A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia

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A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia
Title:
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia
Journal Title:
Annual Meeting of the Association for Computational Linguistics (ACL)
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Publication Date:
22 June 2014
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Abstract:
Dialog topic tracking aims at analyzing and maintaining topic transitions in ongoing dialogs. This paper proposes a composite kernel approach for dialog topic tracking to utilize various types of domain knowledge obtained from Wikipedia. Two kernels are defined based on history sequences and context trees constructed based on the extracted features. The experimental results show that our composite kernel approach can significantly improve the performances of topic tracking in mixed-initiative human-human dialogs.
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