Search Results for author: André Greiner-Petter

Found 8 papers, 1 papers with code

Towards Grounding of Formulae

no code implementations EMNLP (sdp) 2020 Takuto Asakura, André Greiner-Petter, Akiko Aizawa, Yusuke Miyao

Our results indicate that it is worthwhile to grow the techniques for the proposed task to contribute to the further progress of mathematical language processing.

Information Retrieval Retrieval

TEIMMA: The First Content Reuse Annotator for Text, Images, and Math

1 code implementation22 May 2023 Ankit Satpute, André Greiner-Petter, Moritz Schubotz, Norman Meuschke, Akiko Aizawa, Olaf Teschke, Bela Gipp

This demo paper presents the first tool to annotate the reuse of text, images, and mathematical formulae in a document pair -- TEIMMA.

Math

Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation-, and Assistance-Systems

no code implementations12 May 2023 Bela Gipp, André Greiner-Petter, Moritz Schubotz, Norman Meuschke

This project investigated new approaches and technologies to enhance the accessibility of mathematical content and its semantic information for a broad range of information retrieval applications.

Information Retrieval Retrieval

Semantic Preserving Bijective Mappings of Mathematical Formulae between Document Preparation Systems and Computer Algebra Systems

no code implementations17 Sep 2021 Howard S. Cohl, Moritz Schubotz, Abdou Youssef, André Greiner-Petter, Jürgen Gerhard, Bonita V. Saunders, Marjorie A. ~McClain

Using LaTeX, LaTeXML, and tools generated for use in the National Institute of Standards (NIST) Digital Library of Mathematical Functions, semantically enhanced mathematical LaTeX markup (semantic LaTeX) is achieved by using a semantic macro set.

Math

Mathematical Formulae in Wikimedia Projects 2020

no code implementations20 Mar 2020 Moritz Schubotz, André Greiner-Petter, Norman Meuschke, Olaf Teschke, Bela Gipp

This poster summarizes our contributions to Wikimedia's processing pipeline for mathematical formulae.

Why Machines Cannot Learn Mathematics, Yet

no code implementations20 May 2019 André Greiner-Petter, Terry Ruas, Moritz Schubotz, Akiko Aizawa, William Grosky, Bela Gipp

Nowadays, Machine Learning (ML) is seen as the universal solution to improve the effectiveness of information retrieval (IR) methods.

BIG-bench Machine Learning Information Retrieval +1

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