Knowledge-aware multimodal fashion chatbot

Author

Lizi LIAO, Singapore Management UniversityFollow
You ZHOU
Yunshan MA
Richang HONG
Tat-Seng CHUA

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2018

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 endto-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.

Discipline

Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

MM '18: Proceedings of the 26th ACM international conference on Multimedia, Seoul, October 22-26

First Page

1265

Last Page

1266

ISBN

9781450356657

Identifier

10.1145/3240508.3241399

Publisher

ACM

City or Country

Seoul Republic of Korea

Citation

LIAO, Lizi; ZHOU, You; MA, Yunshan; HONG, Richang; and CHUA, Tat-Seng. Knowledge-aware multimodal fashion chatbot. (2018). MM '18: Proceedings of the 26th ACM international conference on Multimedia, Seoul, October 22-26. 1265-1266.
Available at: https://ink.library.smu.edu.sg/sis_research/7574

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

http://doi.org/10.1145/3240508.3241399