Search Results for author: Andreas Spitz

Found 14 papers, 7 papers with code

Mind Your Bias: A Critical Review of Bias Detection Methods for Contextual Language Models

1 code implementation15 Nov 2022 Silke Husse, Andreas Spitz

The awareness and mitigation of biases are of fundamental importance for the fair and transparent use of contextual language models, yet they crucially depend on the accurate detection of biases as a precursor.

Bias Detection Word Embeddings

Collaborative and AI-aided Exam Question Generation using Wikidata in Education

1 code implementation15 Nov 2022 Philipp Scharpf, Moritz Schubotz, Andreas Spitz, Andre Greiner-Petter, Bela Gipp

To address this need, we propose a multilingual Wikimedia framework that allows for collaborative worldwide teacher knowledge engineering and subsequent AI-aided question generation, test, and correction.

Question Generation Question-Generation

United States Politicians' Tone Became More Negative with 2016 Primary Campaigns

1 code implementation17 Jul 2022 Jonathan Külz, Andreas Spitz, Ahmad Abu-Akel, Stephan Günnemann, Robert West

There is a widespread belief that the tone of US political language has become more negative recently, in particular when Donald Trump entered politics.

Quote Erat Demonstrandum: A Web Interface for Exploring the Quotebank Corpus

no code implementations7 Jul 2022 Vuk Vuković, Akhil Arora, Huan-Cheng Chang, Andreas Spitz, Robert West

The use of attributed quotes is the most direct and least filtered pathway of information propagation in news.

Strong Heuristics for Named Entity Linking

1 code implementation NAACL (ACL) 2022 Marko Čuljak, Andreas Spitz, Robert West, Akhil Arora

Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods.

Entity Linking

IM-META: Influence Maximization Using Node Metadata in Networks With Unknown Topology

no code implementations5 Jun 2021 Cong Tran, Won-Yong Shin, Andreas Spitz

Since the structure of complex networks is often unknown, we may identify the most influential seed nodes by exploring only a part of the underlying network, given a small budget for node queries.

DeepNC: Deep Generative Network Completion

1 code implementation17 Jul 2019 Cong Tran, Won-Yong Shin, Andreas Spitz, Michael Gertz

In this paper, we present DeepNC, a novel method for inferring the missing parts of a network based on a deep generative model of graphs.

Link Prediction

TopExNet: Entity-Centric Network Topic Exploration in News Streams

no code implementations29 May 2019 Andreas Spitz, Satya Almasian, Michael Gertz

The recent introduction of entity-centric implicit network representations of unstructured text offers novel ways for exploring entity relations in document collections and streams efficiently and interactively.

Retrieving Multi-Entity Associations: An Evaluation of Combination Modes for Word Embeddings

no code implementations22 May 2019 Gloria Feher, Andreas Spitz, Michael Gertz

Word embeddings have gained significant attention as learnable representations of semantic relations between words, and have been shown to improve upon the results of traditional word representations.

Retrieval Word Embeddings

Word Embeddings for Entity-annotated Texts

1 code implementation6 Feb 2019 Satya Almasian, Andreas Spitz, Michael Gertz

We discuss two distinct approaches to the generation of such embeddings, namely the training of state-of-the-art embeddings on raw-text and annotated versions of the corpus, as well as node embeddings of a co-occurrence graph representation of the annotated corpus.

Clustering Entity Embeddings +4

Community Detection in Partially Observable Social Networks

no code implementations30 Dec 2017 Cong Tran, Won-Yong Shin, Andreas Spitz

The discovery of community structures in social networks has gained significant attention since it is a fundamental problem in understanding the networks' topology and functions.

Community Detection

HeidelPlace: An Extensible Framework for Geoparsing

no code implementations EMNLP 2017 Ludwig Richter, Johanna Gei{\ss}, Andreas Spitz, Michael Gertz

Geographic information extraction from textual data sources, called geoparsing, is a key task in text processing and central to subsequent spatial analysis approaches.

Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding

1 code implementation11 Aug 2017 Erich Schubert, Andreas Spitz, Michael Weiler, Johanna Geiß, Michael Gertz

We then select keywords based on their significance and construct the word cloud based on the derived affinity.

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