{"id":16271499,"url":"https://github.com/shreyaskarnik/pubmedlda","last_synced_at":"2025-09-22T02:33:10.351Z","repository":{"id":1565196,"uuid":"1989537","full_name":"shreyaskarnik/PubMedLDA","owner":"shreyaskarnik","description":"Making it easy to perform LDA on PubMed abstracts.","archived":false,"fork":false,"pushed_at":"2013-06-01T02:03:54.000Z","size":123,"stargazers_count":5,"open_issues_count":2,"forks_count":2,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-05T03:19:37.576Z","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/shreyaskarnik.png","metadata":{"files":{"readme":"README","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":"2011-07-03T00:02:10.000Z","updated_at":"2020-07-07T17:47:37.000Z","dependencies_parsed_at":"2022-08-26T21:53:09.093Z","dependency_job_id":null,"html_url":"https://github.com/shreyaskarnik/PubMedLDA","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/shreyaskarnik%2FPubMedLDA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shreyaskarnik%2FPubMedLDA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shreyaskarnik%2FPubMedLDA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shreyaskarnik%2FPubMedLDA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/shreyaskarnik","download_url":"https://codeload.github.com/shreyaskarnik/PubMedLDA/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":233663788,"owners_count":18710721,"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":"2024-10-10T18:13:42.256Z","updated_at":"2025-09-22T02:33:05.089Z","avatar_url":"https://github.com/shreyaskarnik.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"This is code for performing topic modeling on PubMed abstracts. \nDepends on package gensim and nltk.\nThe package contains two parts:\n1. Retrieve PubMed abstracts using the script getpmAbstracts.py\nUsage: usage:python getpmAbstracts.py -q [query] -o [output] -s [flag for steming]\n\nOptions:\n  -h, --help            show this help message and exit\n  -q QUERY, --query=QUERY\n                        Enter the PubMed query (PubMed style queries\n                        supported)\n  -o OFILE, --output=OFILE\n                        Enter the output file name to store result\n  -s, --stem            To stem result\n2. Once you have the PubMed abstracts in a file run LDA over them:\n\nUsage: python gensim_lda_pubmed.py -i [inputfile] -k [number of topics to extract] -v [verbose output FALSE by default] -t [TRUE/ FALSE for TFIDF weights] -r [return topics per document TRUE/FALSE (default FALSE)]\n\nOptions:\n  -h, --help            show this help message and exit\n  -i IFILE, --inputfile=IFILE\n                        Enter the file containing PubMed abstracts\n  -k NTOP, --numtopics=NTOP\n                        Number of topics\n  -t TFIDF, --tfidf=TFIDF\n                        TFIDF weignting (default TRUE)\n  -v VERBOSE            Verbose Output TRUE/FALSE (default FALSE)\n  -r FIT                Return topics per document TRUE/FALSE (default FALSE)\n\nAll the code in this project is under Creative Commons License. \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshreyaskarnik%2Fpubmedlda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshreyaskarnik%2Fpubmedlda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshreyaskarnik%2Fpubmedlda/lists"}