EDBT 2026 Demo / reviewers in the wild / expert

Ayferi Kutlu

dblp:30/2128 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

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

Databases, data management, data science and information retrieval · 1Theory of computation · 1

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
2 papers
Spatial and temporal data management · 50% Query processing and optimization · 27% Data models and query languages · 23%

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

TopicWeightPapersLastEvidence papers
Query processing and optimization
similarity query processing		 0.012004
Bounded similarity querying for time-series data · Inf. Comput. 2004
Spatial and temporal data management
time series data		 0.012004
Bounded similarity querying for time-series data · Inf. Comput. 2004
Data models and query languages
constraint databases		 0.012003
The Constraint Database Framework: Lessons Learned from CQA/CDB · ICDE 2003
Spatial and temporal data management
spatial databases		 0.012003
The Constraint Database Framework: Lessons Learned from CQA/CDB · ICDE 2003

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

time series indexing · 0.0similarity search · 0.0linear constraint databases · 0.0
YearPublicationVenuePosition
2004 Bounded similarity querying for time-series data
Dina Q. Goldin, Todd D. Millstein, Ayferi Kutlu
 Inf. Comput.3
2003 The Constraint Database Framework: Lessons Learned from CQA/CDB
abstract
We describe our experience with CQA/CDB, a prototype rational linear constraint database. First, we show that the standard semantics of constraint databases lead to an anomaly when queried in the presence of missing attributes. In CQA/CDB, this anomaly is avoided by enriching the CDB relational schema, resulting in heterogenous databases. Then, we present spatial databases as a special case of heterogenous databases and extend constraint query algebras (CQAs) with two additional spatial operators, proving that the resulting language is safe for linear constraints.
Dina Q. Goldin, Ayferi Kutlu, Mingjun Song
 ICDE2