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citrus search

★4.3
💬50
💲Free

Citrus is a powerful tool for researchers looking to find relevant scientific papers based on similarity rather than keywords. It uses machine learning and graph analysis to provide an overview of important contributions in a research field, helping users discover closely related work and avoid missing key publications.

💻
Platform
web
Academic search engineCitation analysisMachine learningOpen Research CorpusResearchScientific literature searchSemantic Scholar

What is citrus search?

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.

Core Technologies

  • Machine Learning
  • Graph Analysis
  • Text-Based Similarity

Key Capabilities

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

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

Core Benefits

  • Finds relevant papers based on similarity, not just keywords
  • Provides an overview of important contributions on a timeline
  • Uses machine learning techniques to compute paper similarity
  • Indexes a large dataset of scientific publications

Key Features

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

How to Use

  1. 1
    Select a seed paper
  2. 2
    Start the search (or add additional seed papers first)
  3. 3
    Get an overview of closely related work

Frequently Asked Questions

Q.What is Citrus?

A.Citrus is a similarity-based search engine for scientific literature that helps you find closely related publications based on a seed paper.

Q.How does Citrus work?

A.You choose a seed paper, and Citrus returns closely related publications based on the similarity measure you select (Citation Network or Content). The similarity is computed using graph and text-based machine-learning techniques.

Q.What data does Citrus use?

A.Citrus indexes data provided by Semantic Scholar's Open Research Corpus, which spans over 200 Million publications and around 2 Billion citations.

Pros & Cons (Reserved)

✓ Pros

  • Finds relevant papers based on similarity, not just keywords
  • Provides an overview of important contributions on a timeline
  • Uses machine learning techniques to compute paper similarity
  • Indexes a large dataset of scientific publications

✗ Cons

  • Requires a seed paper to start the search
  • Similarity depends on the selected similarity measure (Citation Network or Content)
  • The site is under active development, so bugs may be present

Alternatives

No alternatives found.