Neural network Connected Papers

Connected Papers is an online tool for searching and analyzing scientific articles that helps researchers navigate the sea of ​​publications. With its help, you can see a visual map of connections between articles, built on the basis of their citations and thematic similarity.

How does this work? Simply enter an article title or link, and Connected Papers will create a graph showing how that article relates to others. This helps you discover new research, follow current topics, and compare approaches from different authors.

Features of Connected Papers

• Link analysis . To create a graph, the tool analyzes about 50,000 articles and selects dozens of the most similar topics.
• Visual chart . Connected Papers builds a graph where articles are arranged based on their thematic proximity. Even if articles do not quote each other directly, they may be related by similar ideas.
• Similarity metric . Links between articles are based on co-citation and bibliographic connections. The more overlap in references and citations, the more likely it is that articles cover similar topics.
• Graphic distribution . The algorithm distributes articles on the graph so that similar works are closer to each other, and less related ones are farther away. This helps the researcher to clearly see the structure of the field and choose directions for further study.

Connected Papers is connected to the Semantic Scholar database, which covers hundreds of millions of scientific publications from various fields.