Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yinon Nachshon"'
Publikováno v:
Applied Network Science, Vol 7, Iss 1, Pp 1-25 (2022)
Abstract Centrality, in some sense, captures the extent to which a vertex controls the flow of information in a network. Here, we propose Local Detour Centrality as a novel centrality-based betweenness measure that captures the extent to which a vert
Externí odkaz:
https://doaj.org/article/ac6c6ccc307e4783bf44b68beceb218d
Publikováno v:
Axioms, Vol 11, Iss 9, p 486 (2022)
Temporal information plays a central role in shaping the structure of a network. In this paper, we consider the impact of an object on network structure over time. More specifically, we use a novel object-based dynamic measure to reflect the extent t
Externí odkaz:
https://doaj.org/article/607749b0c1f94cc0be2664fbd4faa592
Publikováno v:
Symmetry, Vol 14, Iss 8, p 1737 (2022)
Building on a modified version of the Haantjes path-based curvature, this article offers a novel measure that considers the direction of a stream of associations in a semantic network and estimates the extent to which any single association attracts
Externí odkaz:
https://doaj.org/article/a7b07416433b42bd898fa13effb39e88
In this article, we hypothesize that a metric underlies similarity within an active “patch” of a semantic space, meaning the subset of the semantic space to which attention is directed at a given moment and whose metric and content change constan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b3771b487ff22aebb00596318569f15
https://doi.org/10.31234/osf.io/fhkq8
https://doi.org/10.31234/osf.io/fhkq8
We introduce a novel model of similarity. Following previous models, we espouse the metric approach, namely, (dis)similarity between objects is represented as distance. Unlike previous models, we incorporate a distinction between a long term memory (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c402c592d670dce46091f450241f141d
https://doi.org/10.31234/osf.io/fyd4q
https://doi.org/10.31234/osf.io/fyd4q