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Analysis of institutional authors

Cayci A.Corresponding AuthorEibe SAuthor

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July 25, 2020
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Self-configuring data mining for ubiquitous computing

Publicated to: INFORMATION SCIENCES. 246 83-99 - 2013-10-10 246(), DOI: 10.1016/j.ins.2013.05.015

Authors:

Cayci, A; Menasalvas, E; Saygin, Y; Eibe, S
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Affiliations

Sabanci Univ, Fac Engn & Nat Sci - Author
Sabanci Universitesi - Author
Univ Politecn Madrid, Fac Informat - Author
Universidad Politécnica de Madrid - Author
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Abstract

Ubiquitous computing software needs to be autonomous so that essential decisions such as how to configure its particular execution are self-determined. Moreover, data mining serves an important role for ubiquitous computing by providing intelligence to several types of ubiquitous computing applications. Thus, automating ubiquitous data mining is also crucial. We focus on the problem of automatically configuring the execution of a ubiquitous data mining algorithm. In our solution, we generate configuration decisions in a resource aware and context aware manner since the algorithm executes in an environment in which the context often changes and computing resources are often severely limited. We propose to analyze the execution behavior of the data mining algorithm by mining its past executions. By doing so, we discover the effects of resource and context states as well as parameter settings on the data mining quality. We argue that a classification model is appropriate for predicting the behavior of an algorithm's execution and we concentrate on decision tree classifier. We also define taxonomy on data mining quality so that tradeoff between prediction accuracy and classification specificity of each behavior model that classifies by a different abstraction of quality, is scored for model selection. Behavior model constituents and class label transformations are formally defined and experimental validation of the proposed approach is also performed. © 2013 Elsevier Inc. All rights reserved.
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Keywords

Data miningDecision treeUbiquitous computing

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal INFORMATION SCIENCES 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, 2013, it was in position 8/135, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Information Systems.

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 2026-04-24:

  • Google Scholar: 8
  • WoS: 7
  • Scopus: 7
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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 2026-04-24:

  • 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: 39 (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/19174/

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: 458
  • Downloads: 485
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Turkey.

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 (MENASALVAS RUIZ, ERNESTINA) and Last Author (EIBE GARCIA, SANTIAGO).

the author responsible for correspondence tasks has been MENASALVAS RUIZ, ERNESTINA.

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