caa a22 4500 605446806 CHVBK 20210128100129.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s11042-014-1970-x doi (NATIONALLICENCE)springer-10.1007/s11042-014-1970-x Nonnegative cross-media recoding of visual-auditory content for social media analysis [Elektronische Daten] [Hong Zhang, Xin Xu] Cross-media semantics understanding, which focuses on multimedia data of different modalities, is a rising hot topic in social media analysis. One of the most challenging issues for cross-media semantics understanding is how to represent multimedia data of different modalities. Most traditional multimedia semantics analysis works are based on single modality data sources, such as Flickr images or YouTube videos, leaving efficient cross-media data representation wide open. In this paper, we propose a novel nonnegative cross-media recoding approach, which learns co-occurrences of cross-media feature spaces by explicitly learning a common subset of basis vectors. Moreover, we impose the nonnegativity constraint on the decomposed matrices so that the basis vectors represent important and locally meaningful features of the cross-media data. We take two kinds of typical multimedia data, that is, image and audio, as experimental data. Our approach can be applied to a wide range of multimedia applications. The experiments are conducted on image-audio dataset for applications of cross-media retrieval and data clustering. Experiment results are encouraging and show that the performance of our approach is effective. Springer Science+Business Media New York, 2014 Cross-media nationallicence Subspace learning nationallicence Distance metric nationallicence Data clustering nationallicence Zhang Hong College of Computer Science & Technology, Wuhan University of Science & Technology, 430081, Wuhan, China aut Xu Xin College of Computer Science & Technology, Wuhan University of Science & Technology, 430081, Wuhan, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/2(2015-01-01), 577-593 1380-7501 74:2<577 2015 74 11042 https://doi.org/10.1007/s11042-014-1970-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-1970-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang Hong College of Computer Science & Technology, Wuhan University of Science & Technology, 430081, Wuhan, China aut NATIONALLICENCE 700 1- Xu Xin College of Computer Science & Technology, Wuhan University of Science & Technology, 430081, Wuhan, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/2(2015-01-01), 577-593 1380-7501 74:2<577 2015 74 11042