Alejandro Ramos-Soto

413 citations
22 papers · 241 · h-index 9

Impact in

Papers in

    • Natural Language Processing Techniques 9
    • Speech and dialogue systems 7
    • Semantic Web and Ontologies 6
    • Advanced Text Analysis Techniques 3
    • Topic Modeling 3
    • Fuzzy Logic and Control Systems 3
    • Data Management and Algorithms 5

Alejandro Ramos-Soto

19 papers receiving 230 citations

Peers

Alejandro Ramos-Soto
Comparison fields: 5 of 55
  • Artificial Intelligence 185
  • Computer Science Applications 19
  • Signal Processing 32
  • Geography, Planning and Development 16
  • Management Science and Operations Research 26
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Citations per field
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Citations per year

Countries citing papers authored by Alejandro Ramos-Soto

Since Specialization
Citations

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

Fields of papers citing papers by Alejandro Ramos-Soto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alejandro Ramos-Soto. 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 Alejandro Ramos-Soto. The network helps show where Alejandro Ramos-Soto may publish in the future.

Co-authors

The 16 scholars most cited alongside Alejandro Ramos-Soto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alejandro Ramos-Soto Line = papers co-authored together Alejandro Ramos-Soto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201461
2 201552
3 201615
4 201614
5 201713
6 201812
7 201111
8 201511
9
Automatic linguistic descriptions of meteorological data a soft computing approach for converting open data to open information
20138
10 20198
11 20177
12 20166
13
Hybrid Data-Expert Explainable Beer Style Classifier
20184
14 20224
15 20154
16
Explainable AI beer style classifier
20183
17 20173
18 20152
19
Computing with perceptions for the linguistic description of complex phenomena through the analysis of time series data
20142
20 20221

About Alejandro Ramos-Soto

Alejandro Ramos-Soto is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Networks and Communications and Computational Theory and Mathematics, having authored 22 papers that have together received 241 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Speech and dialogue systems (7 papers), Semantic Web and Ontologies (6 papers), Data Management and Algorithms (5 papers), Advanced Text Analysis Techniques (3 papers), Topic Modeling (3 papers), Fuzzy Logic and Control Systems (3 papers) and Online Learning and Analytics (2 papers). The work is most often cited by research in Artificial Intelligence (185 citations), Computer Science Applications (19 citations), Signal Processing (32 citations), Geography, Planning and Development (16 citations) and Management Science and Operations Research (26 citations). Alejandro Ramos-Soto has collaborated with scholars based in Spain, United Kingdom and Italy. Frequent co-authors include Alberto Bugarín, Senén Barro, J. J. Taboada, José M. Alonso, Ehud Reiter, Kees van Deemter, Patricia Martín-Rodilla, Adriana Gewerc Barujel, Ciro Castiello and Manuel Lama. Their work appears in journals such as Fuzzy Sets and Systems, IEEE Transactions on Fuzzy Systems, Applied Soft Computing, International Journal of Intelligent Systems and Data Technologies and Applications.

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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