A Hybrid Approach Based Diet Recommendation System Using ML and Big Data Analytics

Authors

  • Muhib Anwar Lambay CSE Dept, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India
  • S. Pakkir Mohideen CSE Dept, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1864

Keywords:

Healthcare recommendations, recommender system, intelligent healthcare recommendation system, healthy diet recommender

Abstract

Recommendations are useful suggestions used by people from all walks of life. However, the usage of recommender systems plays a vital role in modern applications. They are found in different domains such as E-commerce. Concerning the health care industry, recommendations play a very crucial role. This industry has significance as it is linked to the lives of people and their well-being. Human health depends on the diet followed. Keeping this fact in mind, in this paper, we investigated healthy diet recommendations. The recommender systems that are existing in healthcare focused a little in this area. From the literature, it is understood that most of the frameworks on health recommendations are theoretical in nature. As food decides health, it is to be given paramount importance. In this paper, we proposed a hybrid mechanism based on Artificial Intelligence (AI) for big data analytics. Particularly we used Machine Learning (ML) for generating healthy diet recommendations. The proposed system is known as Hybrid Recommender System (HRS). It involves a hybrid approach with Natural Language Processing (NLP) and machine learning. An algorithm named Intelligent Recommender for Healthy Diet (IR-HD) is proposed to analyze data and provide healthy diet recommendations. IR-HD could generate recommendations on a healthy diet and outperform existing models. Python data science platform is used to implement the recommender system. The results of experiments showed that the system is capable of providing quality recommendations and it has performance improvement over the state of the art.

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Author Biographies

Muhib Anwar Lambay, CSE Dept, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

Muhib Anwar Lambay has 12++ years of experience in teaching field, received his Master of Technology (M.Tech) in Computer Science & Engineering from Jawaharlal Nehru Technological University, Hyderabad, India in year 2014 and Bachelor of Engineering (B.E.) in Computer Engineering from University of Mumbai, India in year 2008. Currently pursuing his Ph.D in Computer Science & Engineering from B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai. He presented various academic as well as research-based papers at several National and International Conferences. He is holding many publications in his area and many more papers are in pipeline. Presently working as an Assistant Professor in the department of Computer Engineering at Theem College of Engineering, Affiliated to University of Mumbai. His main research work focuses on Big Data Analytics and Machine Learning.

S. Pakkir Mohideen, CSE Dept, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

S. Pakkir Mohideen received his Ph.D in the field of Personalized Ontology based Adaptive Learning System from Anna University, Chennai in 2017 and M.E. in Computer Science & Engineering from Anna University, Chennai in 2007. He is currently working as an Associate Professor & Head of the Computer Application department at B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai. He participated in several high profile conferences, has many publications and is presently working on many more papers. In addition to his academic career, He received a “Certificate of Appreciation” award for having produced excellent academic results. His areas of research include Big data analytics, Data Mining, Information Retrieval System.

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Published

2022-07-18

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Articles