Focus Group: Natural Language Processing and Information Retrieval (Prof. Ponzetto and Prof. Glavaš)

The NLP and IR group at DWS conducts research on methods for knowledge acquisition and natural language processing (NLP), as well as their application to support empirical research in (Computational) Social Sciences and (Digital) Humanities. In our work, we investigate a wide range of techniques for text understanding - ranging from representation learning and distributional semantics all the way through symbolic, entity-based approaches leveraging wide-coverage knowledge graphs - and apply these to a wide range of research topics such as such computational semantics, multilinguality, information retrieval and multimodal NLP, to name a few.

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 *  joint project with the AI group

Projects

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Publications

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Master and Bachelor Theses

This thesis should provide an in-depth overview of the various recurrent neural network models (fully recurrent networks, recursive networks, long...

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This thesis should provide an in-depth overview of the state-of-the-art methods for representing knowledge graphs and knowledge bases in the (i.e.,...

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Social network are of high interests, for many applications ranging from simple user profiling to user customized advertisement. In this thesis, we...

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Continuous emotions detection is a core aspect for many real application. In this work we will experiment with an existing interactive installation...

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The goal of this thesis would be to organize news from German news outlets in such a way to detect events and salient topics in the news. The...

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Convolutional neural networks have been shown to be very successful to various text classification tasks. The main shortcoming of CNNs used for text...

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Recently the DWS group released a huge repository of hypernymy relations the Web, the WebIsADb (http://webdatacommons.org/isadb/), containing a large...

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In this thesis we will build upon and extend an annotation tool to conduct a user study and better understand the requirements towards image...

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Object detection in images from news articles is a very challenging task. On the one hand, available training data for object detectors is only...

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Introduction/problem: Speculation/hedging/vagueness identification plays significant role in many applications, e.g. information extraction, machine...

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