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|Year=2015
 
|Year=2015
 
|Month=April
 
|Month=April
|Booktitle=Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29 - April 2, 2015. Proceedings
+
|Booktitle=Advances in Information Retrieval: 37th European Conference on IR Research (ECIR), Vienna, Austria.
 
|Publisher=Springer International Publishing
 
|Publisher=Springer International Publishing
 
|Address=Cham, Germany
 
|Address=Cham, Germany

Version vom 5. März 2016, 11:44 Uhr


Multi-Modal Correlated Centroid Space for Multi-Lingual Cross-Modal Retrieval


Multi-Modal Correlated Centroid Space for Multi-Lingual Cross-Modal Retrieval



Published: 2015 April
Herausgeber: Hanbury, Allan and Kazai, Gabriella and Rauber, Andreas and Fuhr, Norbert
Buchtitel: Advances in Information Retrieval: 37th European Conference on IR Research (ECIR), Vienna, Austria.
Verlag: Springer International Publishing
Erscheinungsort: Cham, Germany

Referierte Veröffentlichung

BibTeX

Kurzfassung
We present a novel cross-modal retrieval approach where the textual modality is present in different languages. We retrieve semantically similar documents across modalities in different languages using a correlated centroid space unsupervised retrieval (C2SUR) approach. C2SUR consists of two phases. In the first phase, we extract heterogeneous features from a multi-modal document and project it to a correlated space using kernel canonical correlation analysis (KCCA). In the second phase, correlated space centroids are obtained using clustering to retrieve cross-modal documents with different similarity measures. Experimental results show that C2SUR outperforms the existing state-of-the-art English cross-modal retrieval approaches and achieve similar results for other languages.

Weitere Informationen unter: Link
DOI Link: 10.1007/978-3-319-16354-3_9

Projekt

XLiMe



Forschungsgruppe

Web Science und Wissensmanagement


Forschungsgebiet

Maschinelles Lernen, Multimedia Annotation & Retrieval