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Analysis of institutional authors

Rosso, PAuthor

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October 31, 2024
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Silhouette + Attraction: A Simple and Effective Method for Text Clustering

Publicated to: Natural Language Engineering. 22 (5): 687-726 - 2016-01-01 22(5), DOI: 10.1017/S1351324915000273

Authors:

Errecalde, Marcelo; Cagnina, Leticia; Rosso ., Paolo
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Affiliations

Univ Nacl San Luis, LIDIC - Author
Univ Politecn Valencia, NLE Lab, PRHLT Res Ctr - Author

Abstract

This article presents silhouette-attraction (Sil-Att), a simple and effective method for text clustering, which is based on two main concepts: the silhouette coefficient and the idea of attraction. The combination of both principles allows us to obtain a general technique that can be used either as a boosting method, which improves results of other clustering algorithms, or as an independent clustering algorithm. The experimental work shows that Sil-Att is able to obtain high-quality results on text corpora with very different characteristics. Furthermore, its stable performance on all the considered corpora is indicative that it is a very robust method. This is a very interesting positive aspect of Sil-Att with respect to the other algorithms used in the experiments, whose performances heavily depend on specific characteristics of the corpora being considered.
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Keywords

AlgorithmAlgorithmsAnttreeBoosting methodCluster analysisClustering algorithmsHardnessHigh qualityModelRobust methodsStable performanceText clusteringText clustering, silhouette coefficientText corporaValidation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Natural Language Engineering due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2016, it was in position 95/133, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science, Artificial Intelligence. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Artificial Intelligence.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-02:

  • WoS: 3
  • Scopus: 4
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-02:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 9.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 9 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: http://hdl.handle.net/10251/82648
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Argentina; United Kingdom.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (Rosso, Paolo).

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