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ORCIDTobias Eljasik-Swoboda
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2020 – today
- 2021
[b1]Tobias Eljasik-Swoboda:
Bootstrapping Explainable Text Categorization in Emergent Knowledge-Domains. University of Hagen, Germany, 2021- 2020
- [c10]Tobias Eljasik-Swoboda, Wilhelm Demuth:
Leveraging Clustering and Natural Language Processing to Overcome Variety Issues in Log Management. ICAART (2) 2020: 281-288
2010 – 2019
- 2019
- [c9]Tobias Eljasik-Swoboda, Felix Engel, Michael Kaufmann, Matthias L. Hemmje:
Word Embedding Based Extension of Text Categorization Topic Taxonomies. CERC 2019: 15-26 - [c8]Tobias Eljasik-Swoboda, Felix Engel
, Matthias L. Hemmje:
Using Topic Specific Features for Argument Stance Recognition. DATA 2019: 13-22 - [c7]Tobias Eljasik-Swoboda, Christian Rathgeber, Rainer Hasenauer:
Assessing Technology Readiness for Artificial Intelligence and Machine Learning based Innovations. DATA 2019: 281-288 - 2018
- [c6]Tobias Eljasik-Swoboda, Michael Kaufmann, Matthias L. Hemmje:
No Target Function Classifier - Fast Unsupervised Text Categorization using Semantic Spaces. DATA 2018: 35-46 - [c5]Christian Nawroth, Felix Engel, Tobias Eljasik-Swoboda, Matthias L. Hemmje:
Towards Enabling Emerging Named Entity Recognition as a Clinical Information and Argumentation Support. DATA 2018: 47-55 - 2017
- [c4]Michael Kaufmann, Tobias Eljasik-Swoboda, Christian Nawroth, Kevin Berwind, Marco X. Bornschlegl, Matthias L. Hemmje:
Modeling and Qualitative Evaluation of a Management Canvas for Big Data Applications. DATA 2017: 149-156 - 2016
- [c3]Tobias Swoboda, Christian Nawroth, Michael Kaufmann, Matthias L. Hemmje:
Toward Interactive Visualization of Results from Domain-Specific Text Analytics. BDA@AVI 2016: 75-87 - [c2]Tobias Swoboda, Michael A. Kaufmann, Matthias L. Hemmje:
Toward Cloud-based Classification and Annotation Support. CLOSER (2) 2016: 131-137 - [c1]Tobias Swoboda, Matthias L. Hemmje, Mihai Dascalu, Stefan Trausan-Matu:
Combining Taxonomies using Word2vec. DocEng 2016: 131-134
Coauthor Index
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