{"id":26482112,"url":"https://github.com/daandouwe/svd-doc2vec","last_synced_at":"2026-05-16T20:36:40.897Z","repository":{"id":78707296,"uuid":"148511950","full_name":"daandouwe/svd-doc2vec","owner":"daandouwe","description":"Turn documents into vectors by decomposing a PPMI cooccurence matrix.","archived":false,"fork":false,"pushed_at":"2018-09-13T14:51:47.000Z","size":136,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-20T04:01:42.559Z","etag":null,"topics":["doc2vec","ppmi","svd","wikitext"],"latest_commit_sha":null,"homepage":null,"language":"HTML","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/daandouwe.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-09-12T16:48:05.000Z","updated_at":"2021-10-11T11:41:35.000Z","dependencies_parsed_at":"2023-02-24T08:15:49.861Z","dependency_job_id":null,"html_url":"https://github.com/daandouwe/svd-doc2vec","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/daandouwe/svd-doc2vec","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daandouwe%2Fsvd-doc2vec","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daandouwe%2Fsvd-doc2vec/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daandouwe%2Fsvd-doc2vec/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daandouwe%2Fsvd-doc2vec/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/daandouwe","download_url":"https://codeload.github.com/daandouwe/svd-doc2vec/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daandouwe%2Fsvd-doc2vec/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33118125,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-16T18:38:32.183Z","status":"ssl_error","status_checked_at":"2026-05-16T18:38:29.903Z","response_time":115,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["doc2vec","ppmi","svd","wikitext"],"created_at":"2025-03-20T04:00:21.614Z","updated_at":"2026-05-16T20:36:40.893Z","avatar_url":"https://github.com/daandouwe.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Doc2vec with PPMI-SVD\nFactor a document-word cooccurence-matrix that is scaled with positive pointwise mutual information (PPMI) using singular value decomposition (SVD).\n\n## Setup\nWe use the [WikiText dataset](https://einstein.ai/research/the-wikitext-long-term-dependency-language-modeling-dataset).\n\nTo extract documents from WikiText and save as json file, run:\n```bash\nmkdir data\n./parse-wikitext.py wikitext-2-raw/wiki.train.raw data/wikitext-2-raw.docs.json\n```\n\n## Usage\nIn the project terminal, run\n```bash\nmkdir vec\n./main.py --data data/wikitext-2-raw.docs.json --outpath vec/wikitext-2-raw.vec.txt \\\n    --lower --num-words 1000 --dim 10\n```\nfor a quick demo. Plots are saved in the folder `plots`.\n\nTo rank the documents based on the vectors, use:\n```bash\n./rank.py vec/wikitext-2-raw.vec.txt \u003e wikitext-2-raw.ranking.txt\n```\n\n\n## Requirements\n```\nnumpy\nscipy\ntqdm\nmatplotlib\nsklearn\nbokeh\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaandouwe%2Fsvd-doc2vec","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaandouwe%2Fsvd-doc2vec","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaandouwe%2Fsvd-doc2vec/lists"}