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A Web Survey on the Use of Active Learning to Support Annotation of Text Data
Number of Authors: 2
2009 (English)In: Proceedings of Active Learning for Natural Language Processing (ALNLP-09), 2009, 1, , 4 p.45-48 p.Conference paper (Refereed)
Abstract [en]

As supervised machine learning methods for addressing tasks in natural language processing (NLP) prove increasingly viable, the focus of attention is naturally shifted towards the creation of training data. The manual annotation of corpora is a tedious and time consuming process. To obtain high-quality annotated data constitutes a bottleneck in machine learning for NLP today. Active learning is one way of easing the burden of annotation. This paper presents a first probe into the NLP research community concerning the nature of the annotation projects undertaken in general, and the use of active learning as annotation support in particular.

Place, publisher, year, edition, pages
2009, 1. , 4 p.45-48 p.
Keyword [en]
active learning, machine learning, survey, questionnaire
National Category
Computer and Information Science
URN: urn:nbn:se:ri:diva-23517OAI: diva2:1042593
Active Learning for Natural Language Processing (ALNLP-09), held in conjunction with HLT-NAACL 2009
Available from: 2016-10-31 Created: 2016-10-31

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Computer and Information Science

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