A high-quality content analysis is essential for retrieval functionalities but the manual extraction of key phrases and classification is expensive. Natural language processing provides a framework to automatize the process. Here, a machine-based approach for the content analysis of mathematical texts is described. A prototype for key phrase extraction and classification of mathematical texts is presented.
%0 Journal Article
%1 schoneberg_delivermath_2013
%A Schöneberg, Ulf
%A Sperber, Wolfram
%D 2013
%K terminologieextraktion
%T The DeLiVerMATH project : text analysis in mathematics
%U http://arxiv.org/abs/1306.6944
%X A high-quality content analysis is essential for retrieval functionalities but the manual extraction of key phrases and classification is expensive. Natural language processing provides a framework to automatize the process. Here, a machine-based approach for the content analysis of mathematical texts is described. A prototype for key phrase extraction and classification of mathematical texts is presented.
@article{schoneberg_delivermath_2013,
abstract = {A high-quality content analysis is essential for retrieval functionalities but the manual extraction of key phrases and classification is expensive. Natural language processing provides a framework to automatize the process. Here, a machine-based approach for the content analysis of mathematical texts is described. A prototype for key phrase extraction and classification of mathematical texts is presented.},
added-at = {2018-11-04T17:02:36.000+0100},
author = {Schöneberg, Ulf and Sperber, Wolfram},
biburl = {https://www.bibsonomy.org/bibtex/2ee6cc2c85db348a757a8cf8ac9117eb6/lepsky},
interhash = {812cc6b2b785df765b1ebfd04c5d652c},
intrahash = {ee6cc2c85db348a757a8cf8ac9117eb6},
keywords = {terminologieextraktion},
timestamp = {2018-11-04T17:02:36.000+0100},
title = {The {DeLiVerMATH} project : text analysis in mathematics},
url = {http://arxiv.org/abs/1306.6944},
year = 2013
}