Giulia Venturi⋄

1.3k total citations
60 papers, 529 citations indexed

About

Giulia Venturi⋄ is a scholar working on Artificial Intelligence, General Health Professions and Language and Linguistics. According to data from OpenAlex, Giulia Venturi⋄ has authored 60 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 8 papers in General Health Professions and 7 papers in Language and Linguistics. Recurrent topics in Giulia Venturi⋄'s work include Natural Language Processing Techniques (38 papers), Text Readability and Simplification (20 papers) and Topic Modeling (18 papers). Giulia Venturi⋄ is often cited by papers focused on Natural Language Processing Techniques (38 papers), Text Readability and Simplification (20 papers) and Topic Modeling (18 papers). Giulia Venturi⋄ collaborates with scholars based in Italy, United States and United Kingdom. Giulia Venturi⋄'s co-authors include Felice Dell’Orletta⋄, Simonetta Montemagni⋄, Dominique Brunato⋄, Andrea Cimino, Paul M. Thompson, John McNaught, Sophia Ananiadou, Francesca Bonin, Thomas François and Philippe Blache and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and BMC Bioinformatics.

In The Last Decade

Giulia Venturi⋄

52 papers receiving 491 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giulia Venturi⋄ Italy 13 381 70 53 45 37 60 529
Vicki Bennett Australia 11 104 0.3× 42 0.6× 34 0.6× 88 2.0× 35 0.9× 21 465
Neil Barrett Taiwan 13 59 0.2× 26 0.4× 47 0.9× 113 2.5× 127 3.4× 33 507
Christian Rapp Switzerland 7 57 0.1× 27 0.4× 65 1.2× 92 2.0× 46 1.2× 35 360
Edgar Dale 5 336 0.9× 9 0.1× 87 1.6× 266 5.9× 58 1.6× 12 671
Rob Voigt United States 10 133 0.3× 6 0.1× 15 0.3× 10 0.2× 11 0.3× 23 453
Kyle MacDonald United States 9 66 0.2× 12 0.2× 13 0.2× 141 3.1× 92 2.5× 18 405
Junyi Li China 11 78 0.2× 4 0.1× 17 0.3× 53 1.2× 40 1.1× 24 424
Alan Bailin United States 7 113 0.3× 3 0.0× 34 0.6× 62 1.4× 34 0.9× 16 253
Lucas Nunes Vieira United Kingdom 10 181 0.5× 3 0.0× 58 1.1× 9 0.2× 20 0.5× 32 360
Richard D. Janda Canada 9 81 0.2× 6 0.1× 25 0.5× 12 0.3× 94 2.5× 30 427

Countries citing papers authored by Giulia Venturi⋄

Since Specialization
Citations

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

Fields of papers citing papers by Giulia Venturi⋄

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giulia Venturi⋄. 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 Giulia Venturi⋄. The network helps show where Giulia Venturi⋄ may publish in the future.

