Federico Sangati

23 papers receiving 100 citations

Peers

Federico Sangati
Comparison fields: 5 of 29
  • Artificial Intelligence 91
  • Experimental and Cognitive Psychology 8
  • Language and Linguistics 8
  • Molecular Biology 7
  • Cultural Studies 7
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Countries citing papers authored by Federico Sangati

Since Specialization
Citations

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

Fields of papers citing papers by Federico Sangati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federico Sangati

This figure shows the co-authorship network connecting the top 25 collaborators of Federico Sangati. A scholar is included among the top collaborators of Federico Sangati 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 Federico Sangati. Federico Sangati 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
#WorkIndexed citations
1 1
2 1
3 10
4
Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet.
2
5
Designing a Prototype Architecture for Crowdsourcing Language Resources
3
6 2
7
Pinocchio in Emojitaliano
2
8
PARSEME-It Corpus - An annotated Corpus of Verbal Multiword Expressions in Italian
0
9
D(H)ante: A New Set of Tools for XIII Century Italian
0
10
New online Tools and Digital Environments for Translation into Emoji
1
11
Emojitalianobot and EmojiWorldBot - New online Tools and Digital Environments for Translation into Emoji
2
12
School-tagging: interactive language exercises in classrooms
1
13
Automatic labeling of phonesthemic senses
8
14
Discontinuous Data-Oriented Parsing: A mildly context-sensitive all-fragments grammar
9
15
A Probabilistic Generative Model for an Intermediate Constituency-Dependency Representation
1
16
Efficiently extract recurring tree fragments from large treebanks
13
17 6
18 13
19
A simple DOP model for constituency parsing of Italian sentences
1
20
TOWARDS SIMPLER TREE SUBSTITUTION GRAMMARS
1

About Federico Sangati

Federico Sangati is a scholar working on Computer Science Applications, Artificial Intelligence and Human-Computer Interaction, having authored 25 papers that have together received 110 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (14 papers), Topic Modeling (11 papers) and Text Readability and Simplification (6 papers). The work is most often cited by research in Artificial Intelligence (91 citations), Cultural Studies (7 citations) and Language and Linguistics (8 citations). Federico Sangati has collaborated with scholars based in Netherlands, Italy and Cyprus. Frequent co-authors include Willem Zuidema, Rens Bod, Andreas van Cranenburgh, Raquel Fernández, Remko Scha, Christian Mazza, Frank Keller, Soheil Keshmiri, Tom Froese and Umair ul Hassan. Their work appears in journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and Frontiers in Neurorobotics.

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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