Search Results for author: Wahed Hemati

Found 9 papers, 2 papers with code

Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages

1 code implementation5 Aug 2020 Alexander Mehler, Wahed Hemati, Pascal Welke, Maxim Konca, Tolga Uslu

From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading.

The Frankfurt Latin Lexicon: From Morphological Expansion and Word Embeddings to SemioGraphs

1 code implementation21 May 2020 Alexander Mehler, Bernhard Jussen, Tim Geelhaar, Alexander Henlein, Giuseppe Abrami, Daniel Baumartz, Tolga Uslu, Wahed Hemati

In this article we present the Frankfurt Latin Lexicon (FLL), a lexical resource for Medieval Latin that is used both for the lemmatization of Latin texts and for the post-editing of lemmatizations.

Lemmatization Word Embeddings

Voting for POS tagging of Latin texts: Using the flair of FLAIR to better Ensemble Classifiers by Example of Latin

no code implementations LREC 2020 Manuel Stoeckel, Alex Henlein, Wahed Hemati, Alex Mehler, er

Since most of the available Latin word embeddings were trained on either few or inaccurate data, we trained several embeddings on better data in the first step.

Lemmatization Part-Of-Speech Tagging +3

From Topic Networks to Distributed Cognitive Maps: Zipfian Topic Universes in the Area of Volunteered Geographic Information

no code implementations4 Feb 2020 Alexander Mehler, Rüdiger Gleim, Regina Gaitsch, Wahed Hemati, Tolga Uslu

To this end, we explore Volunteered Geographic Information (VGI) to model texts addressing places at the level of cities or regions with the help of so-called topic networks.

When Specialization Helps: Using Pooled Contextualized Embeddings to Detect Chemical and Biomedical Entities in Spanish

no code implementations WS 2019 Manuel Stoeckel, Wahed Hemati, Alexander Mehler

The recognition of pharmacological substances, compounds and proteins is an essential preliminary work for the recognition of relations between chemicals and other biomedically relevant units.

Word Embeddings

TextImager: a Distributed UIMA-based System for NLP

no code implementations COLING 2016 Wahed Hemati, Tolga Uslu, Alex Mehler, er

More and more disciplines require NLP tools for performing automatic text analyses on various levels of linguistic resolution.

Sentiment Analysis Text Classification

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