Mukta, Md. Saddam Hossain
An Artificial Intelligence-based Framework to Achieve the Sustainable Development Goals in the Context of Bangladesh
Hasan, Md. Tarek, Shamael, Mohammad Nazmush, Akter, Arifa, Islam, Rokibul, Mukta, Md. Saddam Hossain, Islam, Salekul
Sustainable development is a framework for achieving human development goals. It provides natural systems' ability to deliver natural resources and ecosystem services. Sustainable development is crucial for the economy and society. Artificial intelligence (AI) has attracted increasing attention in recent years, with the potential to have a positive influence across many domains. AI is a commonly employed component in the quest for long-term sustainability. In this study, we explore the impact of AI on three pillars of sustainable development: society, environment, and economy, as well as numerous case studies from which we may deduce the impact of AI in a variety of areas, i.e., agriculture, classifying waste, smart water management, and Heating, Ventilation, and Air Conditioning (HVAC) systems. Furthermore, we present AI-based strategies for achieving Sustainable Development Goals (SDGs) which are effective for developing countries like Bangladesh. The framework that we propose may reduce the negative impact of AI and promote the proactiveness of this technology.
Predicting Movie Genre Preferences from Personality and Values of Social Media Users
Mukta, Md. Saddam Hossain (Bangladesh University of Engineering and Technology) | Khan, Euna Mehnaz (Bangladesh University of Engineering and Technology) | Ali, Mohammed Eunus (Bangladesh University of Engineering and Technology) | Mahmud, Jalal (IBM Research)
We propose a novel technique to predict a user’s movie genre preference from her psycholinguistic attributes obtained from user social media interactions. In particular, we build machine learning based classification models that take user tweets as input to derive her psychological attributes: personality and value scores, and gives her movie genre preference as output. We train these models using user tweets in Twitter, and her reviews and ratings of movies of different genres in Internet movie database (IMDb). We exploit a key concept of psychology, i.e., an individual’s personality and values may influence her choice in performing different actions in real life. We have investigated how personality and values independently and collectively influence a user preference on different movie genres. Our proposed model can be used for recommending movies to social media users.