[{"_1":2,"_191":-5,"_192":-5},"loaderData",{"_3":4,"_17":18,"_25":26,"_166":167},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7,"_13":14,"_15":16},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","theme","system","contrast","normal","routes/_layout",{"_19":-5,"_20":21,"_22":21,"_23":11,"_24":21},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","showHoneypotTrap","routes/_layout.r.$namespace.$reponame",{"_27":28,"_29":-5,"_30":11,"_31":11,"_32":33,"_34":35,"_36":-5,"_37":11,"_38":39,"_88":89,"_110":111,"_155":-5,"_156":11,"_157":21,"_158":11,"_159":-5,"_160":11,"_161":-5,"_162":163,"_164":112,"_165":-7},"canonicalUrl","https://hub.docker.com/r/liaad/kep/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","liaad","reponame","kep","cloudBuildSource","isAutobuildsAvailable","repo",{"_40":41,"_42":43,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":55,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":64,"_65":66,"_67":-5,"_68":62,"_69":70,"_71":11,"_72":33,"_73":74,"_79":11,"_80":81,"_85":33,"_86":87},"categories",[],"content_types",[44],"image","date_registered","2020-06-15T09:33:01.211216Z","description","Keyphrase Extraction Package","is_private","last_updated","2020-06-15T19:59:14.915197Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[56],"application/vnd.docker.container.image.v1+json","name","pull_count",314,"repository_type","star_count",0,"status",1,"status_description","active","source","collaborator_count","full_description","# KEP - Keyphrase Extraction Package\n\nKEP package (http://github.com/liaad/kep) here available as a docker image, enables one to extract keyphrases from documents (single or multiple documents) by applying a number of algorithms, the big majority of which provided by [pke](http://www.aclweb.org/anthology/C16-2015) an [open-source package](https://github.com/boudinfl/pke). Differently from PKE, we provide a ready to run code to extract keyphrases not only from a single document, but also in batch mode (i.e., several documents). More to the point, we consider 20 state-of-the-art datasets from which keyphrases may be extracted, and the corresponding dfs, lda and KEA pre-computed models (which contrasts with pke as only semeval-2010 models are made available). \n\n## List of Datasets\n\nKEP can extract keyphrases from 20 datasets:\n\n- 110-PT-BN-KP (110 docs; PT)\n- 500N-KPCrowd-v1.1 (500 docs; EN)\n- cacic (888 docs; ES)\n- citeulike180 (183 docs; EN)\n- fao30 (30 docs; EN)\n- fao780 (779 docs; EN)\n- Inspec (2000 docs; EN)\n- kdd (755 docs; EN)\n- Krapivin2009 (2304 docs; EN)\n- Nguyen2007 (209 docs; EN)\n- pak2018 (50 docs; PL)\n- PubMed (500 docs; EN)\n- Schutz2008 (1231 docs; EN)\n- SemEval2010 (243 docs; EN)\n- SemEval2017 (493 docs; EN)\n- theses100 (100 docs; EN)\n- wicc (1640 docs; ES)\n- wiki20 (20 docs; EN)\n- WikiNews (100 docs; FR)\n- www (1330 docs; EN)\n\n
\nNote however that more datasets can be added as long as they follow the coming structure:\n\n- keys: a folder that contains for each document a file with the corresponding keywords (ground-truth)\n- docsutf8: a folder that contains the documents text\n- lan.txt: a file that specifies the language of the document (e.g., EN). Used to load the stopwords\n\n## Keyphrase Extraction Algorithms\n\n\n### Unsupervised Algorithms\n#### Statistical Methods\n\n- TF.IDF. By PKE\n- RAKE (Ref: Rose S, Engel D, Cramer N, Cowley W (2010). [Automatic Keyword Extraction from Individual Documents](https://onlinelibrary.wiley.com/doi/abs/10.1002/9780470689646.ch1)). By PKE\n- KP-Miner (Ref: El-Beltagy S, Rafea A (2009). [KP-Miner: A Keyphrase Extraction System for English and Arabic Documents](https://www.sciencedirect.com/science/article/abs/pii/S0306437908000537). By PKE\n- YAKE! (Ref: Campos R, Mangaravite V, Pasquali A, Jorge A, Nunes C, Jatowt A (2020). [YAKE! Keyword Extraction from Single Documents using Multiple Local Features](https://www.sciencedirect.com/science/article/pii/S0020025519308588?via%3Dihub); (2018) [A Text Feature Based Automatic Keyword Extraction Method for Single Documents](https://link.springer.com/chapter/10.1007/978-3-319-76941-7_63); [Demo](http://yake.inesctec.pt))\n\n#### Graph-based Methods\n\n- TextRank (Ref: Mihalcea R, Tarau P (2004). [TextRank: Bringing Order into Texts](https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf)). By PKE\n- SingleRank (Ref: Wan X, Xiao J (2008). [Single Document Keyphrase Extraction Using Neighborhood Knowledge](https://pdfs.semanticscholar.org/8a99/634e0b418ee61c9bd81f61d334b80486dc53.pdf)). By PKE\n- TopicRank (Ref: Bougouin A, Boudin F, Daille B (2013). [TopicRank: Graph-Based Topic Ranking for Keyphrase Extraction](http://www.aclweb.org/anthology/I13-1062)). By PKE\n- TopicalPageRank (Ref: Sterckx L, Demeester T, Deleu J, Develder C (2015). [Topical Word Importance for Fast Keyphrase Extraction](https://core.ac.uk/download/pdf/55828317.pdf)). By PKE\n- PositionRank (Ref: Florescu C, Caragea C (2017). [PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents](http://people.cs.ksu.edu/~ccaragea/papers/acl17.pdf)). By PKE\n- MultipartiteRank (Ref: Boudin F (2018). [Unsupervised Keyphrase Extraction with Multipartite Graphs](http://www.aclweb.org/anthology/N18-2105)). By PKE\n\n### Supervised Algorithms\n- KEA (Ref:\tWitten I, Paynter G, Frank E, Gutwin C, Nevill-Manning C, (1999). [KEA: Practical Automatic Keyphrase Extraction](https://www.cs.waikato.ac.nz/ml/publications/2005/chap_Witten-et-al_Windows.pdf)). By PKE\n\n## Installing KEP on Docker\n### Install Docker\n\n#### Windows\nDocker for Windows requires 64bit Windows 10 Pro with Hyper-V available. \nIf you have this, then proceed to download here: (https://docs.docker.com/docker-for-windows/install/#download-docker-for-windows) and click on Get Docker for Windows (Stable)\n

