Using noun phrases extraction for the improvement of hybrid clustering with text- and citation-based components. The example of "Information Systems Research"

Bart Thijs, Wolfgang Glänzel, Martin S. Meyer

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

6 Citations (Scopus)

Abstract

The hybrid clustering approach combining lexical and link-based similarities suffered for a long time from the different properties of the underlying networks. We propose a method based on noun phrase extraction using natural language processing to improve the measurement of the lexical component. Term shingles of different length are created form each of the extracted noun phrases. Hybrid networks are built based on weighted combination of the two types of similarities with seven different weights. We conclude that removing all single term shingles provides the best results at the level of computational feasibility, comparability with bibliographic coupling and also in a community detection application.
Original languageEnglish
Title of host publicationProceedings of the Workshop Mining Scientific Papers: Computational Linguistics and Bibliometrics
Subtitle of host publication15th International Society of Scientometrics and Informetrics Conference (ISSI), Istanbul, Turkey
Pages28-33
Number of pages6
Volume1384
Publication statusPublished - 1 Jun 2015

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