Final Report for the DFG-Project Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation- and Assistance-Systems. Gipp, B., Greiner-Petter, A., Schubotz, M., & Meuschke, N. Technical Report University of Goettingen, March, 2023. ![Final Report for the DFG-Project Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation- and Assistance-Systems [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
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Demo 1 Demo 2 doi abstract bibtex 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. To achieve this goal, the project addressed three main research challenges: (1) syntactic analysis of mathematical expressions, (2) semantic enrichment of mathematical expressions, and (3) evaluation using quality metrics and demonstrators. To make our research useful for the research community, we published tools that enable researchers to process mathematical expressions more effectively and efficiently. The project has made significant research contributions to various Mathematical Information Retrieval (MathIR) tasks and systems, including plagiarism detection and recommendation systems, search engines, the first mathematical type assistance system, math question answering and tutoring systems, automatic plausibility checks for mathematical expressions on Wikipedia, automatic computability of mathematical content via Computer Algebra Systems (CAS), and others. Although our project focused on MathIR tasks, its impact on other natural language research was significant, leading to a more extensive range of demonstrators than originally expected. Many of these demonstrators introduced novel applications, such as the tutoring system PhysWikiQuiz or LaCASt, which automatically verifies the correctness of math formulae on Wikipedia or the Digital Library of Mathematical Functions (DLMF) via commercial CAS. During the project, we published 29 peer-reviewed articles in international venues, including prestigious conferences like the Joint Conference on Digital Libraries (JCDL) and The Web Conference (WWW) (CORE rank A*), as well as journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (IF: 24.314) and Scientometrics (IF: 3.801). Our Wikipedia demonstrator was also featured in public media. Furthermore, we actively presented our contributions, especially demonstrators, to the research community in multiple workshops. This project has strengthened our international collaborations, particularly with colleagues at the National Institute of Standards and Technology (NIST) in the US and the National Institute of Informatics (NII) in Japan. Several subprojects were partially developed in course projects and theses at the Universities of Konstanz, Wuppertal, and Göttingen, exposing junior researchers to cutting-edge technologies and sensitizing students and researchers to the outstanding issues in MathIR technologies. We firmly believe that this project will have a lasting effect on following MathIR technologies. Several of the subprojects initiated as part of this grant are ongoing and motivating follow-up DFG projects, such as Analyzing Mathematics to Detect Disguised Academic Plagiarism (project no. 437179652).
@techreport{GippGSM23,
title = {Final {Report} for the {DFG}-{Project} {Methods} and {Tools} to {Advance} the {Retrieval} of {Mathematical} {Knowledge} from {Digital} {Libraries} for {Search}-, {Recommendation}- and {Assistance}-{Systems}},
copyright = {Creative Commons Attribution 4.0 International, Open Access},
url = {paper=https://zenodo.org/record/7924634/files/Gipp2023_DFG_Report_MathIR.pdf demo_1=https://lacast.wmflabs.org/ demo_2=https://physwikiquiz.wmflabs.org},
abstract = {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. To achieve this goal, the project addressed three main research challenges: (1) syntactic analysis of mathematical expressions, (2) semantic enrichment of mathematical expressions, and (3) evaluation using quality metrics and demonstrators. To make our research useful for the research community, we published tools that enable researchers to process mathematical expressions more effectively and efficiently. The project has made significant research contributions to various Mathematical Information Retrieval (MathIR) tasks and systems, including plagiarism detection and recommendation systems, search engines, the first mathematical type assistance system, math question answering and tutoring systems, automatic plausibility checks for mathematical expressions on Wikipedia, automatic computability of mathematical content via Computer Algebra Systems (CAS), and others. Although our project focused on MathIR tasks, its impact on other natural language research was significant, leading to a more extensive range of demonstrators than originally expected. Many of these demonstrators introduced novel applications, such as the tutoring system PhysWikiQuiz or LaCASt, which automatically verifies the correctness of math formulae on Wikipedia or the Digital Library of Mathematical Functions (DLMF) via commercial CAS. During the project, we published 29 peer-reviewed articles in international venues, including prestigious conferences like the Joint Conference on Digital Libraries (JCDL) and The Web Conference (WWW) (CORE rank A*), as well as journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (IF: 24.314) and Scientometrics (IF: 3.801). Our Wikipedia demonstrator was also featured in public media. Furthermore, we actively presented our contributions, especially demonstrators, to the research community in multiple workshops. This project has strengthened our international collaborations, particularly with colleagues at the National Institute of Standards and Technology (NIST) in the US and the National Institute of Informatics (NII) in Japan. Several subprojects were partially developed in course projects and theses at the Universities of Konstanz, Wuppertal, and Göttingen, exposing junior researchers to cutting-edge technologies and sensitizing students and researchers to the outstanding issues in MathIR technologies. We firmly believe that this project will have a lasting effect on following MathIR technologies. Several of the subprojects initiated as part of this grant are ongoing and motivating follow-up DFG projects, such as Analyzing Mathematics to Detect Disguised Academic Plagiarism (project no. 437179652).},
language = {en},
urldate = {2023-05-15},
institution = {University of Goettingen},
author = {Gipp, Bela and Greiner-Petter, André and Schubotz, Moritz and Meuschke, Norman},
month = mar,
year = {2023},
doi = {10.5281/ZENODO.7924634},
}
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