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Crowd Knowledge Enhanced Multimodal Conversational Assistant in Travel Domain

  • Lizi LiaoEmail author
  • Lyndon Kennedy
  • Lynn Wilcox
  • Tat-Seng Chua
Conference paper
  • 1.1k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11961)

Abstract

We present a new solution towards building a crowd knowledge enhanced multimodal conversational system for travel. It aims to assist users in completing various travel-related tasks, such as searching for restaurants or things to do, in a multimodal conversation manner involving both text and images. In order to achieve this goal, we ground this research on the combination of multimodal understanding and recommendation techniques which explores the possibility of a more convenient information seeking paradigm. Specifically, we build the system in a modular manner where each modular construction is enriched with crowd knowledge from social sites. To the best of our knowledge, this is the first work that attempts to build intelligent multimodal conversational systems for travel, and moves an important step towards developing human-like assistants for completion of daily life tasks. Several current challenges are also pointed out as our future directions.

Keywords

Multimodal assistant Conversational systems Travel 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Lizi Liao
    • 1
    Email author
  • Lyndon Kennedy
    • 2
  • Lynn Wilcox
    • 2
  • Tat-Seng Chua
    • 1
  1. 1.NGSNational University of SingaporeSingaporeSingapore
  2. 2.FXPALPalo AltoUSA

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