Using Discourse Context to Interpret Object-Denoting Mathematical Expressions

Wolska, Magdalena; Grigore, Mihai; Kohlhase, Michael

  • Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011, Publisher: Masaryk University Press(Brno, Czech Republic), page 85-101

Abstract

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We present a method for determining the context-dependent denotation of simple object-denoting mathematical expressions in mathematical documents. Our approach relies on estimating the similarity between the linguistic context within which the given expression occurs and a set of terms from a flat domain taxonomy of mathematical concepts; one of 7 head concepts dominating a set of terms with highest similarity score to the symbol’s context is assigned as the symbol’s interpretation. The taxonomy we used was constructed semi-automatically by combining structural and lexical information from the Cambridge Mathematics Thesaurus and the Mathematics Subject Classification. The context information taken into account in the statistical similarity calculation includes lexical features of the discourse immediately adjacent to the given expression as well as global discourse. In particular, as part of the latter we include the lexical context of structurally similar expressions throughout the document and that of the symbol’s declaration statement if one can be found in the document. Our approach has been evaluated on a gold standard manually annotated by experts, achieving 66% precision.

How to cite

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Wolska, Magdalena, Grigore, Mihai, and Kohlhase, Michael. "Using Discourse Context to Interpret Object-Denoting Mathematical Expressions." Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011. Brno, Czech Republic: Masaryk University Press, 2011. 85-101. <http://eudml.org/doc/221783>.

@inProceedings{Wolska2011,
abstract = {We present a method for determining the context-dependent denotation of simple object-denoting mathematical expressions in mathematical documents. Our approach relies on estimating the similarity between the linguistic context within which the given expression occurs and a set of terms from a flat domain taxonomy of mathematical concepts; one of 7 head concepts dominating a set of terms with highest similarity score to the symbol’s context is assigned as the symbol’s interpretation. The taxonomy we used was constructed semi-automatically by combining structural and lexical information from the Cambridge Mathematics Thesaurus and the Mathematics Subject Classification. The context information taken into account in the statistical similarity calculation includes lexical features of the discourse immediately adjacent to the given expression as well as global discourse. In particular, as part of the latter we include the lexical context of structurally similar expressions throughout the document and that of the symbol’s declaration statement if one can be found in the document. Our approach has been evaluated on a gold standard manually annotated by experts, achieving 66% precision.},
author = {Wolska, Magdalena, Grigore, Mihai, Kohlhase, Michael},
booktitle = {Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011},
location = {Brno, Czech Republic},
pages = {85-101},
publisher = {Masaryk University Press},
title = {Using Discourse Context to Interpret Object-Denoting Mathematical Expressions},
url = {http://eudml.org/doc/221783},
year = {2011},
}

TY - CLSWK
AU - Wolska, Magdalena
AU - Grigore, Mihai
AU - Kohlhase, Michael
TI - Using Discourse Context to Interpret Object-Denoting Mathematical Expressions
T2 - Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011
PY - 2011
CY - Brno, Czech Republic
PB - Masaryk University Press
SP - 85
EP - 101
AB - We present a method for determining the context-dependent denotation of simple object-denoting mathematical expressions in mathematical documents. Our approach relies on estimating the similarity between the linguistic context within which the given expression occurs and a set of terms from a flat domain taxonomy of mathematical concepts; one of 7 head concepts dominating a set of terms with highest similarity score to the symbol’s context is assigned as the symbol’s interpretation. The taxonomy we used was constructed semi-automatically by combining structural and lexical information from the Cambridge Mathematics Thesaurus and the Mathematics Subject Classification. The context information taken into account in the statistical similarity calculation includes lexical features of the discourse immediately adjacent to the given expression as well as global discourse. In particular, as part of the latter we include the lexical context of structurally similar expressions throughout the document and that of the symbol’s declaration statement if one can be found in the document. Our approach has been evaluated on a gold standard manually annotated by experts, achieving 66% precision.
UR - http://eudml.org/doc/221783
ER -

References

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