Laura Po

948 total citations
54 papers, 463 citations indexed

About

Laura Po is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Laura Po has authored 54 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 15 papers in Information Systems and 11 papers in Signal Processing. Recurrent topics in Laura Po's work include Semantic Web and Ontologies (23 papers), Air Quality Monitoring and Forecasting (11 papers) and Biomedical Text Mining and Ontologies (10 papers). Laura Po is often cited by papers focused on Semantic Web and Ontologies (23 papers), Air Quality Monitoring and Forecasting (11 papers) and Biomedical Text Mining and Ontologies (10 papers). Laura Po collaborates with scholars based in Italy, Spain and Greece. Laura Po's co-authors include Sonia Bergamaschi, Nikos Bikakis, George Papastefanatos, Maciej Gawinecki, Sergio Ilarri, Domenico Beneventano, Bharath Sudharsan, José R. R. Viqueira, John G. Breslin and Eduardo Mena and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Laura Po

52 papers receiving 432 citations

Peers

Laura Po
Comparison fields: 5 of 69
  • Artificial Intelligence 234
  • Information Systems 99
  • Computer Networks and Communications 80
  • Computer Vision and Pattern Recognition 80
  • Building and Construction 79
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Citations per field, relative to Laura Po
Laura Po · 1×
Citations per year, relative to Laura Po
Laura Po · 1×

Countries citing papers authored by Laura Po

Since Specialization
Citations

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

Fields of papers citing papers by Laura Po

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura Po. 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 Laura Po. The network helps show where Laura Po may publish in the future.

Co-authorship network of co-authors of Laura Po

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 1
4 4
5 4
6 2
7 2
8 1
9 6
10 20
11 19
12 36
13
SenseBoard: Sensor monitoring for air quality experts
4
14
Providing Effective Visualizations over Big Linked Data.
1
15 9
16
High-level Visualization Over Big Linked Data.
5
17 6
18
LODeX: A tool for Visual Querying Linked Open Data
13
19
A visual summary for linked open data sources
20
20
Automatic annotation for mapping discovery in data integration systems.
8

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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