Detail of Publication
| Text Language | Japanese |
|---|---|
| Authors | Masashi Tada,Tomoyuki Muto,Masakazu Iwamura,Koichi Kise |
| Title | Extensions of Approximate Nearest Neighbor Search Based on a Multi-Valued Expression of Closeness to General Distributions |
| Journal | Proc. First Forum on Data Engineering and Information Management |
| Presentation number | F3-2 |
| Month & Year | February 2010 |
| Abstract | Approximate nearest neighbor search is a technique which greatly reduces processing time and required amount of memory for nearest neighbor search. We proposed two approximate nearest neighbor methods: MVH1 and MVH2. We comfirmed the effectiveness of these methods for uniform distribution with L1 norm. In this report, we get rid of the restrictions of these methods and propose efficient methods for Lp norm and general distributions. For L2 norm, improved MVH1 achived about 75% of processing time of LSH. Improved MVH2 achived about 50% of required amount of memory of LSH. |
- Following file is available.
- Entry for BibTeX
@InCollection{Tada2010, author = {Masashi Tada and Tomoyuki Muto and Masakazu Iwamura and Koichi Kise}, title = {Extensions of Approximate Nearest Neighbor Search Based on a Multi-Valued Expression of Closeness to General Distributions}, booktitle = {Proc. First Forum on Data Engineering and Information Management}, year = 2010, month = feb, presenID = {F3-2} }