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The Proposed Context Matching Algorithm and Its Application for User Preferences of Tourism in COVID-19 Pandemic

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 471)


Currently, many applications of information search tourism are limited in the COVID-19 pandemic using a search engine. However, most application service online has not supported directly, matching end users with their preferences to find suitable tourist places. This paper has presented a proposed model using the Context Matching algorithm mostly based on the Smartphones; matching with user’s preferences and behaviors allows users to find tourism packages and regions. The experimental results show that the proposed model achieves significant improvements in matching user preferences for the domain under dynamic uncertainty. We posit that our novel approach holds the prospect of improvements in user preferences for tourism and weather in the COVID-19 Pandemic.


  • Service context
  • Context matching algorithm
  • The weather forecast
  • The help system

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This work was supported by the University of Economics Ho Chi Minh City (UEH), Vietnam under project CS-2021-51.

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Correspondence to Quoc Hung Nguyen .

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Pham, V.H., Nguyen, Q.H., Truong, V.P., Tran, L.P.T. (2023). The Proposed Context Matching Algorithm and Its Application for User Preferences of Tourism in COVID-19 Pandemic. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 471. Springer, Singapore.

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  • Print ISBN: 978-981-19-2534-4

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