Please use this identifier to cite or link to this item: https://doi.org/10.1145/3240508.3241399
Title: Knowledge-aware Multimodal Fashion Chatbot
Authors: Lizi Liao 
You Zhou
Yunshan Ma 
Richang Hong 
Tat-Seng Chua 
Issue Date: 26-Oct-2018
Publisher: Association for Computing Machinery, Inc
Citation: Lizi Liao, You Zhou, Yunshan Ma, Richang Hong, Tat-Seng Chua (2018-10-26). Knowledge-aware Multimodal Fashion Chatbot. ACM Multimedia Conference 2018 : 1265-1266. ScholarBank@NUS Repository. https://doi.org/10.1145/3240508.3241399
Abstract: Multimodal fashion chatbot provides a natural and informative way to fulfill customers' fashion needs. However, making it 'smart' in generating substantive responses remains a challenging problem. In this paper, we present a multimodal domain knowledge enriched fashion chatbot. It forms a taxonomy-based learning module to capture the fine-grained semantics in images and leverages an end-to-end neural conversational model to generate responses based on the conversation history, visual semantics, and domain knowledge. To avoid inconsistent dialogues, deep reinforcement learning method is used to further optimize the model. © 2018 Copyright held by the owner/author(s).
Source Title: ACM Multimedia Conference 2018
URI: https://scholarbank.nus.edu.sg/handle/10635/167280
ISBN: 9781450356657
DOI: 10.1145/3240508.3241399
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