{"id":27290540,"url":"https://github.com/jbochi/facts","last_synced_at":"2025-04-11T21:29:00.929Z","repository":{"id":57501040,"uuid":"99372815","full_name":"jbochi/facts","owner":"jbochi","description":"Matrix Factorization based recsys in Golang. Because facts are more important than ever","archived":false,"fork":false,"pushed_at":"2018-02-22T20:45:36.000Z","size":11,"stargazers_count":34,"open_issues_count":1,"forks_count":4,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-06-20T02:12:10.712Z","etag":null,"topics":["implicit","implicit-feedback","matrix-factorization","recommender-system"],"latest_commit_sha":null,"homepage":null,"language":"Go","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jbochi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-08-04T19:12:42.000Z","updated_at":"2024-04-26T11:39:44.000Z","dependencies_parsed_at":"2022-09-14T19:41:44.316Z","dependency_job_id":null,"html_url":"https://github.com/jbochi/facts","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/jbochi%2Ffacts","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbochi%2Ffacts/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbochi%2Ffacts/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jbochi%2Ffacts/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jbochi","download_url":"https://codeload.github.com/jbochi/facts/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248482579,"owners_count":21111355,"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":["implicit","implicit-feedback","matrix-factorization","recommender-system"],"created_at":"2025-04-11T21:29:00.482Z","updated_at":"2025-04-11T21:29:00.912Z","avatar_url":"https://github.com/jbochi.png","language":"Go","readme":"# facts\n\n[![Build Status](https://travis-ci.org/jbochi/facts.svg?branch=master)](https://travis-ci.org/jbochi/facts)\n\nMatrix Factorization based recommender system in Go. Because **facts** are more important than ever.\n\nThis project provides a `vectormodel` package that can be used to serve real time recommendations. First of all, you will need to train a model to get document embeddings or latent **fact**ors. I highly recommend the [implicit](https://github.com/benfred/implicit) library for that. Once you have the documents as a map of `int` ids to arrays of `float64`, you can create the vector model by calling:\n\n`model, err := NewVectorModel(documents map[int][]float64, confidence, regularization float64)`\n\nAnd to generate recommendations call `.Recommend` with a set of items the user has seen:\n\n`recs := model.Recommend(seenDocs *map[int]bool, n int)`\n\nNote that user vectors are not required. Matter of fact, you can use this to recommend documents to users that were *not* in the training set. The recommendations will be computed very efficiently (probably \u003c1ms, depends on your model size) in real time.\n\nCheck out the [demo](https://github-recs.appspot.com/) for a complete example that recommends GitHub repositories.\n\nDemo source code is available here: https://github.com/jbochi/github-recs\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjbochi%2Ffacts","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjbochi%2Ffacts","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjbochi%2Ffacts/lists"}