Research Navigator: Automating Insight Extraction
The Research Navigator is a semantic research paper analysis tool designed to automate the extraction of key insights from academic documents.
Core Objectives & Problem Solved
Extract Structured Insights
Automatically extract key entities, concepts, methodologies, and findings from research papers.
Facilitate Semantic Understanding
Go beyond keywords to understand the deeper meaning of academic content.
Visualize Relationships
Provide interactive visualizations of connections between concepts, methods, and findings.
Natural Language Querying
Enable researchers to query documents and summarize papers using a chatbot.
This tool addresses the time-consuming nature of reading and summarizing research papers, especially for literature reviews.
Methodology & Architecture
01
Data Input & Preprocessing
Users upload PDF/TXT files or paste text. Content is cleaned, segmented, and tokenized using SpaCy.
02
NLP & Entity Extraction
Named Entity Recognition (NER) identifies entities like PERSON, ORG, GPE. Noun phrases extract key concepts.
03
Rule-based Extraction
Sentences with research verbs identify methodology; finding keywords extract results.
04
Embeddings & Clustering
Token and sentence embeddings are generated. Agglomerative clustering groups semantically similar tokens.
05
Concept Graph Construction
Nodes represent concepts, methods, findings; edges are weighted by cosine similarity and visualized with Plotly.
06
Question Answering Chatbot
SentenceTransformer retrieves relevant chunks, and Flan-T5 generates context-aware answers for summaries or specific queries.
Results & Future Vision
Fig 1: Preprocessing Preview showing raw, cleaned, and segmented text.
Fig 2: Named Entity Recognition highlighting different entity types.
Fig 3: Semantic Clustering & Concept Graph with interactive nodes.
Fig 4: Chatbot Queries demonstrating context-aware answers.
The Research Navigator significantly enhances literature review productivity. Future work includes multilingual support, collaborative annotation, and enhanced long-document reasoning.
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