106 citations · 394 across the 16 of their papers we have counts for
4 papers · 1 filter
Principal Components of the Meaning
Neslihan Suzen, Alexander Gorban, Jeremy Levesley +1
In this paper we argue that (lexical) meaning in science can be represented in a 13 dimension Meaning Space. This space is constructed using principal component analysis (singular…
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data
Sergey E. Golovenkin, Jonathan Bac, Alexander Chervov +5
Large observational clinical datasets become increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considere…
Fractional norms and quasinorms do not help to overcome the curse of dimensionality
Evgeny M. Mirkes, Jeza Allohibi, Alexander N. Gorban
The curse of dimensionality causes the well-known and widely discussed problems for machine learning methods. There is a hypothesis that using of the Manhattan distance and even fr…
Informational Space of Meaning for Scientific Texts
Neslihan Suzen, Evgeny M. Mirkes, Alexander N. Gorban
In Natural Language Processing, automatic extracting the meaning of texts constitutes an important problem. Our focus is the computational analysis of meaning of short scientific t…