{ "info": { "author": "Junpei Kawamoto", "author_email": "kawamoto.junpei@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Natural Language :: English", "Programming Language :: Python", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Software Development :: Libraries" ], "description": "CLI tools for analyzing review graphs \n======================================\n\n|GPLv3| |Build Status| |wercker status| |Release|\n\n|Logo|\n\nThis package provides useful scripts to analyze datasets themselves and\nrun an method for mining review graphs.\n\nInstallation\n------------\n\nUse ``pip`` to install this package.\n\n.. code:: sh\n\n $ pip install --upgrade rgmining-script\n\ndataset command\n---------------\n\ndataset command provides a set of functions to inspect a dataset. Those\nfunctions are divided to two groups, analyzing reviewer information and\nanalyzing product information.\n\nAnalyzing reviewer information\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nTo analyze reviewer information of a dataset, dataset command provides\nthe following subcommands:\n\n- retrieve: output the ID of reviewers who review at least one of the\n given products,\n- active: output the ID of reviewers who review at least threshold\n items,\n- reviewer\\_size: output the number of reviews of each reviewer who\n reviews target products,\n- filter: output reviews posted by reviewers whose IDs match the given\n set of IDs.\n\nAnalyzing product information\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nTo analyze product information of a dataset, dataset command provides\nthe following subcommands:\n\n- average: output average rating scores of each product,\n- distinct: output distinct product IDs,\n- popular: output ID of products of which the member of reviews >=\n threshold.\n- filter: output reviews posted to products of which IDs match the\n given set of IDs.\n- variance: output variances of reviews for each product.\n\nBasic usage\n~~~~~~~~~~~\n\nThe basic usage of this command is\n\n.. code:: sh\n\n $ dataset reviewer \n\nor\n\n.. code:: sh\n\n $ dataset product \n\nwhere the dataset-specifier is a name of the dataset to be analyzed. It\nis depended on which libraries you have installed and ``dataset -h``\nreturns a list of available dataset names.\n\ndataset-parameters are optional arguments specified with\n``--dataset-param`` flag. The ``--dataset-param`` flag takes a string\nwhich connecting key and value with a single =. The ``--dataset-param``\nflag can be given multi-times. You can find what kinds of parameter keys\nare defined in the dataset you want to use from documents of function\n``load`` defined in the dataset.\n\nFor example, dataset ``file`` means loading a dataset from a file, of\nwhich each line contains a review in `the JSON\nformat `__.\nTo load such dataset, use ``file`` as the dataset-specifier and give the\nfile path as a dataset-parameter with ``file`` key, i.e.\n``--dataset-param file=\"path/to/file\"``.\n\nSee `document site `__ for more\ninformation about each subcommand.\n\nanalyze command\n---------------\n\nanalyze command loads a dataset and run a method to find anomalous\nreviewers and compute a rating summary of each product.\n\nThe basic usage of this command is\n\n.. code:: sh\n\n $ analyze \n\nThe dataset-specifier and datasset-parameters are the same parameters\ndescribed in the dataset command explanation.\n\nThe method-specifier is a name of installed method. You can see\navailable method names by ``analyze -h``.\n\nmethod-parameters are optional arguments specified with\n``--method-param`` flag. The ``--method-param`` flag takes a string\nwhich connecting key and value with a single =, and can be given\nmulti-times.\n\nYou can find what kinds of parameter keys are defined in the method you\nwant to run from documents of the constructor of the review graph object\ndefined in the method.