Part‐of‐speech tagging
Wiley Interdisciplinary Reviews Computational StatisticsPublished 30 September 2011
Angel R. Martinez
Citations38
SJR quartileQ1
SJR score1.45
SNIP3.11
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TL;DR
A brief state‐of-the‐art account on part‐of‐speech (POS) tagging is presented, finding rule‐based and stochastic methods have been successful, attaining accuracies of 96–97%.
Abstract
Abstract Presented here is a brief state‐of‐the‐art account on part‐of‐speech (POS) tagging. POS tagging is an essential preprocessing task for many natural language processing goals and applications. Some POS tagging approaches make use of annotated corpora to train computational models to perform the task with minimal human intervention. Rule‐based and stochastic methods have been successful, attaining accuracies of 96–97%. Representative approaches of these two methodologies are discussed. WIREs Comp Stat 2012, 4:107–113. doi: 10.1002/wics.195 This article is categorized under: Software for Computational Statistics > Artificial Intelligence and Expert Systems Data: Types and Structure > Text Data Statistical Learning and Exploratory Methods of the Data Sciences > Text Mining
Keywords
Computer Science
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