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Deepak Murthy

dblp:13/7033 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1998
—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
Information retrieval · 67% Data integration and cleaning · 33%

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

TopicWeightPapersLastEvidence papers
Information retrieval › image retrieval
content-based image retrieval
0.011998
Global Integration of Visual Databases · ICDE 1998
Data integration and cleaning
database integration
0.011998
Global Integration of Visual Databases · ICDE 1998
Information retrieval › query formulation
visual query
0.011998
Global Integration of Visual Databases · ICDE 1998

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

metadata matching · 0.0feature extraction · 0.0
YearPublicationVenuePosition
1998 Global Integration of Visual Databases
abstract
Different visual databases have been designed in various locations. The global integration of such databases can enable users to access data across the world in a transparent manner. In this paper, we investigate an approach to the design and creation of an integrated information system which supports global visual query access to various visual databases over the Internet. Specifically, a metaserver, including a hierarchical metadatabase, a metasearch agent and a query manager, is designed to support such an integration. The metadatabase houses abstracted data about individual remote visual databases. To support visual content-based queries, the abstracted data in the metadatabase reflect the semantics of each visual database. The query manager extracts the feature contents from the queries. The metasearch agent processes the queries by matching their feature contents with the metadata. A list of relevant database sites is derived for efficient retrieval of the query in the selected databases. The performance of the system is refined based on the user's feedback. The proposed system is implemented using Java in a Web-based environment.
Wendy Chang, Deepak Murthy, Aidong Zhang 0001, Tanveer F. Syeda-Mahmood
ICDE2