{ "info": { "author": "Ra\u00fal B. Netto", "author_email": "raulbeni@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Information Technology", "Intended Audience :: System Administrators", "Intended Audience :: Telecommunications Industry", "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 3", "Topic :: Security" ], "description": "# WHOIS Similarity Distance\nThis algorithm allows you to determine a numeric distance between two given domains, using their WHOIS information.\nThis work is part of my master thesis and the soonest possible I going to add more theoric information and the experiments have been carried out for this algorithm.\n\n\n\n## Authors\n- **Ra\u00fal B. Netto** \n ([@Piuliss](https://www.twitter.com/Piuliss), , )\n- **Sebast\u00edan Garc\u00eda**\n ([@eldraco](https://www.twitter.com/eldraco), )\n\n## Getting started\n \n git clone git@github.com:stratosphereips/whois-similarity-distance.git\n pip install -r requirements.txt\n python ./wsd_domains.py google.com cisco.com\n \n## Using pip \nYou can find [whois_similarity_distance](https://pypi.python.org/pypi/whois_similarity_distance) \nin Pypi\n \n pip install whois_similarity_distance \n \n## Optional\nWSD scripts works with [pythonwhois](https://pypi.python.org/pypi/pythonwhois/2.4.3) library to get the \nWHOIS information of the domains. 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