Abstract
In automated health services based on text and voice interfaces, there is a need to be able to understand what the user is talking about, and what is the attitude of the user towards a subject. Typical machine learning methods for text analysis require a lot of annotated data for the training. This is often a problem in addressing specific and possibly very personal health care needs. In this paper, we propose an active learning algorithm for the training of a text classifier for a conversational therapy application in the area of health behavior change. A new active learning algorithm, Query by Embedded Committee (QBEC), is proposed in the paper. The methods are particularly suitable for the text classification task in a dynamic environment and give a good performance with realistic test data.
Original language | English |
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Title of host publication | Artificial Intelligence in Health - 1st International Workshop, AIH 2018, Revised Selected Papers |
Editors | Pau Herrero, Andrew Koster, Fernando Koch, Isabelle Bichindaritz |
Publisher | Springer-Verlag London Ltd. |
Pages | 48-58 |
Number of pages | 11 |
ISBN (Print) | 9783030127374 |
DOIs | |
Publication status | Published - 2019 |
Externally published | Yes |
Event | 1st International Workshop on Artificial Intelligence in Health - Stockholm, Sweden Duration: 13 Jul 2018 → 14 Jul 2018 Conference number: 1 |
Publication series
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11326 LNAI |
ISSN | 0302-9743 |
Workshop
Workshop | 1st International Workshop on Artificial Intelligence in Health |
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Abbreviated title | AIH 2018 |
Country/Territory | Sweden |
City | Stockholm |
Period | 13/07/18 → 14/07/18 |