Thursday, 30th of January 2020, 12:00 – 1:00

Cross-DomainText Classification

SR1, ICT Building,
Technikerstraße 21a, 6020 Innsbruck

Benjamin Murauer
Researcher at DBIS group, University of Innsbruck


  Text classification problems are usually solved by providing training data to machine learning algorithms which than predict the outcome on test data. Ideally, the training and testing data are as similar as possible, without overlapping. Whenever this is no longer the case and training and testing data are different in some dimension, a problem is called a cross-domain text classification problem. These dimensions range from different topics to languages, and they impact on classification problems in various ways. In this talk I will present different difficulties and solutions, while focussing on the specific classification task of authorship attribution. 

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