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2017 | OriginalPaper | Chapter

Probabilistic Topic Modelling for Controlled Snowball Sampling in Citation Network Collection

Authors : Hennadii Dobrovolskyi, Nataliya Keberle, Olga Todoriko

Published in: Knowledge Engineering and Semantic Web

Publisher: Springer International Publishing

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Abstract

The paper presents a probabilistic topic model (PTM) application to citation network collection. Snowball sampling method is moderated with the selection of the most relevant papers by means of the PTM. The PTM used in the paper is modified to treat collections of short texts. It is constructed from the titles of seed papers collection united with the papers obtained through unrestricted snowball sampling. The objective of the research is to propose and to experimentally verify the approach of application of PTM of short text documents for improvement of a citation network collection. The preliminary analysis has shown that the method is robust: seed paper collection variations do not affect the most influencing papers subset in the collected citation network.

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Title: Probabilistic Topic Modelling for Controlled Snowball Sampling in Citation Network Collection
Authors: Hennadii Dobrovolskyi
Nataliya Keberle
Olga Todoriko
Publisher: Springer International Publishing
Book: Knowledge Engineering and Semantic Web
Print ISBN: 978-3-319-69547-1

Electronic ISBN: 978-3-319-69548-8

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-69548-8_7

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