Ivan edited this page Feb 5, 2016 · 3 revisions

dbADAM is a database system based on PostgreSQL that supports nearest neigbour retrieval for feature vector data. In addition, it comes with Vector Approximation-File to make querying more efficient.

Find more information on dbADAM in the following publications:

  • Ivan Giangreco, Ihab Al Kabary, and Heiko Schuldt (2014): ADAM — A Database and Information Retrieval System for Big Multimedia Collections. Proceedings of the 3rd IEEE International Congress on Big Data. Anchorage, USA. http://dx.doi.org/10.1109/BigData.Congress.2014.66

  • Ivan Giangreco, Ihab Al Kabary, and Heiko Schuldt (2014): ADAM — A System for Jointly Providing IR and Database Queries in Large-Scale Multimedia Retrieval. SIGIR '14: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval Proceedings. Gold Coast, Australia. http://doi.acm.org/10.1145/2600428.2611182

ADAM is being developed in the course of the iMotion project (http://imotion-project.eu) at the Databases and Information Systems Research Group (http://dbis.cs.unibas.ch) at the University of Basel, Switzerland.


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