A Co-occurrence Based Approach for Mining Overlapped Co-clusters in Binary Data

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

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

Evaluating the effect of compressing algorithms for trajectory similarity and classification problems

Autor: Antonios Makris, José Antônio Fernandes de Macêdo, Konstantinos Tserpes, Vania Bogorny, Luis Otavio Alvares, Camila Leite da Silva

Publikováno v: GeoInformatica

During the last few years the volumes of the data that synthesize trajectories have expanded to unparalleled quantities. This growth is challenging traditional trajectory analysis approaches and solutions are sought in other domains. In this work, we

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7efe2bf87155247f50b94892aac17337
https://zenodo.org/record/6338137

Exploring frequency-based approaches for efficient trajectory classification

Autor: Francisco Vicenzi, Camila Leite da Silva, Luis Otavio Alvares, Vania Bogorny, Lucas May Petry

Publikováno v: SAC

In the last few years, several trajectory classification methods have been proposed for mobility data collected from GPS devices. Most of them only use information derived from the physical movement of the object, as speed, acceleration, and directio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::214d508c3c4aced8632c257f8f43ab6a
https://doi.org/10.1145/3341105.3374045

Unveiling movement uncertainty for robust trajectory similarity analysis

Autor: Vania Bogorny, Nikos Pelekis, Luis Otavio Alvares, Andre Salvaro Furtado, Yannis Theodoridis

Publikováno v: International Journal of Geographical Information Science

Trajectory data analysis and mining require distance and similarity measures, and the quality of their results is directly related to those measures. Several similarity measures originally proposed for time-series were adapted to work with trajectory

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47a9f83724f0a7704f1d8462ff07bcc3
https://doi.org/10.1080/13658816.2017.1372763

Unusual behavior detection and object ranking from movement trajectories in target regions

Autor: Mateus Barragana, Vania Bogorny, Luis Otavio Alvares

Publikováno v: International Journal of Geographical Information Science. 31:364-386

Unusual behavior detection has been of interest in video analysis, transportation systems, movement trajectories, and so on. In movement trajectories, only a few works identify unusual behavior of objects around pre-defined points of interest POI, su

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::203289e27304d54b125c4570f9ff28ab
https://doi.org/10.1080/13658816.2016.1202415