Modeling Text Data Over Time - Example on Job Postings

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.