A5053856890- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Advanced Graph Neural Networks
- Spam and Phishing Detection
- Data Mining Algorithms and Applications
- Rough Sets and Fuzzy Logic
- Bioinformatics and Genomic Networks
- Advanced Clustering Algorithms Research
- Mental Health Research Topics
- Imbalanced Data Classification Techniques
- Digital Marketing and Social Media
- Network Security and Intrusion Detection
- Image Retrieval and Classification Techniques
- Social Media and Politics
- Advanced Image and Video Retrieval Techniques
- Anomaly Detection Techniques and Applications
- Human Mobility and Location-Based Analysis
- Remote-Sensing Image Classification
- Advanced MIMO Systems Optimization
- Advanced Text Analysis Techniques
- Machine Learning in Bioinformatics
- Domain Adaptation and Few-Shot Learning
- Neuroscience and Music Perception
- Telecommunications and Broadcasting Technologies
- Stock Market Forecasting Methods
Thapar Institute of Engineering & Technology
2022-2025
University of Delhi
2022
Bennett University
2019-2022
Indian Institute of Technology BHU
2018-2020
Banaras Hindu University
2018-2020
IBM (India)
2013
The influence maximization (IM) problem identifies the subset of influential users in network to provide solutions for real-world problems like outbreak detection, viral marketing, etc. Therefore, IM is an essential tackle some real-life and activities. Accordingly, many reviews surveys are presented, most them mainly focused on classical frameworks single networks avoided other frameworks. In this context, still has important design aspects along with new challenges problem. Inspired by...
Influence maximization (IM) is the fundamental study of social network analysis. The IM problem finds top k nodes that have maximum influence in network. Most studies focus on maximizing number activated static But real life, networks are dynamic nature. This work addresses diversification proposes an objective function maximizes communities by utilizing bridge nodes. We also propose a diffusion model considers role inactive influencing node. prove submodularity, and monotonicity under...
Abstract The information deployment on social networks through word-of-mouth spreading by online users has contributed well to forming opinions, groups, and connections. This process of is known as diffusion. Its models play a significant role in network analysis. Seeing this importance, the present paper focuses process, model, deployment, applications diffusion First, article discusses background such components, models. Next, their application have been discussed. A comparative analysis...
This Natural language processing, Computer vision, and speech recognition are among the fields in which deep learning outperforms prior approaches. The majority of learning-based music recommendation systems analyze consumers' listening history to understand their temporal preferences. cold start disadvantage isn't addressed, these solutions don't properly use features. Furthermore, qualities preferences not organically related, resulting poor suggestion performance. In this study, Deep...
Summary Online social networks play a pivotal role in the propagation of information and influence as form word‐of‐mouth spreading. The maximization (IM) problem is fundamental to identify small set individuals, which have maximal spread network. Unfortunately, IM NP‐hard. It has been depicted that hill‐climbing greedy approach gives good approximation guarantee. However, it inefficient run on large‐scale networks. In this paper, global evaluation function presented for optimization problem....
The growing popularity of online social networks is quite evident nowadays and provides an opportunity to allow researchers in finding solutions for various practical applications. Link prediction the technique understanding network structure identifying missing future links networks. One well-known classes methods link a similarity-based method, which uses local global topological information predict links. Some also exist based on quasi-local features achieve trade-off between static These...