Cloud-Based Distributed Solution for Optimizing the Search for Tourist Destinations

The proposed system offers users the ability to efficiently search for information about various tourist destinations, accommodation options, and other relevant details. Users can explore a wide range of destinations, filter results according to their preferences, and access information about tourist attractions or destinations. Through the crawling process, the solution ensures broader search coverage and increased efficiency in data collection. The analysis and processing of this information enable the provisioning of accurate and up-to-date results for users. Additionally, it integrates an image search option that uses object recognition technologies and convolutional neural networks, allowing users to identify and obtain information about tourist attractions using photos. The novelty of the solution consists of the combination of different techniques, all while employing cloud services, in order to allow for an efficient management of tourism information facilitating the search process and enhancing the user experience in the tourism field.

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Publication Details

Published
2024-09-19
DOI
https://doi.org/10.1109/roedunet64292.2024.10722704
Citations
3
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
1.05
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article

Cloud-Based Distributed Solution for Optimizing the Search for Tourist Destinations

Adrian Alexandrescu, Dinu Țurcanu, Oana Agapie
3 citations
Data Management and Algorithms
1.05
article

Cloud-Based Distributed Solution for Optimizing the Search for Tourist Destinations

Adrian Alexandrescu, Dinu Țurcanu, Oana Agapie
article en
3 citations

Abstract

The proposed system offers users the ability to efficiently search for information about various tourist destinations, accommodation options, and other relevant details. Users can explore a wide range of destinations, filter results according to their preferences, and access information about tourist attractions or destinations. Through the crawling process, the solution ensures broader search coverage and increased efficiency in data collection. The analysis and processing of this information enable the provisioning of accurate and up-to-date results for users. Additionally, it integrates an image search option that uses object recognition technologies and convolutional neural networks, allowing users to identify and obtain information about tourist attractions using photos. The novelty of the solution consists of the combination of different techniques, all while employing cloud services, in order to allow for an efficient management of tourism information facilitating the search process and enhancing the user experience in the tourism field.

Technical University of Moldova (MD), Gheorghe Asachi Technical University of Iași (RO)
Openalex Percentile: Top 23%
Data Management and Algorithms
1.05
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