Connected Papers

Connected Papers is a tool designed to help researchers and academics explore and understand the relationships between scientific papers through a visual graph representation.

Key features:
- Generates a graph where each node represents a research paper, with edges indicating relevance and connection between papers
- Allows interactive exploration by clicking on nodes to view detailed information about each paper, including title, authors, abstract, and publication details
- Helps users find closely related papers to a given paper, making it easier to explore literature around a specific topic
- Enables identification of seminal and influential papers in a field by examining connections and centrality of nodes in the graph
- Provides search functionality to quickly locate relevant research by title, author, or keywords
- Offers filtering options to narrow down search results based on criteria such as publication year and journal

How it works:
Users input a paper of interest by providing its title, DOI, or other identifying information. Connected Papers then generates a visual graph based on the input paper, displaying related papers and their connections. Users can explore the graph by clicking on nodes to view detailed information about each paper and navigate through the network of related research.

Integrations:
Connected Papers integrates with various academic databases and repositories to fetch and display paper information. It typically works with major academic databases like PubMed, arXiv, and Google Scholar.

Use of AI:
Connected Papers leverages advanced algorithms and possibly machine learning models to analyze and visualize the connections between papers.

How to access:
Connected Papers is available as a web application, accessible through modern web browsers.