Hybrid machine learning model for a next-generation ecofriendly travelling and guides to reduce carbon emissions

Elias Hossain, Wahidur Rahman, Alif B. Ekram, Redwan Abedin, Nasim Ahmed Roni, Erfanul Haque, S. M. Asaduzzaman, Md. Shazzad Hossain, Shah Sufi Nesar Uddin Siddiqui, Shamsul Kabir Masum

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this modern era, travelling has become an inevitable activity for medium-high income people and students to energise their mental strength. As a result, they tried to have a budget tour, such as finding a cheap place to stay or purchasing a cheap ticket. Although, numerous systems have been developed to target travel, yet, innumerable gaps exist between them. For instance, reducing carbon emissions and identifying human needs automatically have not been applied to date. Hence, it is crucial to comprehend the needs of individuals through opinion mining and to design the system accordingly. In this study, we analysed human sentiment through Natural Language Processing (NLP) and Machine Learning (ML) to propose a hybrid software framework (HSF) that will automatically fulfil people’s needs and reduce carbon emissions. Latent Dirichlet Allocation (LDA) techniques are used to analyse the sentiment regarding tourism, including locations, costs, hotels, the nearest food, etc. Positive and negative opinions were classified using the Naive Bayes (NB), Logistic Regression (LR), and Gradient Boosting (GB) models. In contrast, the HSF describes a hybrid system designed as the next generation of travelling software. The accuracy of LR and GB models achieved 95.98% and 95.88%, respectively. These models are further evaluated with the performance of the Receiver Operating Characteristic Curve (ROC) and Average Precision (AP). They enumerated the value of 0.91 and 0.40 in Area-Under the Curve-Precision Recall (AUC-PR). This study even utilised the most dominant words in the sentiment analysis from the hotel review. Therefore, the proposed model can be one of the possible solutions to reduce carbon emissions, minimise plastic use, and be a game-changer for green-ecofriendly living.
Original languageEnglish
Title of host publication2022 25th International Conference on Computer and Information Technology (ICCIT)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9798350346022, 9798350346015
ISBN (Print)9798350346039
Publication statusPublished - 3 Mar 2023
EventIEEE 25th International Conference on Computer and Information Technology (ICCIT) - Long Beach Hotel, Cox’s Bazar, Bangladesh
Duration: 17 Dec 202219 Dec 2022


ConferenceIEEE 25th International Conference on Computer and Information Technology (ICCIT)
CityCox’s Bazar
Internet address

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