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"description": "..\n This file is part of Invenio.\n Copyright (C) 2015 CERN.\n\n Invenio is free software; you can redistribute it\n and/or modify it under the terms of the GNU General Public License as\n published by the Free Software Foundation; either version 2 of the\n License, or (at your option) any later version.\n\n Invenio is distributed in the hope that it will be\n useful, but WITHOUT ANY WARRANTY; without even the implied warranty of\n MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU\n General Public License for more details.\n\n You should have received a copy of the GNU General Public License\n along with Invenio; if not, write to the\n Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston,\n MA 02111-1307, USA.\n\n In applying this license, CERN does not\n waive the privileges and immunities granted to it by virtue of its status\n as an Intergovernmental Organization or submit itself to any jurisdiction.\n\n====================\n Invenio-Classifier\n====================\n\n.. image:: https://img.shields.io/travis/inveniosoftware-contrib/invenio-classifier.svg\n :target: https://travis-ci.org/inveniosoftware-contrib/invenio-classifier\n\n.. image:: https://img.shields.io/coveralls/inveniosoftware-contrib/invenio-classifier.svg\n :target: https://coveralls.io/r/inveniosoftware-contrib/invenio-classifier\n\n.. image:: https://img.shields.io/github/tag/inveniosoftware-contrib/invenio-classifier.svg\n :target: https://github.com/inveniosoftware-contrib/invenio-classifier/releases\n\n.. image:: https://img.shields.io/pypi/dm/invenio-classifier.svg\n :target: https://pypi.python.org/pypi/invenio-classifier\n\n.. image:: https://img.shields.io/github/license/inveniosoftware-contrib/invenio-classifier.svg\n :target: https://github.com/inveniosoftware-contrib/invenio-classifier/blob/master/LICENSE\n\n\nInvenio module for record classification.\n\n* Free software: GPLv2 license\n* Documentation: https://pythonhosted.org/invenio-classifier\n\n\nFeatures\n========\n\nClassifier automatically extracts keywords from fulltext documents. The\nautomatic assignment of keywords to textual documents has clear benefits\nin the digital library environment as it aids catalogization,\nclassification and retrieval of documents.\n\nKeyword extraction is simple\n============================\n\n.. note:: Classifier requires Python `RDFLib `__ in order\n to process the RDF/SKOS taxonomy.\n\nIn order to extract relevant keywords from a document ``fulltext.pdf``\nbased on a controlled vocabulary ``thesaurus.rdf``, you would run\nClassifier as follows:\n\n.. code-block:: shell\n\n ${INVENIO_WEB_INSTANCE} classifier extract -k thesaurus.rdf -f fulltext.pdf\n\nLaunching ``${INVENIO_WEB_INSTANCE} classifier --help`` shows the options available.\n\nAs an example, running classifier on document\n`nucl-th/0204033 `__ using the\nhigh-energy physics RDF/SKOS taxonomy (``HEP.rdf``) would yield the\nfollowing results (based on the HEP taxonomy from October 10th 2008):\n\n.. code-block:: text\n\n Input file: 0204033.pdf\n\n Author keywords:\n Dense matter\n Saturation\n Unstable nuclei\n\n Composite keywords:\n 10 nucleus: stability [36, 14]\n 6 saturation: density [25, 31]\n 6 energy: symmetry [35, 11]\n 4 nucleon: density [13, 31]\n 3 energy: Coulomb [35, 3]\n 2 energy: density [35, 31]\n 2 nuclear matter: asymmetry [21, 2]\n 1 n: matter [54, 36]\n 1 n: density [54, 31]\n 1 n: mass [54, 16]\n\n Single keywords:\n 61 K0\n 23 equation of state\n 12 slope\n 4 mass number\n 4 nuclide\n 3 nuclear model\n 3 mass formula\n 2 charge distribution\n 2 elastic scattering\n 2 binding energy\n\n\nThesaurus\n=========\n\nClassifier performs an extraction of keywords based on the recurrence\nof specific terms, taken from a controlled vocabulary. A controlled\nvocabulary is a thesaurus of all the terms that are relevant in a\nspecific context. When a context is defined by a discipline or branch of\nknowledge then the vocabulary is said to be a *subject thesaurus*.\nVarious existing subject thesauri can be found\n`here `__.\n\nA subject thesaurus can be expressed in several different formats.\nDifferent institutions/disciplines have developed different ways of\nrepresenting their vocabulary systems. The taxonomy used by classifier\nis expressed in RDF/SKOS. It allows not only to list keywords but to\nspecify relations between the keywords and alternative ways to represent\nthe same keyword.