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Fernando Florenzano

dblp:186/2965 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2020
0000-0002-0846-3291ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Algorithms and data structures · 89% Automata and formal languages · 11%
Artificial intelligence
2 papers
Information extraction and text analysis · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › combinatorial algorithms
enumeration algorithms
0.522020
Efficient Enumeration Algorithms for Regular Document Spanners · ACM Trans. Database Syst. 2020
Constant Delay Algorithms for Regular Document Spanners · PODS 2018
Algorithms and data structures › combinatorial algorithms › enumeration algorithms
output-linear delay enumeration
0.412020
Efficient Enumeration Algorithms for Regular Document Spanners · ACM Trans. Database Syst. 2020
Algorithms and data structures › combinatorial algorithms › enumeration algorithms
constant delay enumeration
0.112018
Constant Delay Algorithms for Regular Document Spanners · PODS 2018

Methods — techniques the papers use, named apart from their topics

fine-grained complexity analysis · 0.9
YearPublicationVenuePosition
2020 Efficient Enumeration Algorithms for Regular Document Spanners
abstract
Regular expressions and automata models with capture variables are core tools in rule-based information extraction. These formalisms, also called regular document spanners , use regular languages to locate the data that a user wants to extract from a text document and then store this data into variables. Since document spanners can easily generate large outputs, it is important to have efficient evaluation algorithms that can generate the extracted data in a quick succession, and with relatively little precomputation time. Toward this goal, we present a practical evaluation algorithm that allows output-linear delay enumeration of a spanner’s result after a precomputation phase that is linear in the document. Although the algorithm assumes that the spanner is specified in a syntactic variant of variable-set automata, we also study how it can be applied when the spanner is specified by general variable-set automata, regex formulas, or spanner algebras. Finally, we study the related problem of counting the number of outputs of a document spanner and provide a fine-grained analysis of the classes of document spanners that support efficient enumeration of their results.
Fernando Florenzano, Cristian Riveros, Martín Ugarte, Stijn Vansummeren, Domagoj Vrgoc
ACM Trans. Database Syst.1
2019 Validating Shacl Constraints over a Sparql Endpoint
Julien Corman, Fernando Florenzano, Juan L. Reutter, Ognjen Savkovic
ISWC (1)2
2018 Constant Delay Algorithms for Regular Document Spanners
abstract
Regular expressions and automata models with capture variables are core tools in rule-based information extraction. These formalisms, also called regular document spanners, use regular languages in order to locate the data that a user wants to extract from a text document, and then store this data into variables. Since document spanners can easily generate large outputs, it is important to have good evaluation algorithms that can generate the extracted data in a quick succession, and with relatively little precomputation time. Towards this goal, we present a practical evaluation algorithm that allows constant delay enumeration of a spanner's output after a precomputation phase that is linear in the document. While the algorithm assumes that the spanner is specified in a syntactic variant of variable set automata, we also study how it can be applied when the spanner is specified by general variable set automata, regex formulas, or spanner algebras. Finally, we study the related problem of counting the number of outputs of a document spanner, providing a fine grained analysis of the classes of document spanners that support efficient enumeration of their results.
Fernando Florenzano, Cristian Riveros, Martín Ugarte, Stijn Vansummeren, Domagoj Vrgoc
PODS1