Syntactic clustering of the Web
Selected papers from the sixth international conference on World Wide Web
Extendible hashing—a fast access method for dynamic files
ACM Transactions on Database Systems (TODS)
Similarity estimation techniques from rounding algorithms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
On the Resemblance and Containment of Documents
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Locality-sensitive hashing scheme based on p-stable distributions
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
LSH forest: self-tuning indexes for similarity search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Multi-probe LSH: efficient indexing for high-dimensional similarity search
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
CoPhIR Image Collection under the Microscope
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
Metric Index: An Efficient and Scalable Solution for Similarity Search
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
Building a web-scale image similarity search system
Multimedia Tools and Applications
Stabilizing the recall in similarity search
Proceedings of the Fourth International Conference on SImilarity Search and APplications
Large-scale similarity data management with distributed Metric Index
Information Processing and Management: an International Journal
Use of permutation prefixes for efficient and scalable approximate similarity search
Information Processing and Management: an International Journal
Efficiency and security in similarity cloud services
Proceedings of the VLDB Endowment
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The concept of Locality-sensitive Hashing (LSH) has been successfully used for searching in high-dimensional data and a number of locality-preserving hash functions have been introduced. In order to extend the applicability of the LSH approach to a general metric space, we focus on a recently presented Metric Index (M-Index), we redefine its hashing and searching process in the terms of LSH, and perform extensive measurements on two datasets to verify that the M-Index fulfills the conditions of the LSH concept. We widely discuss "optimal" properties of LSH functions and the efficiency of a given LSH function with respect to kNN queries. The results also indicate that the M-Index hashing and searching is more efficient than the tested standard LSH approach for Euclidean distance.