Pattern Search (Data Mining: Pattern Discovery)
summary
Discusses methods for discovering repeating patterns in datasets—such as frequent itemsets, substrings, subsequences, subgraphs, image elements, or video clips—by mining for all sufficiently frequent patterns and ranking them by occurrence. Gives concrete examples like extracting common user workflows from system logs and focuses on pattern discovery techniques used in data mining.
AI-written summary · about
chapters (14)
- 0:00Pattern definition
- 1:05Pattern applications
- 4:39Formal definition
- 7:11Pattern visualization
- 10:43Pattern enumeration issues
- 13:15Algorithm complexities
- 15:42FP-tree optimizations
- 17:48Closed and maximal patterns
- 20:19Recursion and modifications
- 23:08Pattern constraints
- 25:40Heuristics for data
- 29:21Long patterns
- 31:07Open-source tools
- 34:41Q&A
related talks
26mAnalytic Pattern Matching: From DNA to Twitter
45mBig Data — How to Mine Gold from Data
34mProcess mining from the inside
34mData Mining for Security Anomalies
19mCyclosa: Redundancy-Free Graph Pattern Mining via Set Dataflowi
55mSearching for Time Series Patterns at Big Data Scale
46mProcess Mining and big data: what service and library creators don't tell you
28mData Science Project Patterns that Work