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pro vyhledávání: '"Tariq Abughofa"'
Autor:
Haruna Isah, Tariq Abughofa, Sazia Mahfuz, Dharmitha Ajerla, Farhana Zulkernine, Shahzad Khan
Publikováno v:
IEEE Access, Vol 7, Pp 154300-154316 (2019)
Big data processing systems are evolving to be more stream oriented where each data record is processed as it arrives by distributed and low-latency computational frameworks on a continuous basis. As the stream processing technology matures and more
Externí odkaz:
https://doaj.org/article/f75de772dee24fc3b26ed6181de192ae
Autor:
Farhana Zulkernine, Haruna Isah, Tariq Abughofa, Sazia Mahfuz, Shahzad Khan, Dharmitha Ajerla
Publikováno v:
IEEE Access, Vol 7, Pp 154300-154316 (2019)
Big data processing systems are evolving to be more stream oriented where each data record is processed as it arrives by distributed and low-latency computational frameworks on a continuous basis. As the stream processing technology matures and more
Autor:
Tariq Abughofa, Farhana Zulkernine
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319988115
DEXA (2)
DEXA (2)
Graph data is becoming dominant for many applications such as social networks, targeted advertising, and web indexing. As a result of that, advances in machine learning and data mining techniques depend tightly on the ability to process this data str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e81779fab6a0e7f44bcd16beac2e9a89
https://doi.org/10.1007/978-3-319-98812-2_28
https://doi.org/10.1007/978-3-319-98812-2_28
Autor:
Farhana Zulkernine, Tariq Abughofa
Publikováno v:
IEEE BigData
Graph processing is one of the most important topics in big data processing. The graph architecture is suitable for distributed processing as the processing works in an iterative manner allowing parallelism. Also, the structure has proved to be suita