https://github.com/eXascaleInfolab/axel

Project for exploratory search on scientific articles
https://github.com/eXascaleInfolab/axel

Last synced: 10 months ago
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Project for exploratory search on scientific articles

• Host: GitHub
• URL: https://github.com/eXascaleInfolab/axel
• Owner: eXascaleInfolab
• Created: 2012-08-30T16:44:18.000Z (over 13 years ago)
• Default Branch: master
• Last Pushed: 2015-06-24T11:05:27.000Z (over 10 years ago)
• Last Synced: 2024-08-01T03:31:21.535Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 3.03 MB
• Stars: 3
• Watchers: 8
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
axel

====

Future project to search scientific articles using pre-defined conceps.

Brief details

=============

* We somehow collect research articles from different confrences (ACM proceedings)

* Process all the articles to text, stem/lemmatize, build inverted index

* Load the dictionary of scientific concepts from Computer Science to the system

* Identify all possible concepts inside the article texts, store only TF data

* Create an interface to search for the articles with the concepts you interested in, rank by TF-IDF.

* PROFIT!

Implementation details

======================

* Application should consist of 2 pages initially: one for selecting concepts and another for showings the results.

  * Select concepts page: user autocomplete for concept choosing, then show them as labels (we can also automatically suggest user the other possible relevant concepts as those that appear more often with the target ones)

Platform and frameworks details

===============================

* Django as a back-end framework

* Twitter Boostrap as a front-end framework

* Django haystack (Solr backend) for inverted index

* Celery for background tasks