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Multi paper samples #1
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…tion extraction) Introduces several advanced NLP methods for creating more semantically rich knowledge graphs from research papers. - Adds new node creation strategies: - Scientific entity extraction using a transformer-based NER model (SciBERT). - High-level concept extraction using a hybrid of regex, NLTK, and TF-IDF to identify methods, models, and challenges. - Implements new edge creation techniques: - Relation extraction using spaCy to identify subject-verb-object triples between concepts. - A sophisticated method that combines semantic similarity, co-occurrence analysis, and contextual pattern matching to create typed relationships (e.g., "uses", "improves"). - Provides a new unified `generate_knowledge_graph` API to easily select and combine different extraction methods. - Enhances graph visualization to display relationship labels on edges, a legend, and network statistics.
…ation on individual papers
…nforcement learning graph without unrelated papers
…nto lightrag (fail)
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