2012 ©
             Publication
Journal Publication
Research Title Entropy-based information fusion for multimodal data 
Date of Distribution 30 July 2014 
Conference
     Title of the Conference 2014 International Conference of Computer Science and Engineering Conference (ICSEC) 
     Organiser Department of Computer Science, Faculty of Science, Khon Kean University, Thailand 
     Conference Place Hotel Pullman 
     Province/State Khon Kaen 
     Conference Date 30 July 2014 
     To 1 August 2014 
Proceeding Paper
     Volume
     Issue
     Page 296-301 
     Editors/edition/publisher IEEE 
     Abstract Multimodal data contains a great amount of data in the Internet which hold rich-media content. The fusion of data information is a way to explore the linkage between the Web data in order to integrate the data from heterogeneous sources so that deep information can be extracted. Nowadays Web data are either structured or unstructured and information can be generated from the Web data by supervised or unsupervised methods. The existing methods rely on features generated from histogram data like HMM or pre-defined rules. However, data change in-deterministically at most of time and are hard to pre-define all the states and rules in advance. This paper takes the approach of entropy-based information fusion to treat the information from each source as a stochastic process so that the change of each process can be measured in real time. Then the change of information from each source is integrated and entropy is introduced to measure how far the integrated information of the change is from the best scenario based on histogram data. In such a way, it is possible to deduce an overall inference from data from difference sources in different presentations. Then the inference can be generated automatically with human interference. 
Author
567020043-0 Mrs. PING LIANG [Main Author]
Science Doctoral Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Full paper 
Type of Presentation Oral 
Part of thesis true 
Presentation awarding false 
Attach file
Citation 0