{"id":13765837,"url":"https://github.com/fursovia/geometric_embedding","last_synced_at":"2025-05-10T21:32:11.395Z","repository":{"id":75885738,"uuid":"160752132","full_name":"fursovia/geometric_embedding","owner":"fursovia","description":"\"Zero-Training Sentence Embedding via Orthogonal Basis\" paper implementation","archived":false,"fork":false,"pushed_at":"2018-12-23T08:46:01.000Z","size":164544,"stargazers_count":19,"open_issues_count":0,"forks_count":3,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-04-20T00:36:45.700Z","etag":null,"topics":["embeddings","nlp"],"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/fursovia.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}},"created_at":"2018-12-07T01:05:42.000Z","updated_at":"2020-10-12T12:01:00.000Z","dependencies_parsed_at":"2023-03-06T22:45:13.842Z","dependency_job_id":null,"html_url":"https://github.com/fursovia/geometric_embedding","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/fursovia%2Fgeometric_embedding","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fursovia%2Fgeometric_embedding/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fursovia%2Fgeometric_embedding/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fursovia%2Fgeometric_embedding/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fursovia","download_url":"https://codeload.github.com/fursovia/geometric_embedding/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":213825910,"owners_count":15644056,"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":["embeddings","nlp"],"created_at":"2024-08-03T16:00:47.009Z","updated_at":"2024-08-03T16:03:23.550Z","avatar_url":"https://github.com/fursovia.png","language":"Python","funding_links":[],"categories":["Pooling Methods"],"sub_categories":[],"readme":"## Geometric Embedding Algorithm (GEM)\n\nThis is an implementation of Geometric Embedding Algorithm, a simple and robust non-parameterized approach for building sentence\nrepresentations. See the [paper](https://openreview.net/pdf?id=rJedbn0ctQ) for more details.\n\nThe work is done as a project for [NLA course](http://nla.skoltech.ru/) at Skoltech.\n\n### Example\n\n```python\nfrom gem import SentenceEmbedder\nfrom embeddings import get_embedding_matrix\n\nsentences = [\"We come from the land of the ice and snow\",\n            \"From the midnight sun where the hot springs blow\"]\n            \nembedding_matrix, vocab = get_embedding_matrix('glove.6B.300d.txt')\nembedder = SentenceEmbedder(sentences, embedding_matrix, vocab)\n\nembedded_sentences = embedder.gem(window_size=3, sigma_power=3)\n```\n\n### Data used\n\n* [GloVe embeddings](https://nlp.stanford.edu/projects/glove/)\n* [LexVec embeddings](https://github.com/alexandres/lexvec)\n\n\n### Team\n\n* [Alexey Bokhovkin](https://github.com/alexeybokhovkin)\n* [Eugenia Cheskidova](https://github.com/fogside)\n* [Ivan Fursov](https://github.com/fursovia)\n* [Ruslan Rakhimov](https://github.com/rakhimovv)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffursovia%2Fgeometric_embedding","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffursovia%2Fgeometric_embedding","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffursovia%2Fgeometric_embedding/lists"}