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Mapper and Betti 0 Barcodes Applied to Random Indexing Word-Spaces - a First Survey
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This paper will introduce analytic methods for linguistic

data that is represented in forms of word-spaces constructed

from the random indexing model. The paper will present

two different methods; a visualisation method derived from

an algorithm called Mapper, and a word-space property

measure derived from Betti numbers. The methods will be

explained and thereafter implemented in order to demonstrate

their behaviour with a smaller set of linguistic data.

The implementations will constitute as a foundation for future


Place, publisher, year, edition, pages
2013. , 26 p.
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-142381OAI: diva2:700054
Available from: 2014-03-12 Created: 2014-03-03 Last updated: 2015-02-12

Open Access in DiVA

David Nilsson & Ariel Morell Ekgren(958 kB)567 downloads
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