Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Vania Bogorny"'
Autor:
Salman Haidri, Yaksh J. Haranwala, Vania Bogorny, Chiara Renso, Vinicius Prado da Fonseca, Amilcar Soares
Publikováno v:
SoftwareX, Vol 19, Iss , Pp 101176- (2022)
Trajectory data represents a trace of an object that changes its position in space over time. This kind of data is complex to handle and analyze, since it is generally produced in huge quantities, often prone to errors generated by the geolocation de
Externí odkaz:
https://doaj.org/article/11a74a22f6244d8bb6a0a3d75038fdcd
Publikováno v:
International Journal of Geographical Information Science. 36:1012-1036
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac95ea0f4b849db804f21980acd36be1
https://doi.org/10.1080/13658816.2021.2018593
https://doi.org/10.1080/13658816.2021.2018593
Autor:
Zaineb Chelly Dagdia, Vania Bogorny
Publikováno v:
Communication Papers of the 17th Conference on Computer Science and Intelligence Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73ad68c389310b743c2a384ed044efb2
https://doi.org/10.15439/2022f282
https://doi.org/10.15439/2022f282
Publikováno v:
MDM 2022-23rd IEEE International Conference on Mobile Data Management, pp. 282–285, Paphos, Cyprus, Online, 6-9/06/2022
2022 23rd IEEE International Conference on Mobile Data Management (MDM)
2022 23rd IEEE International Conference on Mobile Data Management (MDM)
ith the rapid increasing availability of information and popularization of mobility devices, trajectories have become more complex in their form. Trajectory data is now high dimensional, and often associated with heterogeneous sources of semantic dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c332fb951a557c4bc805a831ae8c117
https://doi.org/10.1109/mdm55031.2022.00060
https://doi.org/10.1109/mdm55031.2022.00060
Publikováno v:
2022 23rd IEEE International Conference on Mobile Data Management (MDM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58602e0959a23d022b4da9eb693e17ab
https://doi.org/10.1109/mdm55031.2022.00048
https://doi.org/10.1109/mdm55031.2022.00048
Autor:
Luis Otavio Alvares, Vania Bogorny, Willian Zalewski, Carlos Andres Ferrero, Lucas May Petry, Camila Leite da Silva
Publikováno v:
Data Mining and Knowledge Discovery. 34:652-680
In the last few years trajectory classification has been applied to many real problems, basically considering the dimensions of space and time or attributes inferred from these dimensions. However, with the explosion of social media data and the adva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d10892adaee539aff4856c0c8e85943
https://doi.org/10.1007/s10618-020-00676-x
https://doi.org/10.1007/s10618-020-00676-x
Autor:
Matheus Henrique Schaly, Rafael de Santiago, Vania Bogorny, Chiara Renso, Luis Otavio Alvares, Yuri Santa Rosa Nassar dos Santos, Raffaele Perego
Publikováno v:
BRACIS 2021-10th Brazilian Conference on Intelligent Systems, pp. 375–389, Online Conference, 29/11/2021-3/12/2021
Intelligent Systems ISBN: 9783030917012
info:cnr-pdr/source/autori:Santa Rosa Nassar dos Santos Y.; de Santiago R.; Perego R.; Schaly M.H.; Alvares L.O.; Renso C.; Bogorny V./congresso_nome:BRACIS 2021-10th Brazilian Conference on Intelligent Systems/congresso_luogo:Online Conference/congresso_data:29%2F11%2F2021-3%2F12%2F2021/anno:2021/pagina_da:375/pagina_a:389/intervallo_pagine:375–389
Intelligent Systems ISBN: 9783030917012
info:cnr-pdr/source/autori:Santa Rosa Nassar dos Santos Y.; de Santiago R.; Perego R.; Schaly M.H.; Alvares L.O.; Renso C.; Bogorny V./congresso_nome:BRACIS 2021-10th Brazilian Conference on Intelligent Systems/congresso_luogo:Online Conference/congresso_data:29%2F11%2F2021-3%2F12%2F2021/anno:2021/pagina_da:375/pagina_a:389/intervallo_pagine:375–389
Co-clustering is a specific type of clustering that addresses the problem of simultaneously clustering objects and attributes of a data matrix. Although general clustering techniques find non-overlapping co-clusters, finding possible overlaps between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba5bd6529b44c17dea084462fbdb8995
https://zenodo.org/record/5970008
https://zenodo.org/record/5970008
The semantic enrichment of mobility data with several information sources has led to a new type of movement data, the so-called multiple aspect trajectories. Comparing multiple aspect trajectories is crucial for several analysis tasks like querying,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::be3d11a4f1647834ae110086649eef65
https://zenodo.org/record/5902276
https://zenodo.org/record/5902276
Autor:
Salman Haidri, Yaksh J. Haranwala, Vania Bogorny, Chiara Renso, Vinicius Prado da Fonseca, Amilcar Soares
Trajectory data represent a trace of an object that changes its position in space over time. This kind of data is complex to handle and analyze, since it is generally produced in huge quantities, often prone to errors generated by the geolocation dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf98a4ac7c6d61fedac80eaf1a6d516c
http://arxiv.org/abs/2108.13202
http://arxiv.org/abs/2108.13202
Publikováno v:
International Journal of Geographical Information Science. 33:1847-1872
For many years trajectory similarity research has focused on raw trajectories, considering only space and time information. With the trajectory semantic enrichment, emerged the need for similarity ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05118a2d4756920501a0ab64a3df3f88
https://doi.org/10.1080/13658816.2019.1605074
https://doi.org/10.1080/13658816.2019.1605074