Giorgio Satta

97 papers receiving 1.2k citations

Peers

Giorgio Satta
Comparison fields: 5 of 60
  • Artificial Intelligence 1.3k
  • Computational Theory and Mathematics 340
  • Molecular Biology 146
  • Information Systems 81
  • Computer Vision and Pattern Recognition 79
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Citations per field
00.5×4.4×
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Citations per year

Countries citing papers authored by Giorgio Satta

Since Specialization
Citations

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

Fields of papers citing papers by Giorgio Satta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giorgio Satta

This figure shows the co-authorship network connecting the top 25 collaborators of Giorgio Satta. A scholar is included among the top collaborators of Giorgio Satta 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 Giorgio Satta. Giorgio Satta 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
A Transition-Based Dependency Parser Using a Dynamic Parsing Strategy
18
2
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing
12
3
Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing
14
4
Optimal Head-Driven Parsing Complexity for Linear Context-Free Rewriting Systems
4
5
Computation of Infix Probabilities for Probabilistic Context-Free Grammars
5
6
Efficient Parsing of Well-Nested Linear Context-Free Rewriting Systems
26
7
The Importance of Rule Restrictions in CCG
5
8
Parsing and Translation Algorithms Based on Weighted Extended Tree Transducers
2
9
Optimal Rank Reduction for Linear Context-Free Rewriting Systems with Fan-Out Two
7
10
Comparing Italian parsers on a common treebank: the Evalita experience
9
11
Guided Learning for Bidirectional Sequence Classification
112
12
42th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
10
13
20th International Conference on Computational Linguistics, Proceedings of the Conference
1
14
Partially ordered multiset context-free grammars and free-word-order parsing
1
15 1
16
The Membership Problem for Unordered Vector Languages.
1
17
Tree-adjoining grammar parsing and boolean matrix multiplication
19
18 1
19
A tabular method for island-driven context-free grammar parsing
2
20
Head-Driven Bidirectional Parsing: A Tabular Method
12

About Giorgio Satta

Giorgio Satta is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Hardware and Architecture, having authored 102 papers that have together received 1.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (85 papers), Algorithms and Data Compression (49 papers) and semigroups and automata theory (44 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computational Theory and Mathematics (340 citations) and Software (33 citations). Giorgio Satta has collaborated with scholars based in Italy, United States and Sweden. Frequent co-authors include Marco Kuhlmann, Mark-Jan Nederhof, Jason Eisner, Carlos Gómez‐Rodríguez, Shay B. Cohen, Ryan McDonald, Aravind K. Joshi, Libin Shen, Robert Frank and Owen Rambow. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Artificial Intelligence and Journal of the ACM.

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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