International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

A Comparative Study of Collaborative Filtering and Content-Based Approaches for Improving the Accuracy of Travel Recommender Systems for Malayalam Language


Affiliations
1 Department of Computer Science, Sullamussalam Science College, Affiliated to University of Calicut, India
 

In this paper, we present a personalized travel recommender system in the Malayalam language using artificial intelligence techniques. The study focuses on the use of travelogues and travel reviews written by travellers on social media as the primary source of data. A dataset of 11000 posts from 6444 travellers was collected from Facebook and other online platforms during 2020-2023. The data was pre-processed to extract relevant information such as travel mode, type of travel, location visited, and climate. Two approaches were used to build the recommender system: collaborative filtering-based K-means clustering and content-based hierarchical agglomerative clustering. The results of the study showed that the clustering approach significantly improved the efficiency and accuracy of the recommender system. K-means clustering achieved an accuracy of 91% and an F1 score of 85%, while the agglomerative hierarchical clustering approach achieved an accuracy of 85% and an F1 score of 84.25%. The results of this study demonstrate the potential of using travelogues and travel reviews to construct a personalized travel recommender system in regional languages.

Keywords

Personalized Travel Recommendation, Malayalam Language, Travelogues, K-Means Clustering, Agglomerative Clustering, Travel Reviews.
User
Notifications
Font Size

  • Mary Priya Sebastian and Santhosh Kumar G. 2023. Malayalam Natural Language Processing: Challenges in Building a Phrase-Based Statistical Machine Translation System. ACM Trans. Asian Low-Resour. Lang. Inf. Process. 22, 4, Article 117 (April 2023), 51 pages. https://doi.org/10.1145/3579163

  • Thara, S., Poornachandran, P. Social media text analytics of Malayalam–English code-mixed using deep learning. J Big Data 9, 45 (2022). https://doi.org/10.1186/s40537-022-00594-3

  • Shahidul Islam Khan, FaisalBinAziz, Emotion Detection from Multilingual Text and MultiEmotional Sentence using Difference NLP Feature Extraction Technique and ML Classifier, Int. J. Advanced Networking and Applications, Volume: 14 Issue: 03 Pages: 5429-5435(2022) ISSN: 0975-0290

  • Ajees A P, Sumam Mary Idicula, A Named Entity Recognition System for Malayalam using Neural Networks, Procedia Computer Science, Volume 143, 2018, Pages 962-969, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2018.10.338.

  • L. Sindhu and Sumam Mary Idicula. 2017. Plagiarism Detection in Malayalam Language Text using a Composition of Similarity measures. In Proceedings of the 9th International Conference on Machine Learning and Computing (ICMLC 2017). Association for Computing Machinery, New York, NY, USA, 456–460. https://doi.org/10.1145/3055635.3056655

  • Akhil, K.K., Rajimol, R. & Anoop, V.S. Parts-ofSpeech tagging for Malayalam using deep learning techniques. Int. j. inf. tecnol. 12, 741–748 (2020). https://doi.org/10.1007/s41870-020-00491-z

  • C. Liu, X. Zeng, H. Lu, Y. Liu, and J. Guo, A Multi-View Clustering Framework for Personalized Tourist Destination Recommendation, IEEE International Conference on Big Data (Big Data), pp. 6861-6868, 2018.

  • J. Zhang, Y. Su, Y. Chen, Y. Wang, and X. Fan, Personalized Tourist Destination Recommendation based on User Interests, 12th International Conference on Natural Computation (ICNC), pp. 686-691, 2018.

  • X. Zeng, H. Lu, Y. Liu, and J. Guo, Personalized Tourist Destination Recommendation based on User Preferences, 25th International Conference on Computer Communication and Networks (ICCCN), pp. 1-6, 2017.

  • X. Zeng, Y. Liu, J. Guo, and H. Lu, Tourist Destination Recommendation based on User Reviews, 24th International Conference on Computer Communication and Networks (ICCCN), pp. 1-6, 2016.

  • M. Ouzzani, M. El-Hajj, and A. K. Elmagarmid, Tourist Destination Recommendation using a Hybrid Collaborative Filtering and Sentiment Analysis Approach, 10th International Conference on Natural Computation (ICNC), pp. 1537-1541, 2016.

  • Y. Zhao, S. Wang, and L. Chen, Personalized Tourist Destination Recommendation based on Social Network Analysis, 10th International Conference on Natural Computation (ICNC), pp. 1542-1546, 2016.


Abstract Views: 186

PDF Views: 0




  • A Comparative Study of Collaborative Filtering and Content-Based Approaches for Improving the Accuracy of Travel Recommender Systems for Malayalam Language

Abstract Views: 186  |  PDF Views: 0

Authors

Muneer V.K
Department of Computer Science, Sullamussalam Science College, Affiliated to University of Calicut, India
Mohamed Basheer K.P
Department of Computer Science, Sullamussalam Science College, Affiliated to University of Calicut, India

Abstract


In this paper, we present a personalized travel recommender system in the Malayalam language using artificial intelligence techniques. The study focuses on the use of travelogues and travel reviews written by travellers on social media as the primary source of data. A dataset of 11000 posts from 6444 travellers was collected from Facebook and other online platforms during 2020-2023. The data was pre-processed to extract relevant information such as travel mode, type of travel, location visited, and climate. Two approaches were used to build the recommender system: collaborative filtering-based K-means clustering and content-based hierarchical agglomerative clustering. The results of the study showed that the clustering approach significantly improved the efficiency and accuracy of the recommender system. K-means clustering achieved an accuracy of 91% and an F1 score of 85%, while the agglomerative hierarchical clustering approach achieved an accuracy of 85% and an F1 score of 84.25%. The results of this study demonstrate the potential of using travelogues and travel reviews to construct a personalized travel recommender system in regional languages.

Keywords


Personalized Travel Recommendation, Malayalam Language, Travelogues, K-Means Clustering, Agglomerative Clustering, Travel Reviews.

References