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Neighborhood Graph and Tree for Indexing High-dimensional Data
NGT provides commands and a library for performing high-speed approximate nearest neighbor searches against a large volume of data (several million to several 10 million items of data) in high dimensional vector data space.
- Supported operating systems: Linux and macOS
- Object additional registration and removal are available.
- Objects beyond the memory size can be handled using the shared memory (memory mapped file) option.
- Supported distance functions: L1, L2, Cosine similarity, Angular, Hamming, and Jaccard
- Data Types: 4 byte floating point number and 1 byte unsigned integer (binary data)
- Supported languages: Python, Ruby, Go, C, and C++
- Distributed servers: ngtd and vald
- NGTQ can handle billions of objects.
- Python
- Ruby (Thanks Andrew!)
- Go
- C
- C++(sample code)
Copyright (C) 2015-2019 Yahoo Japan Corporation
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Yahoo Japan Corporation has acquired several patents on the technologies used in this software. However, the patent rights shall not be exercised under Apache License Version 2.0, only when the patented techniques are used with this software.
- Iwasaki, M., Miyazaki, D.: Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity. arXiv:1810.07355 [cs] (2018). (pdf)
- Iwasaki, M.: Pruned Bi-directed K-nearest Neighbor Graph for Proximity Search. Proc. of SISAP2016 (2016) 20-33. (pdf)
- Sugawara, K., Kobayashi, H. and Iwasaki, M.: On Approximately Searching for Similar Word Embeddings. Proc. of ACL2016 (2016) 2265-2275. (pdf)
- Iwasaki, M.: Applying a Graph-Structured Index to Product Image Search (in Japanese). IIEEJ Journal 42(5) (2013) 633-641. (pdf)
- Iwasaki, M.: Proximity search using approximate k nearest neighbor graph with a tree structured index (in Japanese). IPSJ Journal 52(2) (2011) 817-828. (pdf)
- Iwasaki, M.: Proximity search in metric spaces using approximate k nearest neighbor graph (in Japanese). IPSJ Trans. on Database 3(1) (2010) 18-28. (pdf)