Feature Extraction for Polish Language Named Entities Recognition in Intelligent Office Assistant

Date
2022-01-04
Authors
Denisiuk, Aleksander
Ganzha, Maria
Wasielewska-Michniewska, Katarzyna
Paprzycki, Marcin
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The purpose of this contribution is to present a feature extractor that was designed as a part of a Named Entity Recognition (NER) system, which is to be used in a Robotic Process Automation application with a self-learning ability. The NER system has a screen of the user interface as its input, and tries to recognize and categorize all the named entities that can be located within this screen. The set of features that can be extracted from the input, is discussed in the article. The local context features appear to be very important in the considered problem. Experiments show that the entities are recognized with a rate that is satisfactory from the business perspective.
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Data, Text, and Web Mining for Business Analytics, decision trees, named entity recognition, robot process automation, semantic context
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10 pages
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Proceedings of the 55th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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