DocumentCode
177437
Title
Wikipedia-based Kernels for dialogue topic tracking
Author
Seokhwan Kim ; Banchs, Rafael E. ; Haizhou Li
Author_Institution
Human Language Technol. Dept., Inst. for Infocomm Res., Singapore, Singapore
fYear
2014
fDate
4-9 May 2014
Firstpage
131
Lastpage
135
Abstract
Dialogue topic tracking aims to segment on-going dialogues into topically coherent sub-dialogues and predict the topic category for each next segment. This paper proposes a kernel method for dialogue topic tracking to utilize various types of information obtained from Wikipedia. The experimental results show that our proposed approach can significantly improve the performances of the task in mixed-initiative human-human dialogues.
Keywords
Web sites; interactive systems; pattern classification; Wikipedia-based kernels; dialogue topic tracking; kernel method; mixed-initiative human-human dialogues; topic category prediction; Electronic publishing; Encyclopedias; Internet; Kernel; Semantics; Vectors; Dialogue Topic Tracking; Kernel Methods; Spoken Dialogue Systems; Wikipedia;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6853572
Filename
6853572
Link To Document