Co-authorship network of co-authors of Giulia Venturi⋄

This figure shows the co-authorship network connecting the top 25 collaborators of Giulia Venturi⋄. A scholar is included among the top collaborators of Giulia Venturi⋄ 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 Giulia Venturi⋄. Giulia Venturi⋄ 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
1.
Dell’Orletta⋄, Felice, et al.. (2024). Evaluating Large Language Models via Linguistic Profiling. 2835–2848.
2.
Brunato⋄, Dominique, et al.. (2022). Probing Linguistic Knowledge in Italian Neural Language Models across Language Varieties. SHILAP Revista de lepidopterología. 8(1). 2 indexed citations
3.
Zamparelli, Roberto, Shammur Absar Chowdhury, Dominique Brunato⋄, et al.. (2022). SemEval-2022 Task 3: PreTENS-Evaluating Neural Networks on Presuppositional Semantic Knowledge. Institutional Research Information System (Università degli Studi di Trento). 228–238. 8 indexed citations
4.
Mattei, Giorgio, Giulia Venturi⋄, Salvatore Alfieri, et al.. (2020). Clinical and Socio-demographic Variables Associated with the Outcome of Vocational Rehabilitation Programs: A Community-Based Italian Study. Community Mental Health Journal. 56(7). 1380–1390. 2 indexed citations
5.
Dell’Orletta⋄, Felice, et al.. (2020). "Voices of the Great War": A Richly Annotated Corpus of Italian Texts on the First World War.. Language Resources and Evaluation. 911–918. 1 indexed citations
6.
Dell’Orletta⋄, Felice, et al.. (2018). Universal Dependencies and Quantitative Typological Trends. A Case Study on Word Order. Language Resources and Evaluation. 2 indexed citations
7.
Mattei, Giorgio, Salvatore Alfieri, Sílvia Ferrari, et al.. (2018). Stakeholders’ views on vocational rehabilitation programs: a call for collaboration with Occupational Health Physicians. ˜La œMedicina del lavoro. 109(3). 201–209. 6 indexed citations
8.
Dell’Orletta⋄, Felice, et al.. (2017). Dangerous Relations in Dependency Treebanks. IEEE Transactions on Learning Technologies. 201–210. 1 indexed citations
9.
Dell’Orletta⋄, Felice, et al.. (2016). CItA: an L1 Italian Learners Corpus to Study the Development of Writing Competence.. Language Resources and Evaluation. 88–95. 5 indexed citations
10.
Brunato⋄, Dominique & Giulia Venturi⋄. (2014). Le tecnologie linguistico-computazionali nella misura della leggibilità di testi giuridici. 111–142.
11.
Dell’Orletta⋄, Felice, Giulia Venturi⋄, & Simonetta Montemagni⋄. (2013). Linguistically-driven Selection of Correct Arcs for Dependency Parsing. Computación y Sistemas. 17(2). 125–136. 1 indexed citations
12.
Cimino, Andrea, Felice Dell’Orletta⋄, Giulia Venturi⋄, & Simonetta Montemagni⋄. (2013). Linguistic Profiling based on General--purpose Features and Native Language Identification. CNR ExploRA. 207–215. 10 indexed citations
13.
Dell’Orletta⋄, Felice, Giulia Venturi⋄, & Simonetta Montemagni⋄. (2013). Unsupervised Linguistically-Driven Reliable Dependency Parses Detection and Self-Training for Adaptation to the Biomedical Domain. CNR ExploRA. 45–53. 3 indexed citations
14.
Dell’Orletta⋄, Felice, Simonetta Montemagni⋄, & Giulia Venturi⋄. (2013). Linguistic Profiling of Texts Across Textual Genres and Readability Levels. An Exploratory Study on Italian Fictional Prose. Recent Advances in Natural Language Processing. 189–197. 4 indexed citations
15.
Lenci, Alessandro, et al.. (2012). Enriching the ISST-TANL Corpus with Semantic Frames. Language Resources and Evaluation. 3719–3726. 1 indexed citations
16.
Dell’Orletta⋄, Felice, Giulia Venturi⋄, & Simonetta Montemagni⋄. (2011). ULISSE: an Unsupervised Algorithm for Detecting Reliable Dependency Parses. CNR ExploRA. 115–124. 7 indexed citations
17.
Bonin, Francesca, Felice Dell’Orletta⋄, Giulia Venturi⋄, & Simonetta Montemagni⋄. (2010). Contrastive Filtering of Domain-Specific Multi-Word Terms from Different Types of Corpora. International Conference on Computational Linguistics. 77–80. 6 indexed citations
18.
Bonin, Francesca, Felice Dell’Orletta⋄, Simonetta Montemagni⋄, & Giulia Venturi⋄. (2010). A Contrastive Approach to Multi-word Extraction from Domain-specific Corpora. Language Resources and Evaluation. 13 indexed citations
19.
Thompson, Paul M., Philip D. Cotter, John McNaught, et al.. (2008). Building a Bio-Event Annotated Corpus for the Acquisition of Semantic Frames from Biomedical Corpora. Language Resources and Evaluation. 2159–2166. 8 indexed citations
20.
Thompson, Paul M., Giulia Venturi⋄, John McNaught, Simonetta Montemagni⋄, & Sophia Ananiadou. (2008). Categorising Modality in Biomedical Texts. Language Resources and Evaluation. 27–34. 29 indexed citations

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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