Title: Searching by Similarity on a Very Large Scale
Lecturer: Giuseppe Amato, CNR Pisa
Period: end of September/beginning of October 2015
- Foundation of Metric Space Searching
- Distance Searching Problem
- Metric Distance Measures
- Similarity Queries
- Basic Partitioning Principles
- Principles of Similarity Query Execution
- Policies for avoiding Distance Computations
- Metric Space Transformations
- Priciples of Approximate Similarity Search
- Advanced issues: Statistics, Proximity, Performance Prediction, Tree quality measures
- Advanced issues: Choosing reference points
- Exact Similarity Search
- Vantage Point Trees
- AESA/LAESA
- GNAT
- The M-Tree Family
- The M-Tree
- Bulk-Loading Algorithm
- Multy-Way Insertion Algorithms
- The Slim Tree
- Slim-Down Algorithm
- Pivoting M-Tree
- Hash Based Methods
- D-Index
- Approximate Similarity Search with M-Tree
- Relative Error Approximation
- Good Fraction Approximation
- Small Chance Improvement Approximation
- Proximity-Based Approximation
- PAC Nearest Neighbor Searching
- Performance tests
- Other Approximate Similarity Search Methods
- Permutation Based Methods
- Permutation Spearman Rho
- PP-Index
- MI-File
- Locality Sensitive Hashing (LSH)
- LSH based on p-stable distributions
- LSH with Hamming Distance