Update README.md

README.md

@@ -121,53 +121,53 @@ The system is modular, consisting of several Python components:
   ## 🚧 Limitations
 
 - **Language**  
-1- Optimized for English. Performance may degrade significantly on other languages.
+  Optimized for English. Performance may degrade significantly on other languages.
 
 - **Domain Specificity**  
-1. Achieves best results in AI/ML domains. Adaptation (e.g., domain-specific rules or keywords) is required for other fields.
+  Achieves best results in AI/ML domains. Adaptation (e.g., domain-specific rules or keywords) is required for other fields.
 
 - **PDF Quality**  
-1. Heavily reliant on clean text extraction. Scanned PDFs, complex layouts, or poor OCR significantly reduce accuracy.
+  Heavily reliant on clean text extraction. Scanned PDFs, complex layouts, or poor OCR significantly reduce accuracy.
 
 - **Scalability**  
-1. Processing very large corpora (e.g., >10,000 papers) may require significant computational resources or distributed infrastructure.
+  Processing very large corpora (e.g., >10,000 papers) may require significant computational resources or distributed infrastructure.
 
 - **Relationship Nuance**  
-1. Relationships are extracted based on co-occurrence and semantic similarity. Logical or causal connections may not be captured.
+  Relationships are extracted based on co-occurrence and semantic similarity. Logical or causal connections may not be captured.
 
 - **Temporal Accuracy**  
-1. Depends on accurate publication date extraction from metadata or filenames. Errors may affect timeline analysis.
+  Depends on accurate publication date extraction from metadata or filenames. Errors may affect timeline analysis.
 
 - **Visualization Clutter**  
-1. Interactive graph visualizations become cluttered and less interpretable when node count exceeds ~1000.
+  Interactive graph visualizations become cluttered and less interpretable when node count exceeds ~1000.
 
 ---
 
 ## 🌱 Future Work
 
-- **Multi-language Support**
-1. Integration of multilingual NLP models to support non-English documents.
+- **Multi-language Support**  
+  Integration of multilingual NLP models to support non-English documents.
 
 - **Citation Integration**  
-1. Incorporating citation links and citation graph data into network analysis.
+  Incorporating citation links and citation graph data into network analysis.
 
 - **ML-based Extraction**  
-1. Training supervised or semi-supervised models to improve concept and relation extraction quality.
+  Training supervised or semi-supervised models to improve concept and relation extraction quality.
 
 - **Advanced Visualizations**  
-1. Implementation of timeline views, dashboards, and alternative graph layouts (e.g., hierarchical, clustered).
+  Implementation of timeline views, dashboards, and alternative graph layouts (e.g., hierarchical, clustered).
 
 - **Improved Temporal Modeling**  
-1.  Use of advanced time-series techniques to detect emerging trends and historical shifts.
+  Use of advanced time-series techniques to detect emerging trends and historical shifts.
 
 - **Web Interface**  
-1. A user-friendly UI for uploading documents, viewing visualizations, and downloading results.
+  A user-friendly UI for uploading documents, viewing visualizations, and downloading results.
 
 - **Knowledge Graph Export**  
-1. Export capabilities for standard knowledge graph formats like RDF, OWL, or JSON-LD.
+  Export capabilities for standard knowledge graph formats like RDF, OWL, or JSON-LD.
 
 - **Concept Disambiguation**  
-1. Methods to differentiate between identically named but contextually distinct concepts.
+  Methods to differentiate between identically named but contextually distinct concepts.
 
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