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RefTools

Tools:

CommonRefs
nCitations

CommonRefs

Have you ever looked at your library of references and wondered: Have I missed an important publication on the topic?
Or, more specifically: What publications are most frequently cited in my references, and do I have them?

commonrefs.py answers the question by parsing the references in your BibTeX file, looking up which papers they cite, generating a ranking of the cited papers, and indicating which papers you're missing.

Dependencies

Install the required python packages via pip3 install requests

Preparation

  1. Get the Elsevier Developers® API Key at https://dev.elsevier.com/user/login and save it inside api_key.txt in the repository folder.
  2. Copy your library's *.bib file into the repository folder. The BibTeX entries must contain the Document Object Identifiers (DOIs) in the doi field. Mendeley can automatically fetch DOIs.

Usage

Open the command line in the repository folder and run python3 commonrefs.py.

Output

Example:

Document Object Identifier (DOI) found for 190 publications
No references found for 49 publications (see not_found.txt file)

Writing results to results.txt:
29 x A model of saliency-based visual attention for rapid scene analysis    ?
24 x ImageNet classification with deep convolutional neural networks
21 x Learning to predict where humans look
20 x Very deep convolutional networks for large-scale image recognition
15 x Shifts in selective visual attention: Towards the underlying neural circuitry    ?
14 x The pascal visual object classes (VOC) challenge    x
14 x Graph-based visual saliency
12 x Saliency based on information maximization
12 x Contextual guidance of eye movements and attention in real-world scenes: The role of global features in object search
11 x Rich feature hierarchies for accurate object detection and semantic segmentation
10 x A feature-integration theory of attention
10 x Object detection with discriminatively trained part-based models
10 x A saliency-based search mechanism for overt and covert shifts of visual attention    ?
10 x State-of-the-art in visual attention modeling
9 x SUN: A Bayesian framework for saliency using natural statistics    ?
9 x Quantitative analysis of human-model agreement in visual saliency modeling: A comparative study
9 x Gradient-based learning applied to document recognition
9 x Modeling the role of salience in the allocation of overt visual attention    ?
9 x Computational modelling of visual attention    ?
9 x Histograms of oriented gradients for human detection    x
...

The number at the beginning of the file indicates the number of times this publication has been cited in the references.
A x at the end of the line indicates that neither the title nor the DOI has been found in the BibTeX file.
A ? at the end of the line indicates that the title has not been found in the BibTeX file and no DOI could be retrieved. The results are written to results.txt

nCitations

nCitations allows you to quickly look up the number of citations of a paper anywhere!
Simply select the title of the paper with your mouse and hit your preferred keyboard shortcut.

Dependencies

Install xclip to provide access to text selection from you shell.
For example, in Ubuntu run sudo apt-get install xclip.

Install the required python packages via pip install beautifulsoup4

Preparation

You have to set up a keyboard shortcut to execute bash <full path to reftools folder>/ncitations.sh.
For example, in Ubuntu

  1. Go to System Settings -> Keyboard -> Shortcuts.
  2. Select Custom Shortcuts, add a new shortcut by clicking +, choose a name and enter the command from above.
  3. Click on Deactivated on the right of your newly created shortcut and hit your preferred keyboard combination (e.g. Ctrl-Alt-N)

Usage

Select the paper title anywhere (e.g. in a pdf document, in your browser, etc.), hit your keyboard shortcut and get the number of citations ion a pop-up window.

The results are cached in cache.txt, so you might occasinally want to remove old entries from that file to keep the results up to date.

Result

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