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Now showing 1 - 4 of 4
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    zbMATH Open: API Solutions and Research Challenges
    (Aachen, Germany : RWTH Aachen, 2021) Petrera, Matteo; Trautwein, Dennis; Beckenbach, Isabel; Ehsani, Dariush; MĂ¼ller, Fabian; Teschke, Olaf; Gipp, Bela; Schubotz, Moritz; Balke, Wolf-Tilo; de Waard, Anita; Fu, Yuanxi; Hua, Bolin; Schneider, Jodi; Song, Ningyuan; Wang, Xiaoguang
    We present zbMATH Open, the most comprehensive collection of reviews and bibliographic metadata of scholarly literature in mathematics. Besides our website zbMATH.org which is openly accessible since the beginning of this year, we provide API endpoints to offer our data. APIs improve interoperability with others, i.e., digital libraries, and allow using our data for research purposes. In this article, we (1) illustrate the current and future overview of the services offered by zbMATH; (2) present the initial version of the zbMATH links API; (3) analyze potentials and limitations of the links API based on the example of the NIST Digital Library of Mathematical Functions; (4) and finally, present thezbMATHOpen dataset as a research resource and discuss connected open research problems.
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    Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra Systems
    (Berlin ; Heidelberg : Springer, 2022) Greiner-Petter, André; Cohl, Howard S.; Youssef, Abdou; Schubotz, Moritz; Trost, Avi; Dey, Rajen; Aizawa, Akiko; Gipp, Bela; Fisman, Dana; Rosu, Grigore
    Digital mathematical libraries assemble the knowledge of years of mathematical research. Numerous disciplines (e.g., physics, engineering, pure and applied mathematics) rely heavily on compendia gathered findings. Likewise, modern research applications rely more and more on computational solutions, which are often calculated and verified by computer algebra systems. Hence, the correctness, accuracy, and reliability of both digital mathematical libraries and computer algebra systems is a crucial attribute for modern research. In this paper, we present a novel approach to verify a digital mathematical library and two computer algebra systems with one another by converting mathematical expressions from one system to the other. We use our previously developed conversion tool (referred to as ) to translate formulae from the NIST Digital Library of Mathematical Functions to the computer algebra systems Maple and Mathematica. The contributions of our presented work are as follows: (1) we present the most comprehensive verification of computer algebra systems and digital mathematical libraries with one another; (2) we significantly enhance the performance of the underlying translator in terms of coverage and accuracy; and (3) we provide open access to translations for Maple and Mathematica of the formulae in the NIST Digital Library of Mathematical Functions.
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    Detecting Cross-Language Plagiarism using Open Knowledge Graphs
    (Aachen, Germany : RWTH Aachen, 2021) StegmĂ¼ller, Johannes; Bauer-Marquart, Fabian; Meuschke, Norman; Ruas, Terry; Schubotz, Moritz; Gipp, Bela; Zhang, Chengzhi; Mayr, Philipp; Lu, Wie; Zhang, Yi
    Identifying cross-language plagiarism is challenging, especially for distant language pairs and sense-for-sense translations. We introduce the new multilingual retrieval model Cross-Language Ontology-Based Similarity Analysis (CL-OSA) for this task. CL-OSA represents documents as entity vectors obtained from the open knowledge graph Wikidata. Opposed to other methods, CL-OSA does not require computationally expensive machine translation, nor pre-training using comparable or parallel corpora. It reliably disambiguates homonyms and scales to allow its application toWebscale document collections. We show that CL-OSA outperforms state-of-the-art methods for retrieving candidate documents from five large, topically diverse test corpora that include distant language pairs like Japanese-English. For identifying cross-language plagiarism at the character level, CL-OSA primarily improves the detection of sense-for-sense translations. For these challenging cases, CL-OSA’s performance in terms of the well-established PlagDet score exceeds that of the best competitor by more than factor two. The code and data of our study are openly available.
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    Mathematics in Wikidata
    (Aachen, Germany : RWTH Aachen, 2021) Scharpf, Philipp; Schubotz, Moritz; Gipp, Bela; Kaffee, Lucie-Aimée; Razniewski, Simon; Hogan, Aidan
    Documents from Science, Technology, Engineering, and Mathematics (STEM) disciplines usually contain a signicant amount of mathematical formulae alongside text. Some Mathematical Information Retrieval (MathIR) systems, e.g., Mathematical Question Answering (MathQA), exploit knowledge from Wikidata. Therefore, the mathematical information needs to be stored in items. In the last years, there have been efforts to define several properties and seed formulae together with their constituting identifiers into Wikidata. This paper summarizes the current state, challenges, and discussions related to this endeavor. Furthermore, some data mining methods (supervised formula annotation and concept retrieval) and applications (question answering and classification explainability) of the mathematical information are outlined. Finally, we discuss community feedback and issues related to integrating Mathematical Entity Linking (MathEL) into Wikidata and Wikipedia, which was rejected in 33% and 12% of the test cases, for Wikidata and Wikipedia respectively. Our long-term goal is to populate Wikidata, such that it can serve a variety of automated math reasoning tasks and AI systems.