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Analysis of institutional authors

Rico, PCorresponding AuthorCuadrado, FAuthorDuenas, JcAuthorAndion, JAuthorParada, GhaAuthor

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October 18, 2021
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Business Process Event Prediction Through Scalable Online Learning

Publicated to: IEEE Access. 9 136313-136333 - 2021-01-01 9(), DOI: 10.1109/ACCESS.2021.3117147

Authors:

Rico, P; Cuadrado, F; Duenas, JC; Andion, J; Parada, GHA
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Affiliations

Univ Politecn Madrid, Dept Ingn Sistemas Telemat, E-28040 Madrid, Spain - Author

Abstract

Predictive process monitoring techniques aim to forecast outcomes of running business process instances. These techniques are based on using predictive models built from past observed behavior, i.e., in an offline setting. However, business process behavior usually changes over time and predictive models are therefore at risk of becoming obsolete. Because of this, the definition of systems that build predictive models through an online setting has recently gained attention. Nevertheless, the scalability of this kind of setting within a context where the amount of data available is experiencing rapid growth is an outstanding issue. To solve this problem, this paper aims to define a framework for event sequence prediction capable of taking advantage of modern distributed processing platforms. An implementation over this framework based on Apache Flink is presented and it is tested upon two different case studies to prove its validity and its capacity to scale.
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Keywords

Data miningData modelsDistributed processingHidden markov modelsMonitoringPredictive modelsProcess monitoringProposalsReal-time systemsScalability

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal IEEE Access due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering (Miscellaneous).

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 2026-04-27:

  • Google Scholar: 2
  • WoS: 1
  • Scopus: 2
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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 2026-04-27:

  • 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: 20 (PlumX).

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: https://oa.upm.es/87195/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 122
  • Downloads: 62
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (RICO PEREIRA, PATRICIA) and Last Author (PARADA GELVEZ, HUGO ALEXER).

the author responsible for correspondence tasks has been RICO PEREIRA, PATRICIA.

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Awards linked to the item

This work was supported in part by the Ministerio de Ciencia, Investigacion y Universidades de Espana, project PRECON-I4, Retos de la Sociedad, under Grant TIN2017-86520-C3-2-R.
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