Which Scores to Predict in Sentence Regression for Text Summarization?

no code implementations • NAACL 2018 • Markus Zopf, Eneldo Loza Menc{\'\i}a, Johannes F{\"u}rnkranz

The task of automatic text summarization is to generate a short text that summarizes the most important information in a given set of documents.

regression Sentence +1

Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization

no code implementations • COLING 2016 • Markus Zopf, Eneldo Loza Menc{\'\i}a, Johannes F{\"u}rnkranz

In this paper, we propose a combination of sequential clustering and contextual importance measures to identify important sentences in a stream of documents in a timely manner.

Clustering

What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation

no code implementations • COLING 2016 • Fabian Hirschmann, Jinseok Nam, Johannes F{\"u}rnkranz

Traditional machine translation systems often require heavy feature engineering and the combination of multiple techniques for solving different subproblems.

Feature Engineering Machine Translation +2

Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization

no code implementations • CONLL 2016 • Markus Zopf, Eneldo Loza Menc{\'\i}a, Johannes F{\"u}rnkranz

Document Summarization Multi-Document Summarization