Giuliano Armano

1.6k citations
94 papers · 942 indexed · h-index 15

Giuliano Armano

89 papers receiving 884 citations

Peers

Giuliano Armano
Comparison fields: 5 of 131
  • Management Science and Operations Research 227
  • Artificial Intelligence 415
  • Signal Processing 62
  • Health Information Management 25
  • Information Systems 120
Replace Keli Xiao with:
Keli Xiao United States
Fabio Stella Italy
Rajashree Dash India
Dawei Cheng China
Soumya Sen India
Parimala Thulasiraman Canada
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Citations per year

Countries citing papers authored by Giuliano Armano

Since Specialization
Citations

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

Fields of papers citing papers by Giuliano Armano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Giuliano Armano, 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 Giuliano Armano Line = papers co-authored together Giuliano Armano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20248
2 20234
3 20232
4 20203
5
NewsVallum: Semantics-Aware Text and Image Processing for Fake News Detection system.
20181
6
Analysis of Term Roles Along Taxonomy Nodes by Adopting Discriminant and Characteristic Capabilities.
20150
7 20157
8 20144
9 20121
10
A Novel Recommender System Inspired by Contextual Advertising Approach
20100
11
Profiling Users to Perform Contextual Advertising
20091
12 20092
13 20071
14 200663
15 200511
16 20042
17
Generating Abstractions from Static Domain Analysis.
20032
18
A parametric hierarchical planner for experimenting abstraction techniques
20038
19
Experimenting the Performance of Abstraction Mechanisms Through a Parametric Hierarchical Planner
20035
20
Region Growing and Merging Techniques for Accurate Image Segmentation
19894

About Giuliano Armano

Giuliano Armano is a scholar working on Artificial Intelligence, Information Systems and Software, having authored 94 papers that have together received 942 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (10 papers), AI-based Problem Solving and Planning (9 papers), Web Data Mining and Analysis (9 papers), Advanced Text Analysis Techniques (8 papers), Machine Learning and Data Classification (8 papers), Face and Expression Recognition (7 papers), Imbalanced Data Classification Techniques (7 papers) and Phonocardiography and Auscultation Techniques (7 papers). The work is most often cited by research in Management Science and Operations Research (227 citations), Artificial Intelligence (415 citations) and Signal Processing (62 citations). Giuliano Armano has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Andréa Murru, Michele Marchesi, Eloisa Vargiu, Marco Alberto Javarone, Andrea Manconi, Luciano Milanesi, Amir Mohammad Amiri, Alessandro Orro, Fabio Roli and Matteo Gnocchi. Their work appears in journals such as Information Sciences, BMC Bioinformatics, IEEE Transactions on NanoBioscience, Energies and Expert Systems with 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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