'Similar pairs' presentation slideshows

Three Essential Techniques for Similar Documents

Three Essential Techniques for Similar Documents. Shingling : convert documents, emails, etc., to sets. Minhashing : convert large sets to short signatures, while preserving similarity. Locality-sensitive hashing : focus on pairs of signatures likely to be similar. Candidate pairs :

747 views • 74 slides

Low-Support, High-Correlation

444 views • 44 slides

Mid-Presentation Wei Li ENGN 2560 April 16,2013

Mid-Presentation Wei Li ENGN 2560 April 16,2013. Topic & Paper. Paper: Learning to Match Images in Large-Scale Collections. (Song Cao and Noah Snavely ) ECCV Workshop on Web-Scale Vision and Social Media , 2012 . http ://www.cs.cornell.edu/projects/matchlearn/. Problem Recall.

361 views • 25 slides

No Free Lunch: Brute Force vs Locality-Sensitive Hashing for Cross-Lingual Pairwise Similarity

No Free Lunch: Brute Force vs Locality-Sensitive Hashing for Cross-Lingual Pairwise Similarity. Ferhan Ture 1 Tamer Elsayed 2 Jimmy Lin 1,3. 1 Department of Computer Science, University of Maryland

235 views • 23 slides