Download Presentation and Final Ideas

UCLA, Winter 2017.
Ideas for Presentation and Final
• Review of Interesting DSMS---e.g., StreamBase, Spark
Streams: System Design and Language Design
• Sketches and other Synopses
• Different streams and complex events: e.g.,XML, text.
• Stream Mining Techniques not covered in class—e.g.
Outlier Detection, Regression, special applications
• Many other topics of on which you have special
interest: topic surveys in referenced books can be very
useful.
Success Stories
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Ariyam Das, Carlo Zaniolo: Fast Lossless Frequent Itemset Mining in Data Streams
using Crucial Patterns. SDM 2016: 576-584
Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniolo:Optimal sampling from sliding
windows. J. Comput. Syst. Sci. 78(1): 260-272 (2012)
Sumit Gouthaman: StreamsUDA Wrapper for Esper and Storm
A Study on Optimizing the Bit-Position Used for the Flajolet-Martin Probabilistic
Counting with Stochastic Averaging Algorithm
Joseph Korpela on Optimizing the Flajolet-Martin sketch:
[1] Flajolet, Philippe, and G. Nigel Martin. "Probabilistic counting algorithms for data base
applications." Journal of computer and system sciences 31.2 (1985): 182-209.
[2] Durand, Marianne, and Philippe Flajolet. "Loglog counting of large cardinalities."AlgorithmsESA 2003. Springer Berlin Heidelberg, 2003. 605-617.
[3] Flajolet, Philippe, et al. "HyperLogLog: the analysis of a near-optimal cardinality estimation
algorithm." DMTCS Proceedings 1 (2008).
[4] Heule, Stefan, Marc Nunkesser, and Alexander Hall. "HyperLogLog in Practice: Algorithmic
Engineering of a State of The Art Cardinality Estimation Algorithm." (2013).