\n\nFor example, `Fraud Eagle `__\ntakes one parameter ``epsilon`` and you can give a value by\n``--method-param epsilon=0.25``.\n\nSee `document site `__ for more\ninformation.\n\nLicense\n-------\n\nThis software is released under The GNU General Public License Version\n3, see\n`COPYING `__ for\nmore detail.\n\n.. |GPLv3| image:: https://img.shields.io/badge/license-GPLv3-blue.svg\n :target: https://www.gnu.org/copyleft/gpl.html\n.. |Build Status| image:: https://travis-ci.org/rgmining/script.svg?branch=master\n :target: https://travis-ci.org/rgmining/script\n.. |wercker status| image:: https://app.wercker.com/status/f973cb1847c2c30e801fa4aa1fd417a6/s/master\n :target: https://app.wercker.com/project/byKey/f973cb1847c2c30e801fa4aa1fd417a6\n.. |Release| image:: https://img.shields.io/badge/release-0.6.1-brightgreen.svg\n :target: https://github.com/rgmining/script/releases/tag/0.6.1\n.. |Logo| image:: https://rgmining.github.io/script/_static/image.png\n :target: https://rgmining.github.io/script/", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/rgmining/script", "keywords": "", "license": "GPLv3", "maintainer": "", "maintainer_email": "", "name": "rgmining-script", "package_url": "https://pypi.org/project/rgmining-script/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/rgmining-script/", "project_urls": { "Homepage": "https://github.com/rgmining/script" }, "release_url": "https://pypi.org/project/rgmining-script/0.6.1/", "requires_dist": null, "requires_python": "", "summary": "Analyzing scripts for Review Graph Mining Project.", "version": "0.6.1" }, "last_serial": 2968772, "releases": { "0.5.0": [ { "comment_text": "", "digests": { "md5": "9c8d47cbed7d460f68bb8493e84d6160", "sha256": "a19f290a856e77cb677a26e30908f54790bfbf828a564517404d16a838ad81d0" }, "downloads": -1, "filename": "rgmining-script-0.5.0.tar.gz", "has_sig": false, "md5_digest": "9c8d47cbed7d460f68bb8493e84d6160", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 62880, "upload_time": "2017-01-27T08:01:32", "url": "https://files.pythonhosted.org/packages/f4/12/9c193cd2f560e43f055c53219a0ee335d66f7be2223049763f277ce810a0/rgmining-script-0.5.0.tar.gz" } ], "0.6.0": [ { "comment_text": "", "digests": { "md5": "5f9eced9f40e2409a1f4aca920eb0637", "sha256": "1350242ae27f6dc6b6d83a38573e19e2a0716e33acc96fbc8b57f193dc61af51" }, "downloads": -1, "filename": "rgmining-script-0.6.0.tar.gz", "has_sig": false, "md5_digest": "5f9eced9f40e2409a1f4aca920eb0637", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 63014, "upload_time": "2017-01-28T01:31:52", "url": "https://files.pythonhosted.org/packages/4c/db/0e998e2d154f0fea4c95ef639bd5cc559b9a0c48dae2f3f9bd025406d7b0/rgmining-script-0.6.0.tar.gz" } ], "0.6.1": [ { "comment_text": "", "digests": { "md5": "8d3617e1f7badb89f7ca25bc57d25556", "sha256": "5d77cad569e4257a7bf7ae5c4c2e90ac459e4059d25a34e355472f32cda85979" }, "downloads": -1, "filename": "rgmining-script-0.6.1.tar.gz", "has_sig": false, "md5_digest": "8d3617e1f7badb89f7ca25bc57d25556", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 64523, "upload_time": "2017-06-22T16:30:36", "url": "https://files.pythonhosted.org/packages/a0/9f/de949333e4e27d2e92a73c38d540b6b6dc18078f87247fafa0e6d18b6c03/rgmining-script-0.6.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "8d3617e1f7badb89f7ca25bc57d25556", "sha256": "5d77cad569e4257a7bf7ae5c4c2e90ac459e4059d25a34e355472f32cda85979" }, "downloads": -1, "filename": "rgmining-script-0.6.1.tar.gz", "has_sig": false, "md5_digest": "8d3617e1f7badb89f7ca25bc57d25556", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 64523, "upload_time": "2017-06-22T16:30:36", "url": "https://files.pythonhosted.org/packages/a0/9f/de949333e4e27d2e92a73c38d540b6b6dc18078f87247fafa0e6d18b6c03/rgmining-script-0.6.1.tar.gz" } ] }