Bibliographic Similarity

Bibliographic similarity analysis focuses on quantifying the relationships between documents based on shared metadata like authors, citations, and keywords, aiding in tasks such as patent infringement assessment and research trend identification. Current research emphasizes leveraging natural language processing to enhance the accuracy of similarity measures, particularly by incorporating semantic analysis of text alongside bibliographic data. This approach improves the automation of tasks previously reliant on manual expert review, offering significant time savings and potentially more objective evaluations across diverse fields like artificial intelligence and optimization algorithm research.