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Social-aware visualized exploration of tourist behaviours

conference contribution
posted on 2023-05-23, 18:40 authored by Li, M, Bao, Z, Song, L, Duh, H
The popularity of social media has generated an abundance of publicly available data about tourist behaviour. We aim to exploit this to provide a snapshot of customized routes for pre-trip tourists and help the tourism industry understand the real behaviour of tourists for better policy making. Therefore, we propose an analytic framework that is able to automatically collect, clean and integrate all forms of tourists' activity data from various social media sites, and provides an interactive yet visualized analysis to facilitate users' exploration of underlying data. Specifically, it is able to (1) support multidimensional views of tourists' trajectory data, e.g. temporally, spatially, textually, etc; (2) support multi-granularity visualization where the trajectory of either a group of tourists or a single tourist can be efficiently retrieved.

History

Publication title

Proceedings

Editors

IEEE

Pagination

289-292

ISBN

978-1-4673-8796-5

Department/School

School of Information and Communication Technology

Publisher

Curran Associates Inc.

Place of publication

Red Hook, New York, United States

Event title

2016 International Conference on Big Data and Smart Computing (BigComp 2016)

Event Venue

Hong Kong, China

Date of Event (Start Date)

2016-01-18

Date of Event (End Date)

2016-01-20

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the information and computing sciences

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