Abstract
With more than 120.000 articles published annually in mathematical journals alone, mathematical search has often been touted as a killer application of computer-supported mathematics. But the artefacts of mathematics – e.g. mathematical documents, formulas, examples, algorithms, concrete data sets, or semantic web-style graph abstractions – that should be searched cover a variety of aspects. All are organized in complex ways and offer distinct challenges and techniques for search. Existing representation languages, the corresponding query languages and search systems usually concentrate on only one of these aspects. As a consequence, each system only partially covers the information retrieval needs of mathematical practitioners, and integrated solutions allowing multi-aspect queries are rare and basic.
We present an architecture for a generic multi-aspect search system and analyze the requirements on paradigmatic practical information retrieval needs.
The authors were supported by DFG grant RA-1872/3-1, KO 2428/13-1 OAF and EU grant Horizon 2020 ERI 676541 OpenDreamKit.
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Berčič, K., Kohlhase, M., Rabe, F. (2020). Towards a Heterogeneous Query Language for Mathematical Knowledge. In: Benzmüller, C., Miller, B. (eds) Intelligent Computer Mathematics. CICM 2020. Lecture Notes in Computer Science(), vol 12236. Springer, Cham. https://doi.org/10.1007/978-3-030-53518-6_3
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