J-EDA: A workbench for tuning similarity and diversity search parameters in content-based image retrieval.
João V. O. NovaesLúcio F. D. SantosLuiz Olmes CarvalhoDaniel de OliveiraMarcos V. N. BedoAgma J. M. TrainaCaetano Traina Jr.Published in: J. Inf. Data Manag. (2021)
Keyphrases
- fine tuning
- multimedia
- maximum likelihood
- search strategy
- parameter settings
- parameter tuning
- similarity measure
- search algorithm
- web content
- search efficiency
- metadata
- fine tune
- similarity matching
- multimedia content
- search result diversification
- low level image features
- search interface
- solution space
- semantic similarity
- user queries
- image retrieval