DBScholar

Back to papers

Query-Sensitive Embeddings

Summary: Embedding-based approximate NN for costly similarity; maps objects to a vector space to speed retrieval. Novel query-sensitive distance metric learned with the embedding adapts to the query, boosting accuracy; tested on handwritten digits and time-series, outperforming prior embeddings. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hb405e664bf110bb7
Venue
SIGMOD
Year
2005
Pagerank
5.9276742e-05
Overall Rank
5,982 | 59.79%
DOI
10.1145/1066157.1066238

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{athitsos_sigmod05,
        title = {{Query-Sensitive Embeddings}},
        author = {Athitsos, Vassilis and Hadjieleftheriou, Marios and Kollios, George and Sclaroff, Stan},
        series = {{SIGMOD} '05},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1066157.1066238},
        url = {https://dl.acm.org/doi/10.1145/1066157.1066238},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
2,505 DSH: Data Sensitive Hashing for High-Dimensional k-NN Search 2014 SIGMOD 8.3779738e-05
3,507 Approximate Embedding-Based Subsequence Matching of Time Series 2008 SIGMOD 7.2494536e-05
4,856 Neighbor-Sensitive Hashing 2016 VLDB 6.3798143e-05
6,312 Putting Context into Schema Matching 2006 VLDB 5.8171904e-05
6,736 Information Preserving XML Schema Embedding 2005 VLDB 5.6928321e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers