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Full-Text Articles in Physical Sciences and Mathematics
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …
Online Multimodal Co-Indexing And Retrieval Of Weakly Labeled Web Image Collections, Lei Meng, Ah-Hwee Tan, Cyril Leung, Liqiang Nie, Tan-Seng Chua, Chunyan Miao
Online Multimodal Co-Indexing And Retrieval Of Weakly Labeled Web Image Collections, Lei Meng, Ah-Hwee Tan, Cyril Leung, Liqiang Nie, Tan-Seng Chua, Chunyan Miao
Research Collection School Of Computing and Information Systems
Weak supervisory information of web images, such as captions, tags, and descriptions, make it possible to better understand images at the semantic level. In this paper, we propose a novel online multimodal co-indexing algorithm based on Adaptive Resonance Theory, named OMC-ART, for the automatic co-indexing and retrieval of images using their multimodal information. Compared with existing studies, OMC-ART has several distinct characteristics. First, OMCART is able to perform online learning of sequential data. Second, OMC-ART builds a two-layer indexing structure, in which the first layer co-indexes the images by the key visual and textual features based on the generalized distributions …