Work

Knowledge-aware Multimodal Fashion Chatbot

Year: 2018

Type: conference-paper

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.

Source: ACM International Conference on Multimedia (ACM MM)

DOI: 10.1145/3240508.3241399

Authors: Lizi Liao, You Zhou, Yunshan Ma, Richang Hong, Tat-Seng Chua

Institutions: National University of Singapore, Hefei University of Technology

Language: English

Topic: Speech and dialogue systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Research Foundation Singapore

OpenAlex ID: W2895842584

FWCI: 1.008

Cites: 5

Cited by: 19

Related to: 10