Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Masoomeh Zameni"'
Autor:
Masoomeh Zameni, Amin Sadri, Kotagiri Ramamohanarao, Christopher Leckie, Zahra Ghafoori, Masud Moshtaghi, Flora D. Salim
Publikováno v:
Knowledge and Information Systems. 62:719-750
A critical problem in time series analysis is change point detection, which identifies the times when the underlying distribution of a time series abruptly changes. However, several shortcomings limit the use of some existing techniques in real-world
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81d0dd2ecf7550de334ba3af54c16b2b
https://doi.org/10.1007/s10115-019-01366-x
https://doi.org/10.1007/s10115-019-01366-x
Publikováno v:
Information Systems. 69:180-193
The ever increasing size of graphs makes them difficult to query and store. In this paper, we present Shrink, a compression method that reduces the size of the graph while preserving the distances between the nodes. The compression is based on the it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d073cac2aba3e25f5c4e7b40b0785cd
https://doi.org/10.1016/j.is.2017.06.001
https://doi.org/10.1016/j.is.2017.06.001
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783030185893
DASFAA (3)
DASFAA (3)
An important task in analysing high-dimensional time series data generated from sensors in the Internet of Things (IoT) platform is to detect changes in the statistical properties of the time series. Accurate, efficient and near real-time detection o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ce40e4008d691d5c61cf6f46f83782c
https://doi.org/10.1007/978-3-030-18590-9_78
https://doi.org/10.1007/978-3-030-18590-9_78
Autor:
Christopher Leckie, Kotagiri Ramamohanarao, Mengyi He, Masud Moshtaghi, James C. Bezdek, Zahra Ghafoori, Masoomeh Zameni
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967
ECML/PKDD (3)
ECML/PKDD (3)
Sensors deployed in different parts of a city continuously record traffic data, such as vehicle flows and pedestrian counts. We define an unexpected change in the traffic counts as an anomalous local event. Reliable discovery of such events is very i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c5472faa97d3c2269813fe2e03a58a1
https://doi.org/10.1007/978-3-030-10997-4_34
https://doi.org/10.1007/978-3-030-10997-4_34
Publikováno v:
PerCom Workshops
Road traffic data analysis has become a major focus of data mining research due to the key role it plays in optimizing road network performance. A major challenge for query processing on road traffic data is the time and memory required due to the la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2a8539a38f86d087120aad55c6d8af9
https://doi.org/10.1109/percomw.2016.7457090
https://doi.org/10.1109/percomw.2016.7457090
Publikováno v:
International Journal of Digital Content Technology and its Applications. 4:118-125
Recently, mining information in sports video data, especially soccer video, has become an active research topic. In this paper, a new algorithm for detection of expected goal events in soccer video is proposed. The proposed algorithm is composed of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::932c11386991292d920d656edd45e9db
https://doi.org/10.4156/jdcta.vol4.issue8.13
https://doi.org/10.4156/jdcta.vol4.issue8.13