{"title":"Acronym Expansion Via Hidden Markov Models","authors":"K. Taghva, Lakshmi Vyas","doi":"10.1109/ICSEng.2011.29","DOIUrl":null,"url":null,"abstract":"In this paper, we report on design and implementation of a Hidden Markov Model (HMM) to extract acronyms and their expansions. We also report on the training of this HMM with Maximum Likelihood Estimation (MLE) algorithm using a set of examples. Finally, we report on our testing using standard recall and precision. The HMM achieves a recall and precision of 98% and 92% respectively.","PeriodicalId":387483,"journal":{"name":"2011 21st International Conference on Systems Engineering","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 21st International Conference on Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEng.2011.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we report on design and implementation of a Hidden Markov Model (HMM) to extract acronyms and their expansions. We also report on the training of this HMM with Maximum Likelihood Estimation (MLE) algorithm using a set of examples. Finally, we report on our testing using standard recall and precision. The HMM achieves a recall and precision of 98% and 92% respectively.