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        "author": "Yusuke Matsubara",
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        "description": "=====================\r\nSCluster\r\n=====================\r\n--------------------------------------------------------\r\nan implementation of spectral clustering for documents\r\n--------------------------------------------------------\r\n\r\n :Homepage: http://github.com/whym/scluster\r\n :Contact:  http://whym.org\r\n\r\nOverview\r\n==============================\r\nSpectral clustering a modern clustering technique considered to be effective for image clustering among others. [#]_ [#]_\r\n\r\nThis software find clusters among documents based on the bag-of-words representation [#]_ and TF-IDF weighting [#]_.\r\n\r\n.. [#] Ulrike von Luxburg, A Tutorial on Spectral Clustering, 2006. http://arxiv.org/abs/0711.0189\r\n.. [#] Chris H. Q. Ding, Spectral Clustering, 2004. http://ranger.uta.edu/~chqding/Spectral/\r\n.. [#] http://en.wikipedia.org/wiki/Bag_of_words_model\r\n.. [#] http://en.wikipedia.org/wiki/Tf%E2%80%93idf\r\n\r\nRequirements\r\n==============================\r\nFollowing softwares are required.\r\n\r\n- Python 2 or 3\r\n- Numpy\r\n- Scipy\r\n\r\nHow to use\r\n==============================\r\n1. Prepare documents as raw-text files, and put them in a directory, for example, 'reuters'.\r\n2. Prepare a category file. For example, 'cats.txt' may contain: ::\r\n\r\n     14833 palm-oil veg-oil\r\n     14839 ship\r\n\r\n   This means that the file '14833' has 'palm-oil' and 'veg-oil' as\r\n   its categories, and '14839' has 'ship' as its category.\r\n\r\n3. Run: ``python scluster/clusterer.py cats.txt reusters/ -m kmeans``,\r\n\r\nNotes\r\n==============================\r\n- When you use the Reuters set, notice No 17980 might contain\r\n  non-Unicode character at Line 10. It should probably read: \"world\r\n  economic growth-side measures ...\"\r\n\r\n.. [#] http://www.daviddlewis.com/resources/testcollections/reuters21578/",
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