Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-030-37731-1_33
Title: Crowd Knowledge Enhanced Multimodal Conversational Assistant in Travel Domain
Authors: Lizi Liao 
Lyndon Kennedy
Lynn Wilcox
Tat-Seng Chua 
Keywords: Multimodal assistant
Conversational systems
Travel
Issue Date: 5-Jan-2020
Publisher: Springer
Citation: Lizi Liao, Lyndon Kennedy, Lynn Wilcox, Tat-Seng Chua (2020-01-05). Crowd Knowledge Enhanced Multimodal Conversational Assistant in Travel Domain. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11961 LNCS : 405 - 418. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-030-37731-1_33
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. © 2020, Springer Nature Switzerland AG.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: https://scholarbank.nus.edu.sg/handle/10635/178635
ISBN: 9783030000000
ISSN: 03029743
DOI: 10.1007/978-3-030-37731-1_33
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