Multimed Tools Appl https://doi.org/10.1007/s11042-018-6205-0 Extended Bayesian generalization model for understanding user’s intention in semantics based images retrieval 1 2,3 Meriem Korichi & MohamedLamineKherfi & 1 4 Mohamed Batouche & Khadra Bouanane Received: 4 September 2017 /Revised: 6 April 2018 /Accepted: 23 May 2018 Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Learning concepts from examples presented in user’s query and infer the other items that belong to this query is still a significant challenge for images retrieval systems. Existing models from cognitive science namely Bayesian models of generalization mainly focus on this challenge where they remarkably succeed at explaining how to generalize from few examples in a wide range of domains. However their success largely depends on the validity of examples. They require that each example is a good representative, which is not always the case in the context of images retrieval. In this paper, we will extend the Bayesian models of generalization to identify the appropriate level of generalization for a given query in the context of query by semantic example systems. Our model uses an ontology as the basis of its hypothesis space which allows us to take advantages of its semantic richness and inference
Multimedia Tools and Applications – Springer Journals
Published: Jun 4, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera