Mapper and Betti 0 Barcodes Applied to Random Indexing Word-Spaces - a First Survey
David Nilsson, Ariel Ekgren · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2013
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 research.