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Pavan K. Chowdary

dblp:12/4159 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

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

Databases, data management, data science and information retrieval · 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
1 paper
Query processing and optimization · 46% Data models and query languages · 23% Indexing and storage engines · 23%

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

TopicWeightPapersLastEvidence papers
Indexing and storage engines
metric space indexing
0.112006
On Pushing Multilingual Query Operators into Relational Engines · ICDE 2006
Query processing and optimization › query optimization
query optimizer integration
0.112006
On Pushing Multilingual Query Operators into Relational Engines · ICDE 2006
Information retrieval › cross-language information retrieval
cross-lingual matching
0.012006
On Pushing Multilingual Query Operators into Relational Engines · ICDE 2006
YearPublicationVenuePosition
2006 On Pushing Multilingual Query Operators into Relational Engines
abstract
To effectively support today’s global economy, database systems need to manage data in multiple languages simultaneously. While current database systems do support the storage and management of multilingual data, they are not capable of querying across different natural languages. To address this lacuna, we have recently proposed two cross-lingual functionalities, LexEQUAL[13] and SemEQUAL[14], for matching multilingual names and concepts, respectively. In this paper, we investigate the native implementation of these multilingual functionalities as first-class operators on relational engines. Specifically, we propose a new multilingual storage datatype, and an associated algebra of the multilingual operators on this datatype. These components have been successfully implemented in the PostgreSQL database system, including integration of the algebra with the query optimizer and inclusion of a metric index in the access layer. Our experiments demonstrate that the performance of the native implementation is up to two orders-of-magnitude faster than the corresponding outsidethe- server implementation. Further, these multilingual additions do not adversely impact the existing functionality and performance. To the best of our knowledge, our prototype represents the first practical implementation of a crosslingual database query engine.
A. Kumaran 0001, Pavan K. Chowdary, Jayant R. Haritsa
ICDE2