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Optimizing visual data retrieval using deep learning driven CBIR for improved human machine interaction. [PDF]

Sci Rep
P A, R G.
europepmc   +1 more source

Construction and application of SARS-CoV-2 protein ontology (CoVPO). [PDF]

PLoS One
Nkhata A, Shi X, Zhang Y, Chen H.
europepmc   +1 more source

The Effects of Index Storage on Ranked Information Retrieval

, 2019
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Leveraging Dual Usability Methods to Evaluate Clinical Decision Support Among Patients With Traumatic Brain Injury: Mixed Methods Study.

JMIR Hum Factors
Rizvi RF, Faisal S, Sussman M, Mendlick P, Brown S, Lindemann E, Switzer S, Melton GB, Tignanelli CJ.   +8 more
europepmc   +1 more source

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Learning to Rank for Biomedical Information Retrieval

2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), 2021
With the continuous development of biomedical, the scale of data has also continued to increase, which makes it difficult for researchers to extract information manually. In order to satisfy the researcher's information requirement, information retrieval techniques for the biomedical field have been resolved.
Yonghu Yang, Yuying Peng
openaire   +2 more sources

Swarming to rank for information retrieval

Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, Swarm-Rank, which is well-founded in a Particle Swarm Optimization framework. SwarmRank learns a ranking function by optimizing the combination of various types of evidences such ...
Lars Schmidt-Thieme, Wolfgang Nejdl, Ernesto Diaz-Aviles   +2 more
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Learning to rank for information retrieval

Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2007
Learning to rank for Information Retrieval (IR) is a task to automatically construct a ranking model using training data, such that the model can sort new objects according to their degrees of relevance, preference, or importance. Many IR problems are by nature ranking problems, and many IR technologies can be potentially enhanced by using learning-to ...
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