Personal Details

Qualification: N/A

Faculty: Science and Technology

ORC_ID: 0000-0001-7903-3988

Google URL: https://scholar.google.com/citations?user=U0qFZnMAAAAJ&hl=en

Research Details

Area of Research: Recommender Systems, Information Filtering, IoT, Data Mining, Knowledge Graph

Research Area Summary:
My Ph.D dessertation proposes a Context-Aware Recommender System Architecture for Smart Social Networks specifically for Event Based Social Networks (EBSNs) and Smart object Based Social Networks (SBSNs). Context modeling and integration have been identified as a major challenge in context-aware recommender systems. To overcome this challenge in EBSNs, Three-Tier IoT-Edge-Cloud (3T-IEC) architecture has been proposed that utilizes edge computing layer to preprocess and filter IoT data for deriving contextual attributes in event generation process. Furthermore, a novel Smart Object Recommendation architecture (SORec) for SBSN has been proposed to suggest appropriate smart objects to users. In order to meet the requirements of these dynamic and everchanging smart social networks, the proposed 3T-IEC architecture has been extended to 3T-IEC* that provides more accurate and personalized recommendations for inductive applications. The proposed architectures lay out a solid foundation for the future development of recommendation applications by researchers and developers.

Research Gate:https://www.researchgate.net/profile/Pratibha-Mahajan-3/research