Detection of Interaction-based Knowledge for Reclassification of Service Robots: Big Data Analytics Perspective

Date
2023-01-03
Authors
Lyu, Fang
Wang, Ming
Choi, Jaewon
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
1591
Ending Page
Alternative Title
Abstract
With the advancement of artificial intelligence technology, the robot industry in human- robot interactive service has rapidly developed. The purpose of this paper is to uncover user acceptance of human-robot interactive service robots based on online reviews. Extract reviews the public service robots and the domestic service robots from YouTube uses word2vec, sentiment classification, and LDA (Latent Dirichlet Allocation) analysis methods for research. The results show that in the interactive technology, the public service robots, the domestic service robots, and the service robots can well receive the user’s speech, gestures, and understanding of emotional states and navigating with and around. However, collaborating with humans, users may be more fearful and worried. At the same time, the positive topic of the public service robots is experience value, and the negative topic is system quality. The positive topic of the domestic service robots is anthropomorphism, and the negative topic is perceived intelligence.
Description
Keywords
Technology and Analytics in Emerging Markets (TAEM), human–robot interactive, latent dirichlet allocation., sentiment classification, service robot, word2vec
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 56th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.