\nIf your system does not meet the requirements to run Docker for Windows (e.g., 64bit Windows 10 Home), you can install Docker Toolbox, which uses Oracle Virtual Box instead of Hyper-V. In that case proceed to download here: (https://docs.docker.com/toolbox/overview/#ready-to-get-started) and click on Get Docker Toolbox for Windows\n

\n\n#### MAC\nDocker for Mac will launch only if all of these requirements (https://docs.docker.com/docker-for-mac/install/#what-to-know-before-you-install) are met.\nIf you have this, then proceed to download here: (https://docs.docker.com/docker-for-mac/install/#download-docker-for-mac) and click on Get Docker for Mac (Stable)\n

\nIf your system does not meet the requirements to run Docker for Mac, you can install Docker Toolbox, which uses Oracle Virtual Box instead of Hyper-V. In that case proceed to download here: (https://docs.docker.com/toolbox/overview/#ready-to-get-started) and click on Get Docker Toolbox for Mac\n

\n\n#### Linux\nProceed to download here: (https://docs.docker.com/engine/installation/#server)\n

\n\n#### Pull Image\nExecute the following command on your docker machine: \n``` bash\ndocker pull liaad/kep\n```\n\n### Run Image\nOn your docker machine run the following to launch the image: \n``` bash\ndocker run -p 9999:8888 --user root liaad/kep\n```\n\nThen go to your browser and type in the following url: \n``` bash\nhttp://:9999\n```\n\nwhere the IP may be the localhost or 192.168.99.100 if you are using a Docker Machine VM.\n \nYou will be required a token which you can find on your docker machine prompt. It will be something similar to this: http://eac214218126:8888/?token=ce459c2f581a5f56b90256aaa52a96e7e4b1705113a657e8. Copy paste the token (in this example, that would be: ce459c2f581a5f56b90256aaa52a96e7e4b1705113a657e8) to the browser, and voilá, you will have KEP package ready to run. Keep this token (for future references) or define a password.\n\n### Run Jupyter notebooks\nOnce you logged in, proceed by running the notebook that we have prepared for you.\n\n### Shutdown\nOnce you are done go to File - Shutdown.\n\n### Login again\nIf later on you decide to play with the same container, you should proceed as follows. The first thing to do is to get the container id:\n``` bash\ndocker ps -a\n```\n\nNext run the following commands:\n``` bash\ndocker start ContainerId\ndocker attach ContainerId (attach to a running container)\n```\n\nNothing happens in your docker machine, but you are now ready open your browser as you did before:\n``` bash\nhttp://:9999\n```\n\nHopefully, you have saved the token or defined a password. If that is not the case, then you should run the following command (before doing start/attach) to have access to your token:\n``` bash\ndocker exec -it jupyter notebook list\n```","has_starred","hub_user","immutable_tags_settings",{"_75":11,"_76":77},"enabled","rules",[78],".