Stefania Gnesi
Italian software engineer
Facts
8 properties- Instance of
- human
- Date of birth
- 1954
- Occupation
- researcher, computer scientist
- Employer
- Consiglio Nazionale delle Ricerche (1984–present)[4]
- Educated at
- University of Pisa (1972–1978)
- Maintained by WikiProject
- WikiProject Mathematics[7]
🏷️ Also known as
en Stefania Gnesi
🔖 Identifiers · 23
- ISNI
- 0000000114504750
- ORCID iD
- 0000-0002-0139-0421
- VIAF cluster ID
- 85388714
- Library of Congress Authorities ID
- n2003004204
- GND ID
- 1049306996
- ACM Digital Library author ID
- 81338488778
- Bibliothèque nationale de France ID
- 146228941
- CAMPUS author ID
- 05618
- CNR-IRIS author ID
- 18357
- DBLP author ID
- g/StefaniaGnesi
- DDB person (GND) ID
- 1049306996
- Dimensions author ID
- 012341703201.17
Show all 23 identifiers +11
- FLORE author ID
- 24518
- Google Knowledge Graph ID
- /g/11bwftwwrl
- Google Scholar author ID
- vkhTk-MAAAAJ
- IEEE Xplore author ID
- 37282428500
- IdRef ID
- 076585085
- J9U entity ID
- 987007461069305171
- NL CR AUT ID
- xx0013781
- SBN author ID
- PISV001623
- Scopus author ID
- 6603718373
- Yale LUX ID
- person/3dfb7099-f6de-48a9-a6fe-ee9c66b078cc
- ZbMATH author ID
- gnesi.stefania
🔗 Connections
Author of 12
A Guidelines framework for understandable BPMN models,
Ambiguity and tacit knowledge in requirements elicitation interviews,
A spaCy-based tool for extracting variability from NL requirements,
Detecting Domain-Specific Ambiguities: An NLP Approach Based on Wikipedia Crawling and Word Embeddings,
Detecting requirements defects with NLP patterns: an industrial experience in the railway domain,
Hacking an Ambiguity Detection Tool to Extract Variation Points,
Identification of Cross-Domain Ambiguity with Language Models,
Inconsistency Detection in Natural Language Requirements using ChatGPT: a Preliminary Evaluation
+4 more
← Authored by 12
A Guidelines framework for understandable BPMN models,
Ambiguity and tacit knowledge in requirements elicitation interviews,
A spaCy-based tool for extracting variability from NL requirements,
Detecting Domain-Specific Ambiguities: An NLP Approach Based on Wikipedia Crawling and Word Embeddings,
Detecting requirements defects with NLP patterns: an industrial experience in the railway domain,
Hacking an Ambiguity Detection Tool to Extract Variation Points,
Identification of Cross-Domain Ambiguity with Language Models,
Inconsistency Detection in Natural Language Requirements using ChatGPT: a Preliminary Evaluation
+4 more
Affiliated with 1
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