\n\n.. code-block:: xml\n\n \n \n scalar\n nostandalone\n \n\n \n \n field theory\n QFT\n /field theor\\w*/\n nostandalone\n \n\n \n \n \n field theory: scalar\n scalar field\n \n\n\nIn RDF/SKOS, every keyword is wrapped around a *concept* which\nencapsulates the full semantics and hierarchical status of a term -\nincluding synonyms, alternative forms, broader concepts, notes and so on\n- rather than just a plain keyword.\n\nThe specification of the SKOS language and `various\nmanuals `__\nthat aid the building of a semantic thesaurus can be found at the `SKOS\nW3C\nwebsite `__.\nFurthermore, Classifier can function on top of an extended version of\nSKOS, which includes special elements such as key chains, composite\nkeywords and special annotations.\n\nKeyword extraction\n==================\n\nClassifier computes the keywords of a fulltext document based on the\nfrequency of thesaurus terms in it. In other words, it calculates how\nmany times a thesaurus keyword (and its alternative and hidden labels,\ndefined in the taxonomy) appears in a text and it ranks the results.\nUnlike other similar systems, Classifier does not use any machine\nlearning or AI methodologies - a just plain phrase matching using\n`regular expressions `__: it\nexploits the conformation and richness of the thesaurus to produce\naccurate results. It is then clear that Classifier performs best on top\nof rich, well-structured, subject thesauri expressed in the RDF/SKOS\nlanguage.\n\nHappy hacking and thanks for flying Invenio-Classifier.\n\n| Inspirehep Development Team\n| Email: admin@inspirehep.net\n| Twitter: http://twitter.com/inveniosoftware\n| GitHub: https://github.com/inveniosoftware-contrib/invenio-classifier\n| URL: http://inveniosoftware.org\n\n\n..\n This file is part of Invenio.\n Copyright (C) 2015, 2018 CERN.\n\n Invenio is free software; you can redistribute it\n and/or modify it under the terms of the GNU General Public License as\n published by the Free Software Foundation; either version 2 of the\n License, or (at your option) any later version.\n\n Invenio is distributed in the hope that it will be\n useful, but WITHOUT ANY WARRANTY; without even the implied warranty of\n MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU\n General Public License for more details.\n\n You should have received a copy of the GNU General Public License\n along with Invenio; if not, write to the\n Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston,\n MA 02111-1307, USA.\n\n In applying this license, CERN does not\n waive the privileges and immunities granted to it by virtue of its status\n as an Intergovernmental Organization or submit itself to any jurisdiction.\n\nChanges\n=======\n\nVersion 1.3.2 (release 2018-03-12)\n----------------------------------\n\nBug fixes\n~~~~~~~~~\n\n- Prevent the \"unprintable KeyError\" problem from happening.\n\nVersion 1.3.1 (release 2017-06-23)\n----------------------------------\n\nBug fixes\n~~~~~~~~~\n\n- Reverse sort core keywords.\n\nVersion 1.3.0 (release 2017-06-22)\n----------------------------------\n\nIncompatible changes\n~~~~~~~~~~~~~~~~~~~~\n\n- Exports list of objects rather than list of tuples, to help ES\n directly indexing the content.\n\nVersion 1.2.0 (release 2017-06-21)\n----------------------------------\n\nIncompatible changes\n~~~~~~~~~~~~~~~~~~~~\n\n- Do not use keywords as dictionary keys, rather as elements in a list.\n\nVersion 1.1.2 (release 2017-05-22)\n----------------------------------\n\nBug fixes\n~~~~~~~~~\n\n- Supports '\u00b7' author separator\n- Support utf8 author-keywords\n\nVersion 1.1.1 (release 2017-05-19)\n----------------------------------\n\nBug fixes\n~~~~~~~~~\n\n- Enforce utf8 also for non PDF files in extractor.\n\nVersion 1.1.0 (release 2017-05-17)\n----------------------------------\n\nIncompatible changes\n~~~~~~~~~~~~~~~~~~~~\n\n- Changes dict export format for author keywords, into an improved and semantic\n way.\n- Renames keys in dict export to be lower case and separated by `_`.\n\nBug fixes\n~~~~~~~~~\n\n- Drop trailing dots in author keywords.\n\nVersion 1.0.1 (release 2017-01-11)\n----------------------------------\n\nIncompatible changes\n~~~~~~~~~~~~~~~~~~~~\n\n- Changes module to be compatible with Invenio 3.\n\nBug fixes\n~~~~~~~~~\n\n- Fixes a crash when trying to discover a taxonomy when\n CLASSIFIER_WORKDIR is set to None.\n- Updates minimum dependencies of Invenio packages to newer versions.\n- Removes a bug in bibclassify_keyword_analyzer.py. If a combination\n is found via a synonym or regexp it is no longer thrown away just\n because the components of the combination are not found in the text.\n- Adds missing `invenio_base` dependency.\n\nVersion 0.1.0 (release 2015-08-19)\n----------------------------------\n\n- Initial public release.\n\n\n",
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