DocumentCode :
2250930
Title :
Towards automatically categorizing mathematical knowledge
Author :
Grabowski, Adam ; Schwarzweller, Christoph
Author_Institution :
Inst. of Inf., Univ. of Bialystok, Białystok, Poland
fYear :
2012
fDate :
9-12 Sept. 2012
Firstpage :
63
Lastpage :
68
Abstract :
Clearly, there is no definitive standard for categorizing information contained in mathematical papers. Even if AMS Mathematics Subject Classification was important for mathematicians for years, nowadays we can observe growing popularity of other schemes, e.g. arXiv categories. On the other hand, in the era of digital information storing one can expect from the process of classification to be more or less automatic. Furthermore, generic categorization can be done inside the search engine. At different level, the distinction between such classical tagging items as lemma, proposition, theorem etc. had the aim of showing importance of proven facts. Here the automatization is much harder, or, to be more precise, the results obtained can be far from the original tagging given by the author. In the paper we point out some problems and thoughts concerned with the categorization of mathematical knowledge, illustrating some of them by examples taken from the Mizar Mathematical Library, large machine-checked repository of mathematical facts.
Keywords :
classification; information storage; knowledge management; mathematics computing; search engines; AMS mathematics subject classification; Mizar Mathematical Library; automatic mathematical knowledge categorization; automatization; classical tagging items; digital information storage; information categorization; large machine-checked repository; mathematical facts; mathematical papers; mathematicians; search engine; Algebra; Complexity theory; Dictionaries; Encyclopedias; Lattices; Libraries;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on
Conference_Location :
Wroclaw
Print_ISBN :
978-1-4673-0708-6
Electronic_ISBN :
978-83-60810-51-4
Type :
conf
Filename :
6354423
Link To Document :
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