I-SEE: Integrated stream execution environment over on-line data streams

Se Jung Shin, Hong Kyu Park, Ho Jin Woo, Won Suk Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The primary objective of various data stream applications is to monitor the on-going variations of data elements newly generated in data streams, so that appropriate services can be delivered to users timely. Basically, such monitoring activities can be divided into three categories: instant event monitoring, frequent behavior monitoring and analytic OLAP measures monitoring. Several prototype systems for data streams have been introduced but they are designated to support only the operations of one or two categories. However, many real-world data stream applications often require mixed operations of the three categories. This demonstration introduces an Integrated Stream Execution Environment (i-SEE) that can support the mixed execution of the operations of the three categories seamlessly, so that an i-SEE system can provide the multifaceted analytic results of on-line data streams continuously for various emerging applications.

Original languageEnglish
Title of host publicationCIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages1959-1960
Number of pages2
DOIs
Publication statusPublished - 2010 Dec 1
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: 2010 Oct 262010 Oct 30

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
CountryCanada
CityToronto, ON
Period10/10/2610/10/30

Fingerprint

Data streams
Integrated
Monitoring
Prototype
Online analytical processing

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Cite this

Shin, S. J., Park, H. K., Woo, H. J., & Lee, W. S. (2010). I-SEE: Integrated stream execution environment over on-line data streams. In CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops (pp. 1959-1960). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1871437.1871784
Shin, Se Jung ; Park, Hong Kyu ; Woo, Ho Jin ; Lee, Won Suk. / I-SEE : Integrated stream execution environment over on-line data streams. CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. pp. 1959-1960 (International Conference on Information and Knowledge Management, Proceedings).
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Shin, SJ, Park, HK, Woo, HJ & Lee, WS 2010, I-SEE: Integrated stream execution environment over on-line data streams. in CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. International Conference on Information and Knowledge Management, Proceedings, pp. 1959-1960, 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10, Toronto, ON, Canada, 10/10/26. https://doi.org/10.1145/1871437.1871784

I-SEE : Integrated stream execution environment over on-line data streams. / Shin, Se Jung; Park, Hong Kyu; Woo, Ho Jin; Lee, Won Suk.

CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. p. 1959-1960 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Shin SJ, Park HK, Woo HJ, Lee WS. I-SEE: Integrated stream execution environment over on-line data streams. In CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. p. 1959-1960. (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1871437.1871784