Ignacio Fernández-Tobías

922 total citations
16 papers, 402 citations indexed

About

Ignacio Fernández-Tobías is a scholar working on Information Systems, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Ignacio Fernández-Tobías has authored 16 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Information Systems, 9 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Ignacio Fernández-Tobías's work include Recommender Systems and Techniques (12 papers), Topic Modeling (5 papers) and Advanced Graph Neural Networks (4 papers). Ignacio Fernández-Tobías is often cited by papers focused on Recommender Systems and Techniques (12 papers), Topic Modeling (5 papers) and Advanced Graph Neural Networks (4 papers). Ignacio Fernández-Tobías collaborates with scholars based in Spain, Italy and Australia. Ignacio Fernández-Tobías's co-authors include Iván Cantador, Francesco Ricci⋆, Alejandro Bellogín, Mehdi Elahi, Marius Kaminskas, Paolo Tomeo, Tommaso Di Noia, Matthias Braunhofer, Vito Walter Anelli and Roi Blanco and has published in prestigious journals such as User Modeling and User-Adapted Interaction, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems and Information Technology & Tourism.

In The Last Decade

Ignacio Fernández-Tobías

16 papers receiving 384 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ignacio Fernández-Tobías Spain 9 288 197 88 54 53 16 402
Jonathan Gemmell United States 10 373 1.3× 274 1.4× 124 1.4× 26 0.5× 56 1.1× 27 581
Ante Odić Slovenia 7 175 0.6× 105 0.5× 82 0.9× 23 0.4× 27 0.5× 12 292
Javier Parapar Spain 15 402 1.4× 385 2.0× 99 1.1× 135 2.5× 42 0.8× 67 632
Matthias Braunhofer Italy 10 195 0.7× 79 0.4× 100 1.1× 32 0.6× 54 1.0× 15 286
Grace Hui Yang United States 14 344 1.2× 464 2.4× 150 1.7× 54 1.0× 67 1.3× 75 725
Hao Fu China 9 144 0.5× 164 0.8× 56 0.6× 14 0.3× 47 0.9× 11 278
Thomas White United States 6 321 1.1× 112 0.6× 62 0.7× 38 0.7× 41 0.8× 36 484
Amirali Salehi‐Abari Canada 12 277 1.0× 106 0.5× 63 0.7× 39 0.7× 55 1.0× 31 383
Daniel Krause Germany 10 196 0.7× 166 0.8× 71 0.8× 26 0.5× 38 0.7× 34 391
Fatih Gedikli Germany 7 285 1.0× 214 1.1× 99 1.1× 56 1.0× 71 1.3× 13 405

Countries citing papers authored by Ignacio Fernández-Tobías

Since Specialization
Citations

This map shows the geographic impact of Ignacio Fernández-Tobías'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 Ignacio Fernández-Tobías with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ignacio Fernández-Tobías more than expected).

Fields of papers citing papers by Ignacio Fernández-Tobías

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ignacio Fernández-Tobías. 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 Ignacio Fernández-Tobías. The network helps show where Ignacio Fernández-Tobías may publish in the future.

Co-authorship network of co-authors of Ignacio Fernández-Tobías

This figure shows the co-authorship network connecting the top 25 collaborators of Ignacio Fernández-Tobías. A scholar is included among the top collaborators of Ignacio Fernández-Tobías 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 Ignacio Fernández-Tobías. Ignacio Fernández-Tobías is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Fernández-Tobías, Ignacio, Iván Cantador, Paolo Tomeo, Vito Walter Anelli, & Tommaso Di Noia. (2019). Addressing the user cold start with cross-domain collaborative filtering: exploiting item metadata in matrix factorization. User Modeling and User-Adapted Interaction. 29(2). 443–486. 65 indexed citations
2.
Tomeo, Paolo, Ignacio Fernández-Tobías, Iván Cantador, & Tommaso Di Noia. (2017). Addressing the Cold Start with Positive-Only Feedback Through Semantic-Based Recommendations. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 25(Suppl. 2). 57–78. 2 indexed citations
3.
Fernández-Tobías, Ignacio & Roi Blanco. (2016). Memory-based Recommendations of Entities for Web Search Users. 35–44. 10 indexed citations
4.
Fernández-Tobías, Ignacio, Paolo Tomeo, Iván Cantador, Tommaso Di Noia, & Eugenio Di Sciascio. (2016). Accuracy and Diversity in Cross-domain Recommendations for Cold-start Users with Positive-only Feedback. 119–122. 18 indexed citations
5.
Fernández-Tobías, Ignacio, Matthias Braunhofer, Mehdi Elahi, Francesco Ricci⋆, & Iván Cantador. (2016). Alleviating the new user problem in collaborative filtering by exploiting personality information. User Modeling and User-Adapted Interaction. 26(2-3). 221–255. 87 indexed citations
6.
Tomeo, Paolo, Ignacio Fernández-Tobías, Tommaso Di Noia, & Iván Cantador. (2016). Exploiting Linked Open Data in Cold-start Recommendations with Positive-only Feedback. 1–8. 6 indexed citations
7.
Elahi, Mehdi, Mouzhi Ge, Francesco Ricci⋆, et al.. (2015). Interaction Design in a Mobile Food Recommender System. Biblos-e Archivo (Universidad Autónoma de Madrid). 49–52. 14 indexed citations
8.
Braunhofer, Matthias, Ignacio Fernández-Tobías, & Francesco Ricci⋆. (2015). Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems. Biblos-e Archivo (Universidad Autónoma de Madrid). 2–8. 4 indexed citations
9.
Fernández-Tobías, Ignacio & Iván Cantador. (2014). Exploiting Social Tags in Matrix Factorization Models for Cross-domain Collaborative Filtering. Conference on Recommender Systems. 34–41. 44 indexed citations
10.
Cantador, Iván & Ignacio Fernández-Tobías. (2014). On the exploitation of user personality in recommender systems. 42–45. 5 indexed citations
11.
Kaminskas, Marius, Ignacio Fernández-Tobías, Francesco Ricci⋆, & Iván Cantador. (2014). Knowledge-based identification of music suited for places of interest. Information Technology & Tourism. 14(1). 73–95. 6 indexed citations
12.
Fernández-Tobías, Ignacio, Iván Cantador, & Laura Plaza. (2013). A social tag-based dimensional model of emotions: Building cross-domain folksonomies. Procesamiento del lenguaje natural. 51(51). 195–202. 1 indexed citations
13.
Cantador, Iván, Ignacio Fernández-Tobías, & Alejandro Bellogín. (2013). Relating personality types with user preferences in multiple entertainment domains. 65 indexed citations
14.
Kaminskas, Marius, Ignacio Fernández-Tobías, Francesco Ricci⋆, & Iván Cantador. (2012). Knowledge-based music retrieval for places of interest. View. 19–24. 19 indexed citations
15.
Fernández-Tobías, Ignacio, Iván Cantador, Marius Kaminskas, & Francesco Ricci⋆. (2011). A generic semantic-based framework for cross-domain recommendation. View. 25–32. 54 indexed citations
16.
Fernández-Tobías, Ignacio, Iván Cantador, & Alejandro Bellogín. (2011). cTag: Semantic Contextualisation of Social Tags. Biblos-e Archivo (Universidad Autónoma de Madrid). 2 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.

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