*","is_automated","permissions",{"_82":21,"_83":11,"_84":11},"read","write","admin","user","storage_size",1547166610,"orgData",{"_90":91,"_92":93,"_94":95,"_96":33,"_97":98,"_99":100,"_101":102,"_103":100,"_104":105,"_106":100,"_107":100,"_108":100,"_109":21},"id","e71eb7cf5c204f8396c446e46ead1d6b","uuid","e71eb7cf-5c20-4f83-96c4-46e46ead1d6b","type","organization","orgname","full_name","Laboratory of Artificial Intelligence and Decision Support","location","","company","INESC TEC","profile_url","date_joined","2019-02-12T22:16:19.501395Z","gravatar_url","gravatar_email","badge","is_active","recentTags",[112,149],{"_113":44,"_114":115,"_116":117,"_90":118,"_119":120,"_50":137,"_138":115,"_139":140,"_141":56,"_57":142,"_143":144,"_145":128,"_146":137,"_147":66,"_148":21},"content_type","creator",8890490,"full_size",1547140134,104992873,"images",[121],{"_122":123,"_124":125,"_126":100,"_127":128,"_129":130,"_131":132,"_133":100,"_134":-5,"_135":117,"_63":66,"_136":-5},"architecture","amd64","digest","sha256:a6905ffe6407e3967eee095d14f4f8b8ba3d6193f478a24a1320532dc56010d1","features","last_pulled","2026-10-03T23:24:29.195658311Z","last_pushed","2020-06-15T19:58:52Z","os","linux","os_features","os_version","size","variant","2020-06-15T19:59:12.24382Z","last_updater","last_updater_username","rncampos","media_type","latest","repository",9259730,"tag_last_pulled","tag_last_pushed","tag_status","v2",{"_113":44,"_114":115,"_116":117,"_90":150,"_119":151,"_50":153,"_138":115,"_139":140,"_141":56,"_57":154,"_143":144,"_145":128,"_146":153,"_147":66,"_148":21},104992879,[152],{"_122":123,"_124":125,"_126":100,"_127":128,"_129":130,"_131":132,"_133":100,"_134":-5,"_135":117,"_63":66,"_136":-5},"2020-06-15T19:59:14.601366Z","v1","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"selectedTag","attestationsUrl","routes/_layout.r.$namespace.$reponame.tags",{"_38":168,"_175":176,"_162":189,"_190":11},{"_40":169,"_42":170,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":171,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":64,"_65":66,"_67":-5,"_68":62,"_69":70,"_71":11,"_72":33,"_73":172,"_79":11,"_80":174,"_85":33,"_86":87},[],[44],[56],{"_75":11,"_76":173},[78],{"_82":21,"_83":11,"_84":11},"tags",{"_177":178,"_179":-5,"_180":-5,"_181":182},"count",2,"next","previous","results",[183,186],{"_113":44,"_114":115,"_116":117,"_90":150,"_119":184,"_50":153,"_138":115,"_139":140,"_141":56,"_57":154,"_143":144,"_145":128,"_146":153,"_147":66,"_148":21},[185],{"_122":123,"_124":125,"_126":100,"_127":128,"_129":130,"_131":132,"_133":100,"_134":-5,"_135":117,"_63":66,"_136":-5},{"_113":44,"_114":115,"_116":117,"_90":118,"_119":187,"_50":137,"_138":115,"_139":140,"_141":56,"_57":142,"_143":144,"_145":128,"_146":137,"_147":66,"_148":21},[188],{"_122":123,"_124":125,"_126":100,"_127":128,"_129":130,"_131":132,"_133":100,"_134":-5,"_135":117,"_63":66,"_136":-5},[],"canDeleteTags","actionData","errors"]

liaad/kep

Tags for liaad/kep