Similarity search in metric spaces: New indexing techniques for similarity search in metric spaces
From International Center for Computational Logic
Similarity search in metric spaces: New indexing techniques for similarity search in metric spaces
Talk by Steffen Guhlemann
- Location: APB 3027
- Start: 10. December 2015 at 1:30 pm
- End: 10. December 2015 at 2:30 pm
- Event series: KBS Seminar
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A topic of growing importance in computer science is the handling of similarity in multiple heterogenous domains. Currently there is no common infrastructure to support this for the general metric space. The goal of this work is lay the foundation for such an infrastructure, which could be integrated into classical data base management systems.
After some analysis of the state of the art the M-Tree is identified as most suitable base and enhanced in multiple ways to the EM-Tree retaining structural compatibility. The query algorithms are optimized to reduce the number of necessary distance calculations. On the basis of a mathematical analysis of the relation between the tree structure and the query performance degrees of freedom in the tree edit algorithms are used to build trees optimized for answering similarity queries using a minimal number of distance calculations.
