{"id":13463680,"url":"https://github.com/natsheh/sensim","last_synced_at":"2025-09-29T06:31:51.220Z","repository":{"id":42409190,"uuid":"44107266","full_name":"natsheh/sensim","owner":"natsheh","description":"Sentence Similarity Estimator (SenSim)","archived":false,"fork":false,"pushed_at":"2018-11-18T12:18:20.000Z","size":32281,"stargazers_count":15,"open_issues_count":4,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-09T18:40:44.021Z","etag":null,"topics":["nlp-machine-learning","nlu","paper","semantic-textual-similarity","sentence-similarity-estimator","text-mining"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/natsheh.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":"2015-10-12T12:53:18.000Z","updated_at":"2022-02-11T01:44:48.000Z","dependencies_parsed_at":"2022-09-20T20:03:46.367Z","dependency_job_id":null,"html_url":"https://github.com/natsheh/sensim","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natsheh%2Fsensim","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natsheh%2Fsensim/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natsheh%2Fsensim/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natsheh%2Fsensim/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/natsheh","download_url":"https://codeload.github.com/natsheh/sensim/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234597578,"owners_count":18857980,"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":["nlp-machine-learning","nlu","paper","semantic-textual-similarity","sentence-similarity-estimator","text-mining"],"created_at":"2024-07-31T14:00:26.339Z","updated_at":"2025-09-29T06:31:44.672Z","avatar_url":"https://github.com/natsheh.png","language":"Python","funding_links":[],"categories":["Data Science"],"sub_categories":[],"readme":"# SenSim\n\nSentence Similarity Estimator (SenSim)\n\nDependancies\n------------\n\tThis repository currently supports Python 2.7\n\tFor the used default values in sts.py/sts_light.py, you need the following:\n\tsklearn==0.18\n\tpolyglot==16.07.04 \n\t\tDependencies: (python-numpy libicu-dev)\n\t\t(to use in ubuntu/debian) sudo apt-get install python-numpy libicu-dev\n\tbeard==0.2\n\tdigify==0.2\n\tenchant==1.6.8\n\tspacy==0.100.5\n\t\tNeeded models: python -m spacy.en.download glove\n\nUsage to reproduce the results in the paper\n-------------------------------------------\n\tAfter cloning the repositpry, use sts.py with its documented arguments\n\n\nUsage to reproduce the results against the STS Benchmark\n--------------------------------------------------------\n\tAfter cloning the repositpry, use sts_benchmark.py with its default param\n\nAccess to the paper\n-------------------\n\thttp://www.aclweb.org/anthology/S17-2013\n\nPlease cite using the following BibTex entry\n--------------------------------------------\n\n```\n@InProceedings{alnatsheh-EtAl:2017:SemEval,\n  author    = {Al-Natsheh, Hussein T.  and  Martinet, Lucie  and  Muhlenbach, Fabrice  and  ZIGHED, Djamel Abdelkader},\n  title     = {UdL at SemEval-2017 Task 1: Semantic Textual Similarity Estimation of English Sentence Pairs Using Regression Model over Pairwise Features},\n  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},\n  month     = {August},\n  year      = {2017},\n  address   = {Vancouver, Canada},\n  publisher = {Association for Computational Linguistics},\n  pages     = {115--119},\n  abstract  = {This paper describes the model UdL we proposed to solve the semantic textual\n\tsimilarity task of SemEval 2017 workshop. The track we participated in was\n\testimating the semantics relatedness of a given set of sentence pairs in\n\tEnglish. The best run out of three submitted runs of our model achieved a\n\tPearson correlation score of 0.8004 compared to a hidden human annotation of\n\t250~pairs. We used random forest ensemble learning to map an expandable set of\n\textracted pairwise features into a semantic similarity estimated value bounded\n\tbetween 0 and 5. Most of these features were calculated using word embedding\n\tvectors similarity to align Part of Speech (PoS) and Name Entities (NE) tagged\n\ttokens of each sentence pair. Among other pairwise features, we experimented a\n\tclassical tf-idf weighted Bag of Words (BoW) vector model but with\n\tcharacter-based range of n-grams instead of words. This sentence vector\n\tBoW-based feature gave a relatively high importance value percentage in the\n\tfeature importances analysis of the ensemble learning.},\n  url       = {http://www.aclweb.org/anthology/S17-2013}\n}\n\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatsheh%2Fsensim","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnatsheh%2Fsensim","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatsheh%2Fsensim/lists"}