Math-aware Similarity of Papers in Digital Mathematics Libraries
| Authors | |
|---|---|
| Year of publication | 2014 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | The exploratory, semantic similarity searching is becoming widespread in digital libraries, and math ones are no exception. For working mathematicians and their use of digital mathematical libraries (DML) as the Czech Digital Mathematics Library DML-CZ or European Digital Mathematics Library (EuDML) we have designed and implemented math-aware similarity computation framework based on leading edge topic modelling techniques implemented by Gensim software package. Studies on the classification of math papers done for DML-CZ have been tested and deployed in EuDML, where for given paper ten most semantically similar papers are computed and shown. In the latest experiments we are evaluating several possible representations of mathematical formulae to get the semantically similar papers. Quality of similarity is measured by comparation to the similarity matrix induced from the Mathematical Subject Classifications every paper is marked up by. In the talk we will report a) about the evaluation of the similarities computed by several different methods, b) on the experience from 20 months of deployment in EuDML and more than 5 years in DML-CZ, c) about the importance of representing formulae even for paper similarity computations, d) on setting up Gensim for the math-aware use in DML projects. |
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