The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
On Approximately Searching for Similar Word Embeddings
Open accessAbstract
We discuss an approximate similarity search for word embeddings, which is an operation to approximately find embeddings close to a given vector.We compared several metric-based search algorithms with hash-, tree-, and graphbased indexing from different aspects.Our experimental results showed that a graph-based indexing exhibits robust performance and additionally provided useful information, e.g., vector normalization achieves an efficient search with cosine similarity.
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“Sugawara, Kobayashi, and Iwasaki (2016) have shown that graph-based indexing has the best performance and precision for word representations.”
From A Method for the Calculation of Parallel Passages for Buddhist Chinese Sources Based on Million-scale Nearest Neighbor Search (2020) · cites this paper as Sugawara, Kobayashi, and Iwasaki (2016)
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Cites
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
Multidimensional binary search trees used for associative searching
Bentley, J. L. (1975) · Communications of the ACM · doi:10.1145/361002.361007 · Cited by 7,498
A unified architecture for natural language processing: deep neural networks with multitask learning
Collobert, R., & Weston, J. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390177 · Cited by 5,058
Scalable Recognition with a Vocabulary Tree
Nistér, D., & Stewénius, H. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.264 · Cited by 3,640
Locality-sensitive hashing scheme based on p-stable distributions
Datar, M., Immorlica, N., Indyk, P., & Mirrokni, V. (2004) · Annual Symposium on Computational Geometry (SoCG) · doi:10.1145/997817.997857 · Cited by 2,971
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Arya, S., Mount, D. M., Netanyahu, N. S., Silverman, R., & Wu, A. Y. (1998) · Journal of the ACM · doi:10.1145/293347.293348 · Cited by 2,347
Inverted files for text search engines
Zobel, J., & Moffat, A. (2006) · ACM Computing Surveys · doi:10.1145/1132956.1132959 · Cited by 1,084
Optimised KD-trees for fast image descriptor matching
Silpa-Anan, C., & Hartley, R. I. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587638 · Cited by 720
Fast Approximate Similarity Search in Extremely High-Dimensional Data Sets
Houle, M. E., & Sakuma, J. (2005) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2005.66 · Cited by 95
Scaling distributional similarity to large corpora
Gorman, J., & Curran, J. R. (2006) · International Conference on Computational Linguistics · doi:10.3115/1220175.1220221 · Cited by 53
Metric-based shape retrieval in large databases
Sebastian, T. B., & Kimia, B. B. (n.d.) · Object recognition supported by user interaction for service robots · doi:10.1109/icpr.2002.1047852
Research works printed but not linked: 8
- Ingwer Borg and Patrick J. F. Groenen. 2005. Modern Multidimensional Scaling. Springer Series in Statis- tics. Springer-Verlag New York.
- Aristides Gionis, Piotr Indyk, and Rajeev Motwani. 1999. Similarity Search in High Dimensions via Hashing. In Proceedings of the 25th International Conference on Very Large Data Bases (VLDB 2009), pages 518-529.
- Kiana Hajebi, Yasin Abbasi-Yadkori, Hossein Shah- bazi, and Hong Zhang. 2011. Fast Approximate Nearest-neighbor Search with K-nearest Neighbor Graph. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pages 1312-1317. AAAI Press.
- Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Cor- rado, and Jeff Dean. 2013a. Distributed Represen- tations of Words and Phrases and their Composition- ality. In Advances in Neural Information Processing Systems 26 (NIPS 2013), pages 3111-3119.
- Curran Associates, Inc. Tomas Mikolov, Wen tau Yih, and Geoffrey Zweig. 2013b. Linguistic Regularities in Continuous Space Word Representations. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2013), pages 746-751. Association for Computational Linguis- tics.
- Jeffrey Pennington, Richard Socher, and Christo- pher D. Manning. 2014b. GloVe: Global Vec- tors for Word Representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), pages 1532- 1543.
- Joseph Turian, Lev Ratinov, and Yoshua Bengio. 2010. CCG: RTE Annotation Data for ACL 2010 publica- tion. http://cogcomp.cs.illinois.edu/ Data/ACL2010_NER_Experiments.php.
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Cited by
Nehrdich, S. (2020) · Journal of the Japanese Association for Digital Humanities · doi:10.17928/jjadh.5.2_132 · Cited by 3
“Sugawara, Kobayashi, and Iwasaki (2016) have shown that graph-based indexing has the best performance and precision for word representations.”
Background
Metadata
- Authors
- Sugawara, K., Kobayashi, H., & Iwasaki, M.
- Affiliations
- Yahoo Japan Corp. (Japan) (JP)
- Venue
- Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2016
- Pages
- 2265-2275
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W2511469006
- Cited by
- 28
- References
- 12
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 4 · 2022: 1 · 2021: 5 · 2020: 2 · 2019: 7 · 2018: 3 · 2017: 2 · 2016: 1
- FWCI
- 1.50
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Keywords
- word embeddings, approximate nearest neighbor search, similarity search, hash-based indexing, tree-based indexing, graph-based indexing, cosine similarity, vector normalization
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