ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings

no code implementations • SEMEVAL 2018 • Lena Hettinger, Alex Dallmann, er, Albin Zehe, Thomas Niebler, Andreas Hotho

In this paper we describe our system for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1. 1) and noisy data (subtask 1. 2).

Classification General Classification +4

ClaiRE at SemEval-2018 Task 7 - Extended Version

no code implementations • 16 Apr 2018 • Lena Hettinger, Alexander Dallmann, Albin Zehe, Thomas Niebler, Andreas Hotho

Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75. 11% for the first subtask and 81. 44% for the second.

General Classification

Learning Semantic Relatedness From Human Feedback Using Metric Learning

no code implementations • 21 May 2017 • Thomas Niebler, Martin Becker, Christian Pölitz, Andreas Hotho

To solve this, we propose to utilize a metric learning approach to improve existing semantic relatedness measures by learning from additional information, such as explicit human feedback.

Metric Learning Word Embeddings