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Sanggoo Lee

dblp:60/2283 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1988
—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 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.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 87% Database theory · 13%

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

TopicWeightPapersLastEvidence papers
Query processing and optimization › recursive query
recursive query optimization
0.011988
Semantic Query Optimization in Recursive Databases · ICDE 1988
Query processing and optimization › semantic query processing
semantic query optimization
0.011988
Semantic Query Optimization in Recursive Databases · ICDE 1988
Database theory
deductive database
0.011988
Semantic Query Optimization in Recursive Databases · ICDE 1988

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

residue propagation · 0.0integrity constraints · 0.0compiled iterative method · 0.0
YearPublicationVenuePosition
1988 Semantic Query Optimization in Recursive Databases
abstract
Semantic query optimization is the process of using semantic knowledge expressed in the form of integrity constraints to transform a query into a semantically equivalent one; one that is thought to be less expensive to process. The authors analyze the possibilities of semantic optimization in a deductive database that includes recursive relations and, consequently, integrity constraints that include recursive literals. They propose a compiled approach to utilizing semantic knowledge in recursive query processing, assuming recursive queries are processed using compiled iterative methods. Also, a method of residue propagation for obtaining implied constraints that are often useful in optimization is presented.>
Sanggoo Lee, Jiawei Han 0001
ICDE1