Silvia Acid

511 total citations
9 papers, 266 citations indexed

About

Silvia Acid is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems. According to data from OpenAlex, Silvia Acid has authored 9 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Management Science and Operations Research and 2 papers in Information Systems. Recurrent topics in Silvia Acid's work include Bayesian Modeling and Causal Inference (8 papers), Data Quality and Management (4 papers) and Rough Sets and Fuzzy Logic (2 papers). Silvia Acid is often cited by papers focused on Bayesian Modeling and Causal Inference (8 papers), Data Quality and Management (4 papers) and Rough Sets and Fuzzy Logic (2 papers). Silvia Acid collaborates with scholars based in Spain. Silvia Acid's co-authors include Luis M. de Campos, Juan M. Fernández‐Luna, Javier G. Castellano and Juan F. Huete and has published in prestigious journals such as Machine Learning, International Journal of Human-Computer Studies and Artificial Intelligence in Medicine.

In The Last Decade

Silvia Acid

9 papers receiving 240 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Silvia Acid Spain	7	194	56	43	40	36	9	266
Ana María Martínez Spain	9	191 1.0×	42 0.8×	52 1.2×	17 0.4×	30 0.8×	29	233
Michael Shwe United States	5	204 1.1×	38 0.7×	20 0.5×	46 1.1×	13 0.4×	6	273
Denis Deratani Mauá Brazil	10	241 1.2×	60 1.1×	10 0.2×	12 0.3×	57 1.6×	49	290
Neville K. Kitson United Kingdom	5	118 0.6×	33 0.6×	18 0.4×	9 0.2×	12 0.3×	11	200
Hei Chan United States	7	148 0.8×	36 0.6×	12 0.3×	9 0.2×	22 0.6×	12	187
Xianchao Xie China	8	154 0.8×	33 0.6×	11 0.3×	16 0.4×	33 0.9×	12	250
Zhongli Ding United States	6	170 0.9×	36 0.6×	46 1.1×	36 0.9×	11 0.3×	10	206
Adam Niewiadomski Poland	9	188 1.0×	67 1.2×	14 0.3×	6 0.1×	77 2.1×	35	265
M. Rifqi France	5	80 0.4×	37 0.7×	19 0.4×	6 0.1×	28 0.8×	8	129

Countries citing papers authored by Silvia Acid

Since Specialization

Citations

This map shows the geographic impact of Silvia Acid's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Silvia Acid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvia Acid more than expected).

Fields of papers citing papers by Silvia Acid

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Silvia Acid. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Silvia Acid. The network helps show where Silvia Acid may publish in the future.

Co-authorship network of co-authors of Silvia Acid

This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Acid. A scholar is included among the top collaborators of Silvia Acid based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Silvia Acid. Silvia Acid is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Acid, Silvia, et al.. (2012). Evaluation methods and strategies for the interactive use of classifiers. International Journal of Human-Computer Studies. 70(5). 321–331. 1 indexed citations

2.

Acid, Silvia, et al.. (2011). Minimum redundancy maximum relevancy versus score-based methods for learning Markov boundaries. 619–623. 7 indexed citations

3.

Acid, Silvia, et al.. (2011). Score-based methods for learning Markov boundaries by searching in constrained spaces. Data Mining and Knowledge Discovery. 26(1). 174–212. 12 indexed citations

4.

Acid, Silvia, Luis M. de Campos, & Javier G. Castellano. (2005). Learning Bayesian Network Classifiers: Searching in a Space of Partially Directed Acyclic Graphs. Machine Learning. 59(3). 213–235. 49 indexed citations

5.

Acid, Silvia, et al.. (2004). A comparison of learning algorithms for Bayesian networks: a case study based on data from an emergency medical service. Artificial Intelligence in Medicine. 30(3). 215–232. 59 indexed citations

6.

Acid, Silvia & Luis M. de Campos. (2003). Searching for Bayesian Network Structures in the Space of Restricted Acyclic Partially Directed Graphs. Journal of Artificial Intelligence Research. 18. 445–490. 68 indexed citations

7.

Acid, Silvia, Luis M. de Campos, Juan M. Fernández‐Luna, & Juan F. Huete. (2003). An information retrieval model based on simple Bayesian networks. International Journal of Intelligent Systems. 18(2). 251–265. 31 indexed citations

8.

Acid, Silvia & Luis M. de Campos. (2001). A hybrid methodology for learning belief networks: BENEDICT. International Journal of Approximate Reasoning. 27(3). 235–262. 38 indexed citations

9.

Acid, Silvia, Luis M. de Campos, & Juan F. Huete. (2001). Estimating probability values from an incomplete dataset. International Journal of Approximate Reasoning. 27(2). 183–204. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact