Jeribi, F.; Ahamed, S.R.; Perumal, U.; Alhameed, M.H.; Chari Kamsali, M. Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security. Sustainability2023, 15, 16276.
Jeribi, F.; Ahamed, S.R.; Perumal, U.; Alhameed, M.H.; Chari Kamsali, M. Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security. Sustainability 2023, 15, 16276.
Jeribi, F.; Ahamed, S.R.; Perumal, U.; Alhameed, M.H.; Chari Kamsali, M. Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security. Sustainability2023, 15, 16276.
Jeribi, F.; Ahamed, S.R.; Perumal, U.; Alhameed, M.H.; Chari Kamsali, M. Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security. Sustainability 2023, 15, 16276.
Abstract
Cultural Tourism (CT), which enhances the economic development of a region, aids a country in reinforcing its identities, enhancing cross-cultural understanding, and preserving the heritage culture of an area. Designing a proper tourism model assists the tourists in understanding the point of interest without the help of a local guide. However, owing to the need for the analysis of different factors, designing such a model is a complex process. Therefore, this article proposes a CT model for Riyadh for peak visitor time. Primarily, the map data and cultural event dataset are processed for location, such as grouping with Kriging Interpolation-based Chameleon (KIC), tree forming, and feature extraction. After that, the event dataset’s attributes are processed with word embedding. Meanwhile, the Social Network Sites (SNS) data like reviews and news are extracted with an external Application Programming Interface (API). The review data is processed with keyword extraction and word embedding, whereas the news data is processed with score value estimation. Lastly, the data are fused corresponding to a historical site and given to the Multi-Quadratic-Long Short Term Memory (MQ-LSTM) Recommendation System (RS); also, the recommended result with the map is stored in a database. Lastly, the database security is maintained with Locality Sensitive Hashing (LSH); moreover, by attaining higher performance values, the proposed model is experimentally verified.
Keywords
cultural tourism (CT); multi‐quadratic‐long short term memory (MQ‐LSTM); social network sites (SNS); tourism recommendation (TR); geographic information system (GIS); Kriging interpolation‐based Chameleon (KIC)
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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