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Grant support

The research leading to the presented results has been undertaken within the AFARCLOUD European Project (Aggregate Farming in the Cloud), under Grant Agreement No. 783221-AFarCloud-H2020-ECSEL-2017-2, and supported in part by the ECSEL JU and in part by the Spanish Ministry of Science, Innovation and Universities under Grant PCI2018-092965. This work has been also partially supported by the China Scholarship Council (CSC).

Analysis of institutional authors

Zhai, ZhaoyuCorresponding AuthorMartinez Ortega, Jose-FernanAuthorCastillejo, PedroAuthorBeltran, VictoriaCorresponding Author

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December 11, 2019
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Article

A Triangular Similarity Measure for Case Retrieval in CBR and Its Application to an Agricultural Decision Support System

Publicated to:Sensors. 19 (21): E4605- - 2019-11-01 19(21), DOI: 10.3390/s19214605

Authors: Zhai, Zhaoyu; Martinez Ortega, Jose-Fernan; Castillejo, Pedro; Beltran, Victoria

Affiliations

UPM, ETSIST, Dept Ingn Telemat & Elect DTE, C Nikola Tesla S-N, Madrid 28031, Spain - Author

Abstract

Case-based reasoning has been a widely-used approach to assist humans in making decisions through four steps: retrieve, reuse, revise, and retain. Among these steps, case retrieval plays a significant role because the rest of processes cannot proceed without successfully identifying the most similar past case beforehand. Some popular methods such as angle-based and distance-based similarity measures have been well explored for case retrieval. However, these methods may match inaccurate cases under certain extreme circumstances. Thus, a triangular similarity measure is proposed to identify commonalities between cases, overcoming the drawbacks of angle-based and distance-based measures. For verifying the effectiveness and performance of the proposed measure, case-based reasoning was applied to an agricultural decision support system for pest management and 300 new cases were used for testing purposes. Once a new pest problem is reported, its attributes are compared with historical data by the proposed triangular similarity measure. Farmers can obtain quick decision support on managing pest problems by learning from the retrieved solution of the most similar past case. The experimental result shows that the proposed measure can retrieve the most similar case with an average accuracy of 91.99% and it outperforms the other measures in the aspects of accuracy and robustness.

Keywords

case retrievalcase-based reasoningdecision support systemsustainable agricultureCase retrievalCase-based reasoningClassificationDecision support systemDistanceImproveSetsSignalsStem borerSustainable agricultureTriangular similarity measureUser similarity

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors 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, 2019, it was in position 15/64, thus managing to position itself as a Q1 (Primer Cuartil), in the category Instruments & Instrumentation.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 1.81, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-14, the following number of citations:

  • WoS: 6
  • Scopus: 7
  • Europe PMC: 2
  • Google Scholar: 13

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 2025-07-14:

  • 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: 25 (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.

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 (ZHAI, ZHAOYU) and Last Author (BELTRAN MARTINEZ, MARIA VICTORIA).

the authors responsible for correspondence tasks have been ZHAI, ZHAOYU and BELTRAN MARTINEZ, MARIA VICTORIA.