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has title::Mathematical Entity Recognition System
status: ongoing
Master: project within::Artificial Intelligence, Intelligent Systems
Student name: student name::Arash Parnia
Dates
Start start date:=March 01 2018
End end date:=August 31 2018
Supervision
Supervisor: Stefan Schlobach
Company: has company::Elsevier
Thesis: has thesis::Media:Thesis.pdf
Poster: has poster::Media:Posternaam.pdf

Signature supervisor



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Abstract

   Mathematical Entities capture the intent of the author in a symbolic and formalized way. Conventions in a scientific field often dictate the use of a mathematical entity. Authors often include a list of mathematical entities within their documents. We have used these lists to automatically annotate mathematical entities that appear within the text. What separates a mathematical entity from a regular word is the context in which they appear. Using this context as well as syntactic features of our entities we have developed various classification methods to recognize Named Mathematical Entities from scientific texts.