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Pedro Bahamondes

dblp:296/4019 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Databases, data management, data science and information retrieval · 1 · 1 since 2021

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.

Databases, data mining, and information retrieval
1 paper
Graph data management · 50% Data models and query languages · 25% Database theory · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data models and query languages
graph query language
0.612022
Temporal Regular Path Queries · ICDE 2022
Database theory
query complexity
0.612022
Temporal Regular Path Queries · ICDE 2022
Graph data management › path query
regular path query
0.612022
Temporal Regular Path Queries · ICDE 2022
Graph data management › graph query processing
temporal graph query
0.612022
Temporal Regular Path Queries · ICDE 2022

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

dataflow framework · 0.6automata-based query evaluation · 0.6
YearPublicationVenuePosition
2022 Temporal Regular Path Queries
abstract
In the last decade, substantial progress has been made towards standardizing the syntax of graph query languages, and towards understanding their semantics and complexity of evaluation. In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries (TRPQs) that incorporate time into TPG navigation. Starting with design principles, we propose a natural syntactic extension of the MATCH clause of popular graph query languages. We then formally present the semantics of TRPQs, and study the complexity of their evaluation. We show that TRPQs can be evaluated in polynomial time if TPGs are time-stamped with time points, and identify fragments of the TRPQ language that admit efficient evaluation over a more succinct interval-annotated representation. Finally, we implement a fragment of the language in a state-of-the-art dataflow framework, and experimentally demonstrate that TRPQ can be evaluated efficiently.
Marcelo Arenas, Pedro Bahamondes, Amir Aghasadeghi, Julia Stoyanovich
ICDE2