About: Integrating Prior Knowledge in Mixed Initiative Social Network Clustering

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Integrating Prior Knowledge in Mixed Initiative Social Network Clustering
Creator	Buono, Paolo Fekete, Jean-Daniel Pister, Alexis Plaisant, Catherine Valdivia, Paola
source	ArXiv
abstract	We propose a new paradigm---called PK-clustering---to help social scientists create meaningful clusters in social networks. Many clustering algorithms exist but most social scientists find them difficult to understand, and tools do not provide any guidance to choose algorithms, or to evaluate results taking into account the prior knowledge of the scientists. Our work introduces a new clustering paradigm and a visual analytics user interface that address this issue. It is based on a process that 1) captures the prior knowledge of the scientists as a set of incomplete clusters, 2) runs multiple clustering algorithms (similarly to clustering ensemble methods), 3) visualizes the results of all the algorithms ranked and summarized by how well each algorithm matches the prior knowledge, 5) evaluates the consensus between user-selected algorithms and 6) allows users to review details and iteratively update the acquired knowledge. We describe our paradigm using an initial functional prototype, then provide two examples of use and early feedback from social scientists. We believe our clustering paradigm offers a novel constructive method to iteratively build knowledge while avoiding being overly influenced by the results of often-randomly selected black-box clustering algorithms.
has issue date	2020-05-06(xsd:dateTime)
has license	arxiv
sha1sum (hex)	887e3081c628fb481a9270a91fea71d676b0a926
resource representing a document's title	Integrating Prior Knowledge in Mixed Initiative Social Network Clustering
resource representing a document's body	covid:887e3081c628fb481a9270a91fea71d676b0a926#body_text
is schema:about of	named entity 'ALGORITHMS' named entity 'SPECIFIED' named entity 'GROUP' named entity 'PRIOR' named entity 'SPECIFICATION' »more»

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