Jakob Jelencic
ABSTRACT
Modelling multilingual text data over time is a challenging task. This PhD is focused on semantic representation of domain specific short to mid length time stamped textual data. The proposed method is evaluated on the example of job postings, where we are modeling demand on IT jobs. More specifically, we addresses the following three problems: unifying the representation of multilingual text data; clustering similar textual data; using the proposed semantic representation to model and predict future demand of jobs. This works starts with a problem statement, followed by a description of the proposed approach and methodology and is concluded with an overview of the first results and summary of the ongoing research.
- David M Blei, Andrew Y Ng, and Michael I Jordan. 2003. Latent dirichlet allocation. Journal of machine Learning research 3, Jan (2003), 993–1022.Google Scholar
Digital Library
- Janez Brank, Gregor Leban, and Marko Grobelnik. 2017. Annotating documents with relevant Wikipedia concepts. Proceedings of SiKDD(2017).Google Scholar
- Jelenčič, Grobelnik, and Mladenić. 2021. Computationally Effective Domain-tailored TextEmbeddings. (2021).Google Scholar
- Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems.Google Scholar
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