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Analysis of institutional authors

Sanchez, JaCorresponding AuthorAnitei, DAuthor

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October 28, 2024
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Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval

Publicated to:Pattern Analysis And Applications. 26 (4): 1571-1584 - 2023-11-01 26(4), DOI: 10.1007/s10044-023-01158-8

Authors: Noya, Ernesto; Benedi, Jose Miguel; Sanchez, Joan Andreu; Anitei, Dan

Affiliations

Univ Politecn Valencia - Author
ValgrAI Valencian Grad Sch & Res Network Artifici - Author

Abstract

We present a discriminative learning algorithm for the probabilistic estimation of two-dimensional probabilistic context-free grammars (2D-PCFG) for mathematical expressions recognition and retrieval. This algorithm is based on a generalization of the H-criterion as the objective function and the growth transformations as the optimization method. For the development of the discriminative estimation algorithm, the N-best interpretations provided by the 2D-PCFG have been considered. Experimental results are reported on two available datasets: Im2Latex and IBEM. The first experiment compares the proposed discriminative estimation method with the classic Viterbi-based estimation method. The second one studies the performance of the estimated models depending on the length of the mathematical expressions and the number of admissible errors in the metric used.

Keywords

Discriminative learningGrowth transformationsImageMathematical expression retrievalNeural-networkProbabilistic indexingTwo-dimensional probabilistic context-free grammars

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Pattern Analysis And Applications 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, 2023, it was in position 66/197, 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 Computer Vision and Pattern Recognition.

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: 1.18, 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 2025-07-06, the following number of citations:

  • WoS: 1
  • Scopus: 2

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 2025-07-06:

  • 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: 3 (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 (Noya, E) and Last Author (Anitei, Dan).

the author responsible for correspondence tasks has been Sánchez Peiró, Joan Andreu.