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Found 7 papers, 6 papers with code
Discovery and Recognition of Formula Concepts using Machine Learning
Our long-term goal is to generalize citation-based IR methods and apply this generalized method to both classical references and mathematical concepts.
Collaborative and AI-aided Exam Question Generation using Wikidata in Education
To address this need, we propose a multilingual Wikimedia framework that allows for collaborative worldwide teacher knowledge engineering and subsequent AI-aided question generation, test, and correction.
Mining Mathematical Documents for Question Answering via Unsupervised Formula Labeling
In this paper, we aim to bridge the gap by presenting data mining methods and benchmark results to employ Mathematical Entity Linking (MathEL) and Unsupervised Formula Labeling (UFL) for semantic formula search and mathematical question answering (MathQA) on the arXiv preprint repository, Wikipedia, and Wikidata, which is part of the Wikimedia ecosystem of free knowledge.
Towards Explaining STEM Document Classification using Mathematical Entity Linking
The results indicate that mathematical entities have the potential to provide high explainability as they are a crucial part of a STEM document.
AutoMSC: Automatic Assignment of Mathematics Subject Classification Labels
Moreover, we find that the method's confidence score allows for reducing the effort by 86% compared to the manual coarse-grained classification effort while maintaining a precision of 81% for automatically classified articles.
Classification and Clustering of arXiv Documents, Sections, and Abstracts, Comparing Encodings of Natural and Mathematical Language
In this paper, we show how selecting and combining encodings of natural and mathematical language affect classification and clustering of documents with mathematical content.
Introducing MathQA -- A Math-Aware Question Answering System
This formulae originate from the knowledge-base Wikidata.
