Location: Conferences » Other » NATO Advanced Study Institute on Mining Massive Data Sets for Security

Data stream management and mining

author:Georges Hebrail, Ecole Normale Superieure
published: Nov. 26, 2007,   recorded: September 2007,   views: 568
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Slides

Slides
0:00 Data stream management and mining
0:55 Outline
2:43 What is a data stream ? (1)
6:03 What is a data stream ? (2)
7:08 Outline - Applications of data stream processing
7:33 Applications of data stream processing - Data stream processing
10:24 Applications of data stream processing - Applications
15:26 Applications of data stream processing - Standard data processing versus data stream processing
17:27 Applications of data stream processing - Let’s go deeper into some examples
17:44 Applications of data stream processing - Network management (1)
18:55 Applications of data stream processing - Network management (2)
21:13 Applications of data stream processing - Stock monitoring
24:10 Applications of data stream processing - Linear Road Benchmark (1)
24:59 Applications of data stream processing - Linear Road Benchmark (2)
25:23 Applications of data stream processing - Linear Road Benchmark (1)
26:39 Applications of data stream processing - Linear Road Benchmark (2)
26:53 Applications of data stream processing - Linear Road Benchmark (3)
28:23 Applications of data stream processing - Linear Road Benchmark (2)
29:20 Applications of data stream processing - Linear Road Benchmark (3)
29:43 Applications of data stream processing - Where is the problem ?
35:01 Outline - Models for data streams
35:24 Models for data streams - Structure of a stream (1)
36:36 Models for data streams - Structure of a stream (2)
37:11 Models for data streams - Model of a stream
38:04 Models for data streams - Contents of a stream
39:05 Models for data streams - Modeling the stream
40:24 Models for data streams - Some canonical models of streams
41:02 Models for data streams - Examples:
42:17 Models for data streams - Windowing (1)
43:48 Models for data streams - Windowing (2)
45:02 Models for data streams - Sliding window
45:38 Outline - Data stream management systems
45:56 DSMS outline - Definition of a DSMS
46:23 DSMS: definition
49:37 DSMS outline - DSMS data model
49:43 DSMS: data model (1)
50:36 DSMS: data model (2)
54:44 DSMS outline - Queries in a DSMS
54:45 DSMS: queries (1)
57:27 DSMS: queries (2)
57:49 DSMS: queries (3)
58:32 DSMS: queries (4)
60:06 DSMS: queries (5)
61:27 DSMS: queries (6)
61:49 DSMS outline - STREAM example with «Linear Road»
61:59 DSMS: STREAM (1)
63:19 DSMS: STREAM (2)
63:21 DSMS: STREAM (3)
63:23 DSMS: STREAM (4)
63:40 DSMS outline - Main architecture of DSMS
64:03 Main architecture of DSMS (1)
64:05 DSMS outline - Approximate answers to queries
64:15 Approximate answers to queries (1)
64:18 DSMS outline - Main existing DSMS
64:24 Main existing DSMS (1)
64:54 Main existing DSMS (2)
67:03 Main existing DSMS (3)
68:43 Outline - Data stream mining
69:24 Data stream mining: outline - Definition
69:47 Data stream mining: definition (1)
70:11 Data stream mining: definition (2)
71:14 Data stream mining: definition (3)
72:39 Data stream mining: definition (4)
74:15 Data stream mining: outline - Decision tree
74:17 Data stream mining: decision tree (1)
75:34 Data stream mining: decision tree (2)
76:53 Data stream mining: decision tree (3)
78:35 Data stream mining: outline - PCA
78:54 Data stream mining: additive methods (1)
80:41 Data stream mining: additive methods (2)
81:55 Data stream mining: outline - Clustering
81:57 Data stream mining: clustering (1)
85:22 Data stream mining: clustering (2)
87:13 Data stream mining: clustering (3)
89:32 Data stream mining: clustering (4)
91:37 Data stream mining: clustering (5)
93:22 Data stream mining: clustering (6)
94:25 Data stream mining: clustering (7)
94:49 Data stream mining: clustering (8)
95:59 Outline - Synopses structures
96:50 Synopses structures
99:57 Synopses structures: random samples
103:21 Synopses structures
104:06 Synopses structures: sketches (1)
106:09 Synopses structures: sketches (2)
108:23 Synopses structures: sketches (3)
109:15 Synopses structures: sketches (4)
110:45 Synopses structures: sketches (5)
112:47 Synopses structures: sketches (6)
115:58 Synopses structures: sketches (7)
117:30 Synopses structures: sketches (8)
118:55 Outline - Conclusion
118:59 Conclusion
123:38 References: general
123:45 References: DSMS
123:47 References: data stream mining
123:54 QUESTIONS ?

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Description

The course provides an introduction to the data stream management and mining field. The following points are treated: (1) applications which motivated these new developments (telecommunications, computer networks, stock market, security, ...), (2) new concepts related to data streams (structure of a stream, timestamps, time windows, ...), (3) main features of data stream management systems, (4) adaptations of data mining algorithms to the case of streams, (5) solutions to summarize data streams.

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Reviews and comments:

Comment1 Reza Maghsoudlou from Iran, May 21, 2008 at 10:31 a.m.:

hi
i'm a student of master in IT and have a final project
my project subject is "Data Stream & Continuos Query" and like use your lectures for completing my project
please help me and give some paper that i can read them and be know about data stream more
thank u very much
my email is "maghsoodloo_reza@yahoo.com "

Comment2 Onur, November 11, 2008 at 2:59 p.m.:

Video is not working for me, using xp with IE6. I tried both flash and WM

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