{"id":13588960,"url":"https://github.com/davidadamojr/TextRank","last_synced_at":"2025-04-08T07:31:32.845Z","repository":{"id":12077552,"uuid":"14665007","full_name":"davidadamojr/TextRank","owner":"davidadamojr","description":"Python implementation of TextRank algorithm for automatic keyword extraction and summarization using Levenshtein distance as relation between text units. This project is based on the paper \"TextRank: Bringing Order into Text\" by Rada Mihalcea and Paul Tarau. https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf","archived":false,"fork":false,"pushed_at":"2022-05-05T15:12:55.000Z","size":41,"stargazers_count":765,"open_issues_count":7,"forks_count":226,"subscribers_count":41,"default_branch":"master","last_synced_at":"2024-11-06T08:43:27.619Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/davidadamojr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2013-11-24T16:56:40.000Z","updated_at":"2024-10-15T01:36:40.000Z","dependencies_parsed_at":"2022-09-09T22:51:35.694Z","dependency_job_id":null,"html_url":"https://github.com/davidadamojr/TextRank","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidadamojr%2FTextRank","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidadamojr%2FTextRank/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidadamojr%2FTextRank/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/davidadamojr%2FTextRank/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/davidadamojr","download_url":"https://codeload.github.com/davidadamojr/TextRank/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247796148,"owners_count":20997521,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-01T16:00:15.722Z","updated_at":"2025-04-08T07:31:32.521Z","avatar_url":"https://github.com/davidadamojr.png","language":"Python","readme":"## TextRank\nThis is a python implementation of TextRank for automatic keyword and sentence extraction (summarization) as done in https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf. However, this implementation uses Levenshtein Distance as the relation between text units.\n\nThis implementation carries out automatic keyword and sentence extraction on 10 articles gotten from http://theonion.com\n\n - 100 word summary\n - Number of keywords extracted is relative to the size of the text (a third of the number of nodes in the graph)\n - Adjacent keywords in the text are concatenated into keyphrases\n\n### Usage\nTo install the library run the `setup.py` module located in the repository's root directory.  Alternatively, if you have access to pip you may install the library directly from github:\n\n```\npip install git+https://github.com/davidadamojr/TextRank.git\n```\n\nUse of the library requires downloading nltk resources.  Use the `textrank initialize` command to fetch the required data.  Once the data has finished downloading you may execute the following commands against the library:\n\n```\ntextrank extract_summary \u003cfilename\u003e\ntextrank extract_phrases \u003cfilename\u003e\n```\n\n### Contributing\nInstall the library as \"editable\" within a virtual environment.\n\n```\npip install -e .\n```\n\n\n### Dependencies\nDependencies are installed automatically with pip but can be installed serparately.\n\n* Networkx - https://pypi.python.org/pypi/networkx/\n* NLTK 3.0 - https://pypi.python.org/pypi/nltk/3.2.2\n* Numpy - https://pypi.python.org/pypi/numpy\n* Click - https://pypi.python.org/pypi/click\n\n\n","funding_links":[],"categories":["PYTHON","📖 Natural Language Processing (NLP)","Python"],"sub_categories":["Tools"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdavidadamojr%2FTextRank","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdavidadamojr%2FTextRank","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdavidadamojr%2FTextRank/lists"}