Estimating User Interest from Open-Domain Dialogue
Dialogue personalization is an important issue in the field of open-domain chat-oriented dialogue systems. If these systems could consider their users{'} interests, user engagement and satisfaction would be greatly improved. This paper proposes a neural network-based method for estimating users{'} interests from their utterances in chat dialogues to personalize dialogue systems{'} responses. We introduce a method for effectively extracting topics and user interests from utterances and also propose a pre-training approach that increases learning efficiency. Our experimental results indicate that the proposed model can estimate user{'}s interest more accurately than baseline approaches.
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Speech RecognitionSimilar Papers 제목 키워드 기반
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