{"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/topicmodel4j-a-java-package-for-topic-models","title":"TopicModel4J: A Java Package for Topic Models","arxiv_id":"2010.14707","date":"2020-10-28","proceeding":null,"authors":["Yang Qian","Yuanchun Jiang","Yidong Chai","Yezheng Liu","Jiansha Sun"],"abstract":"Topic models provide a flexible and principled framework for exploring hidden structure in high-dimensional co-occurrence data and are commonly used natural language processing (NLP) of text. In this paper, we design and implement a Java package, TopicModel4J, which contains 13 kinds of representative algorithms for fitting topic models. The TopicModel4J in the Java programming environment provides an easy-to-use interface for data analysts to run the algorithms, and allow to easily input and output data. In addition, this package provides a few unstructured text preprocessing techniques, such as splitting textual data into words, lowercasing the words, preforming lemmatization and removing the useless characters, URLs and stop words.","url_abs":"https://arxiv.org/abs/2010.14707v1","url_pdf":"https://arxiv.org/pdf/2010.14707v1.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":"topicmodel4j-a-java-package-for-topic-models","repo_url":"https://github.com/soberqian/TopicModel4J","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"lemmatization","task_name":"Lemmatization"},{"task_slug":"topic-models","task_name":"Topic Models"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}