{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/atr4s-toolkit-with-state-of-the-art-automatic","title":"ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala","arxiv_id":"1611.07804","date":"2016-11-23","proceeding":null,"authors":["N. Astrakhantsev"],"abstract":"Automatically recognized terminology is widely used for various\ndomain-specific texts processing tasks, such as machine translation,\ninformation retrieval or sentiment analysis. However, there is still no\nagreement on which methods are best suited for particular settings and,\nmoreover, there is no reliable comparison of already developed methods. We\nbelieve that one of the main reasons is the lack of state-of-the-art methods\nimplementations, which are usually non-trivial to recreate. In order to address\nthese issues, we present ATR4S, an open-source software written in Scala that\ncomprises more than 15 methods for automatic terminology recognition (ATR) and\nimplements the whole pipeline from text document preprocessing, to term\ncandidates collection, term candidates scoring, and finally, term candidates\nranking. It is highly scalable, modular and configurable tool with support of\nautomatic caching. We also compare 10 state-of-the-art methods on 7 open\ndatasets by average precision and processing time. Experimental comparison\nreveals that no single method demonstrates best average precision for all\ndatasets and that other available tools for ATR do not contain the best\nmethods.","url_abs":"http://arxiv.org/abs/1611.07804v1","url_pdf":"http://arxiv.org/pdf/1611.07804v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"atr4s-toolkit-with-state-of-the-art-automatic","repo_url":"https://github.com/ispras/atr4s","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"atr4s-toolkit-with-state-of-the-art-automatic","repo_url":"https://github.com/effectiff-tech/homogeneity-scripts","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"atr4s-toolkit-with-state-of-the-art-automatic","repo_url":"https://github.com/kevinlu1248/pyate","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}