Aline Villavicencio, Helena de Medeiros Caseli, A. Machado
{"title":"Identification of Multiword Expressions in Technical Domains: Investigating Statistical and Alignment-Based Approaches","authors":"Aline Villavicencio, Helena de Medeiros Caseli, A. Machado","doi":"10.1109/STIL.2009.33","DOIUrl":null,"url":null,"abstract":"Multiword Expressions (MWEs) are one of the stumbling blocks for more precise Natural Language Processing (NLP) systems. The lack of coverage of MWEs in resources can impact negatively on the performance of tasks and applications, and can lead to loss of information or communication errors; especially in technical domains where MWE are frequent. This paper investigates some approaches to the identification of MWEs in technical corpora based on: association measures, part-of-speech and lexical alignment information. We examine the influence of some factors on their performance such as sources of information for identification and evaluation. While the association measures emphasize recall, the alignment method focuses on precision.","PeriodicalId":265848,"journal":{"name":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STIL.2009.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Multiword Expressions (MWEs) are one of the stumbling blocks for more precise Natural Language Processing (NLP) systems. The lack of coverage of MWEs in resources can impact negatively on the performance of tasks and applications, and can lead to loss of information or communication errors; especially in technical domains where MWE are frequent. This paper investigates some approaches to the identification of MWEs in technical corpora based on: association measures, part-of-speech and lexical alignment information. We examine the influence of some factors on their performance such as sources of information for identification and evaluation. While the association measures emphasize recall, the alignment method focuses on precision.