Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

User profile as a bridge in cross-domain recommender systems for sparsity reduction

Abstract: In the past two decades, recommender systems have been successfully applied in many e-commerce companies. One of the promising techniques to generate personalized recommendations is collaborative filtering. However, it suffers from sparsity problem. Alleviating this problem, cross-domain recommender systems came into existence in which transfer learning mechanism is applied to exploit the knowledge from other related domains. While applying transfer learning, some information should overlap between source and target domains. Several attempts have been made to enhance the performance of collaborative filtering with the help of other related domains in cross-domain recommender systems framework. Although exploiting the knowledge from other domains is still challenging and open problem in recommender systems. In this paper, we propose a method namely User Profile as a Bridge in Cross-domain Recommender Systems (UP-CDRSs) for transferring knowledge between domains through user profile. Firstly, we build a user profile using demographical information of a user, explicit ratings and content information of user-rated items. Thereafter, the probabilistic graphical model is employed to learn latent factors of users and items in both domains by maximizing posterior probability. At last prediction on unrated item is estimated by an inner product of corresponding latent factors of users and items. Validating of our proposed UP-CDRSs method, we conduct series of experiments on various sparsity levels using cross-domain dataset. The results demonstrate that our proposed method substantially outperforms other without and with transfer learning methods in terms of accuracy.

Wood Polypropylene (PP) Composites Manufactured by Mango Wood Waste with Virgin or Recycled PP: Mechanical, Morphology, Melt Flow Index and Crystalline Behaviour

Abstract: Compositions of wood-polypropylene composites (WPCs) are prepared through melt compounding followed by injection moulding. WPCs are formulated for eight compositions with a different weight ratio of wood, virgin or recycled polypropylene and coupling agent. WPCs compositions are compared in terms of Melt Flow Index, Tensile, FESEM images, Flexural and crystallinity index for same operating variable conditions. From the results, recycled polypropylene based WPCs are superior in comparison to virgin polypropylene based WPCs. With the addition of 5 % coupling agent in recycled polypropylene-based composites for 45:50 composition, tensile and flexural values of WPCs are higher in comparison to all composition and neat virgin or recycled polypropylene. This work stands for the utilization of waste wood with recycled plastic for replacement of wood and virgin plastic.