Citrus

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Similarity-based search engine for scientific literature, using machine learning to find related papers.

Collection time:
2025-01-11
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What is Citrus?

Citrus is a similarity-based search engine for scientific literature. You select a paper, start the search, and jump right to the heart of your research domain. Get an overview of important contributions from seminal papers to the state of the art. Citrus helps you find relevant articles in a research field with a single search. It allows you to explore closely related research, find relevant work fast, view important contributions at a glance on a timeline, and avoid missing papers using different taxonomy. Behind the scenes, the similarity of papers is computed using graph and text-based machine-learning techniques. Citrus indexes data provided by Semantic Scholar’s Open Research Corpus, which spans over 200 Million publications and around 2 Billion citations.


How to use Citrus?

Select a seed paper. 2. Start the search (or add additional seed papers first). 3. Get an overview of closely related work.


Citrus’s Core Features

Similarity-based search for scientific literature Citation network analysis Content-based similarity analysis Timeline view of important contributions


Citrus’s Use Cases

  • Finding closely related research papers based on a seed paper.
  • Getting an overview of important contributions in a research field.
  • Discovering papers that might be missed by traditional text-based search.

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