The system features an AI-powered chatbot for user interaction and automates PDF summarization, providing quick and concise insights from academic documents.
Uses Natural Language Processing (NLP) and Machine Learning (ML) to classify citations as positive, negative, or neutral based on contextual meaning.
AI-powered Optical Character Recognition (OCR) extracts text from scanned PDFs, ensuring that even complex academic documents are processed efficiently.
The system uses AI to analyze citation patterns, highlighting key studies and research gaps, allowing users to identify emerging trends in their field.
Generates network diagrams to visualize the relationships between citations, helping users uncover the broader context of academic research and understand how works are interconnected.
Ensures fast, real-time processing of uploaded documents and citations, providing instant sentiment analysis and visualization updates as new data is inputted, making the analysis process faster and more efficient.
Analyze sentiment, explore citation trends, and gain actionable insights through real-time visualizations, improving research evaluation and decision-making.
Get Started ProjectAI-powered chatbot for assistance and automated PDF summarization for quick insights.
Gain insights into whether citations are positive, negative, or neutral, helping you understand how academic works are perceived.
Explore citation trends and relationships with dynamic visualizations like network diagrams, pie charts, and treemaps.
CiteSense - Citation Sentiment Analysis