Search Results for author: Johannes Hellrich

Found 13 papers, 5 papers with code

Continuous Quality Control and Advanced Text Segment Annotation with WAT-SL 2.0

1 code implementation WS 2019 Christina Lohr, Johannes Kiesel, Stephanie Luther, Johannes Hellrich, Tobias Kolditz, Benno Stein, Udo Hahn

Today{'}s widely used annotation tools were designed for annotating typically short textual mentions of entities or relations, making their interface cumbersome to use for long(er) stretches of text, e. g, sentences running over several lines in a document.

The Influence of Down-Sampling Strategies on SVD Word Embedding Stability

no code implementations WS 2019 Johannes Hellrich, Bernd Kampe, Udo Hahn

The stability of word embedding algorithms, i. e., the consistency of the word representations they reveal when trained repeatedly on the same data set, has recently raised concerns.

Word Embeddings

A Method for Human-Interpretable Paraphrasticality Prediction

no code implementations COLING 2018 Maria Moritz, Johannes Hellrich, Sven B{\"u}chel

However, even as research in the field of plagiarism detection is constantly improving, heavily modified or paraphrased text is still challenging for current methodologies.

Machine Translation text similarity +1

JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena

no code implementations COLING 2018 Johannes Hellrich, Sven Buechel, Udo Hahn

We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and lexical emotions assembled from five large diachronic text corpora.

Sentiment Analysis Word Embeddings

JeSemE: A Website for Exploring Diachronic Changes in Word Meaning and Emotion

2 code implementations11 Jul 2018 Johannes Hellrich, Sven Buechel, Udo Hahn

We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and lexical emotions assembled from five large diachronic text corpora.

Modeling Word Emotion in Historical Language: Quantity Beats Supposed Stability in Seed Word Selection

no code implementations WS 2019 Johannes Hellrich, Sven Buechel, Udo Hahn

To understand historical texts, we must be aware that language -- including the emotional connotation attached to words -- changes over time.

Feelings from the Past---Adapting Affective Lexicons for Historical Emotion Analysis

no code implementations WS 2016 Sven Buechel, Johannes Hellrich, Udo Hahn

We here describe a novel methodology for measuring affective language in historical text by expanding an affective lexicon and jointly adapting it to prior language stages.

Emotion Recognition Word Embeddings

Bad Company---Neighborhoods in Neural Embedding Spaces Considered Harmful

1 code implementation COLING 2016 Johannes Hellrich, Udo Hahn

We assess the reliability and accuracy of (neural) word embeddings for both modern and historical English and German.

Word Embeddings

UIMA-Based JCoRe 2.0 Goes GitHub and Maven Central ― State-of-the-Art Software Resource Engineering and Distribution of NLP Pipelines

no code implementations LREC 2016 Udo Hahn, Franz Matthies, Erik Faessler, Johannes Hellrich

We introduce JCoRe 2. 0, the relaunch of a UIMA-based open software repository for full-scale natural language processing originating from the Jena University Language {\&} Information Engineering (JULIE) Lab.

Management

Disclose Models, Hide the Data - How to Make Use of Confidential Corpora without Seeing Sensitive Raw Data

no code implementations LREC 2014 Erik Faessler, Johannes Hellrich, Udo Hahn

Confidential corpora from the medical, enterprise, security or intelligence domains often contain sensitive raw data which lead to severe restrictions as far as the public accessibility and distribution of such language resources are concerned.

POS POS Tagging +1

Collaboratively Annotating Multilingual Parallel Corpora in the Biomedical Domain---some MANTRAs

no code implementations LREC 2014 Johannes Hellrich, Simon Clematide, Udo Hahn, Dietrich Rebholz-Schuhmann

The coverage of multilingual biomedical resources is high for the English language, yet sparse for non-English languages―an observation which holds for seemingly well-resourced, yet still dramatically low-resourced ones such as Spanish, French or German but even more so for really under-resourced ones such as Dutch.

Named Entity Recognition (NER) Translation

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