the best - The quality of concepts selected to represent an event is more important than quantity - It's an open problem of how to harness the ontology-based mapping MER System - In key evidence loca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dris___00893::8fd7f333c6d09900e1168dc6dd71d833
http://resolver.tudelft.nl/uuid:f74ac94e-7da4-44f5-aea1-cea503a3ecc2
http://resolver.tudelft.nl/uuid:f74ac94e-7da4-44f5-aea1-cea503a3ecc2
Publikováno v:
2014 TREC Video Retrieval Evaluation, TRECVID 2014, 2014 TREC Video Retrieval Evaluation, TRECVID 2014, 10 November 2014 through 12 November 2014
0-Shot System - The simple exact matching performs the best - The quality of concepts selected to represent an event is more important than quantity - It's an open problem of how to harness the ontology-based mapping MER System - In key evidence loca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8fd9b40310a3c887cae7f8bcb432666e
http://resolver.tudelft.nl/uuid:f74ac94e-7da4-44f5-aea1-cea503a3ecc2
http://resolver.tudelft.nl/uuid:f74ac94e-7da4-44f5-aea1-cea503a3ecc2
Publikováno v:
Journal of the Association for Information Science and Technology, 68, 4, pp. 895-910
Journal of the Association for Information Science and Technology
Journal of the Association for Information Science and Technology, 68, 895-910
Journal of the Association for Information Science and Technology
Journal of the Association for Information Science and Technology, 68, 895-910
In this article we evaluate context-aware recommendation systems for information re-finding by knowledge workers. We identify 4 criteria that are relevant for evaluating the quality of knowledge worker support: context relevance, document relevance,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e154905c49c355349e1a1aaeb180348
https://hdl.handle.net/2066/162330
https://hdl.handle.net/2066/162330
Publikováno v:
Information Sciences, 358–359, September, pp. 1-17
Information Sciences, 358-359, 1-17
Information Sciences, 358–359, 1-17
Information Sciences, 358-359, 1-17
Information Sciences, 358–359, 1-17
In this paper, we analyze corporate e-mail messages as a medium to convey work tasks. Research indicates that categorization of e-mail could alleviate the common problem of information overload. Although e-mail clients provide possibilities of e-mail
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23649ac8d6ac22dc7b15f4d690756c1a
https://doi.org/10.1016/j.ins.2016.03.002
https://doi.org/10.1016/j.ins.2016.03.002
Publikováno v:
JMIR mHealth and uHealth, 6(3), e72
JMIR mHealth and uHealth, Vol 6, Iss 3, p e72 (2018)
JMIR mHealth and uHealth
JMIR mHealth and uHealth, 6(3)
JMIR Mhealth Uhealth, 3, 6, e72
JMIR mHealth and uHealth, Vol 6, Iss 3, p e72 (2018)
JMIR mHealth and uHealth
JMIR mHealth and uHealth, 6(3)
JMIR Mhealth Uhealth, 3, 6, e72
BackgroundTo improve workers’ health and well-being, workplace interventions have been developed, but utilization and reach are unsatisfactory, and effects are small. In recent years, new approaches such as mobile health (mHealth) apps are being de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::194d6a65b84225e35c81fb9fb8152535
http://hdl.handle.net/1887/70385
http://hdl.handle.net/1887/70385
Publikováno v:
IEEE Transactions on Affective Computing, 9, 2, pp. 227-239
IEEE Transactions on Affective Computing, 9, 227-239
IEEE Transactions on Affective Computing, 2, 9, 227-239
IEEE Transactions on Affective Computing, 9(2)
IEEE Transactions on Affective Computing, Electronic preprint, 1-27
IEEE Transactions on Affective Computing, 9, 227-239
IEEE Transactions on Affective Computing, 2, 9, 227-239
IEEE Transactions on Affective Computing, 9(2)
IEEE Transactions on Affective Computing, Electronic preprint, 1-27
Employees often report the experience of stress at work. In the SWELL project we investigate how new context aware pervasive systems can support knowledge workers to diminish stress. The focus of this paper is on developing automatic classifiers to i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::258247f140670443c5d79bda2125751d
http://resolver.tudelft.nl/uuid:c1ceb001-56d5-4a98-b6e8-69d136fbc2d5
http://resolver.tudelft.nl/uuid:c1ceb001-56d5-4a98-b6e8-69d136fbc2d5
Background: To improve workers’ health and well-being, workplace interventions have been developed, but utilization and reach are unsatisfactory, and effects are small. In recent years, new approaches such as mobile health (mHealth) apps are being
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dris___00893::2bda8d4bcb4591c36e8c4840ac6f9a8a
http://resolver.tudelft.nl/uuid:c5c7d19b-6f47-425b-8f11-1016d9c37c07
http://resolver.tudelft.nl/uuid:c5c7d19b-6f47-425b-8f11-1016d9c37c07
Publikováno v:
IEEE BigData
2017 IEEE International Conference on Big Data (BIGDATA)
2017 IEEE International Conference on Big Data (BIGDATA)
Big Data Applications (BDAs) are used to support a decision making process, but their developers and users are often unaware of the exact uncertainties that underlie the output of BDAs. In this paper we present a System for Uncertainty Decision Suppo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d808790cac0559d71a3abea77e197e38
https://doi.org/10.1109/bigdata.2017.8258246
https://doi.org/10.1109/bigdata.2017.8258246
Publikováno v:
International Journal of Multimedia Information Retrieval, 1, 1-29
International Journal of Multimedia Information Retrieval, 6(1), 1-29
International Journal of Multimedia Information Retrieval
International Journal of Multimedia Information Retrieval, 6(1), 1-29
International Journal of Multimedia Information Retrieval
This paper presents an overview of the Video Instance Search benchmark which was run over a period of 6 years (2010–2015) as part of the TREC Video Retrieval (TRECVID) workshop series. The main contributions of the paper include i) an examination o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b6a588384f17b4ebb136ddb43c748b1
https://hdl.handle.net/1887/69174
https://hdl.handle.net/1887/69174
Big Data Applications (BDAs) are used to support a decision making process, but their developers and users are often unaware of the exact uncertainties that underlie the output of BDAs. In this paper we present a System for Uncertainty Decision Suppo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dris___00893::4093a8db5b8f24eed305b086b6116253
http://resolver.tudelft.nl/uuid:98676665-d8c0-4c69-bb4d-b75bafbd09da
http://resolver.tudelft.nl/uuid:98676665-d8c0-4c69-bb4d-b75bafbd09da