Data stream management and mining
author:
Georges Hebrail,
Ecole Normale Superieure
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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| 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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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 "