Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Chandima Hewa Nadungodage"'
Publikováno v:
Knowledge and Information Systems. 51:821-850
Temporally uncertain data widely exist in many real-world applications. Temporal uncertainty can be caused by various reasons such as conflicting or missing event timestamps, network latency, granularity mismatch, synchronization problems, device pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::431a66b0780f6904758ca33ea4ba5ed2
https://doi.org/10.1007/s10115-016-0977-1
https://doi.org/10.1007/s10115-016-0977-1
Publikováno v:
BigData Conference
Recommendation systems are a popular marketing strategy for online service providers. These systems predict a customer's future preferences from the past behaviors of that customer and the other customers. Most of the popular online stores process mi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2d68b9cc35e2fd33c21c1457434d4c6
https://doi.org/10.1109/bigdata.2013.6691571
https://doi.org/10.1109/bigdata.2013.6691571
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783642201516
DASFAA (2)
DASFAA (2)
In this demo, we present the StreamFitter system for real-time linear regression analysis on continuous data streams. In order to perform regression on data streams, it is necessary to continuously update the regression model while receiving new data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c00e051e6efaafe2548f48cf99f8db8
https://doi.org/10.1007/978-3-642-20152-3_39
https://doi.org/10.1007/978-3-642-20152-3_39
Autor:
Yingzi Du, Jaehwan John Lee, Yuni Xia, Pranav Vaidya, Francis Bowen, Chandima Hewa Nadungodage
Publikováno v:
SIGMOD Conference
Numerous monitoring applications such as traffic control systems, border patrol monitoring, and person locater services generate a large number of multimedia data streams that need to be analyzed and processed using image processing and data stream m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e08afac1ce95ada66b41c8a4f5f8852
https://doi.org/10.1145/1807167.1807304
https://doi.org/10.1145/1807167.1807304
Publikováno v:
International Journal of Data Mining, Modelling and Management. 6:217
Stream data is generated continuously in a dynamic environment, with huge volume and fast changing behaviour. In order to perform regression on data streams, it is required to incrementally reconstruct the regression model as new stream data flows in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0116b18bc222f69037aeaa44a4610c30
https://doi.org/10.1504/ijdmmm.2014.065146
https://doi.org/10.1504/ijdmmm.2014.065146