Guangshun Chen

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2ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none

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

Databases, data management, data science and information retrieval · 2

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.

Computer graphics and multimedia
2 papers
Visualization and visual analytics · 94% Multimedia analysis and retrieval · 6%
Databases, data mining, and information retrieval
2 papers
Query processing and optimization · 100%

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

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
data exploration
0.021997
DEVise: Integrated Querying and Visual Exploration of Large Datasets (Demo Abstract) · SIGMOD Conference 1997
DEVise: Integrated Querying and Visualization of Large Datasets · SIGMOD Conference 1997
Visualization and visual analytics › interactive visualization
visual querying
0.021997
DEVise: Integrated Querying and Visual Exploration of Large Datasets (Demo Abstract) · SIGMOD Conference 1997
DEVise: Integrated Querying and Visualization of Large Datasets · SIGMOD Conference 1997
Visualization and visual analytics › scientific visualization › multiscale visualization
level-of-detail visualization
0.011997
DEVise: Integrated Querying and Visual Exploration of Large Datasets (Demo Abstract) · SIGMOD Conference 1997

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

visual presentation · 0.0interactive exploration · 0.0data visualization · 0.0data exploration · 0.0
YearPublicationVenuePosition
1997 DEVise: Integrated Querying and Visualization of Large Datasets
abstract
DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentation of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework is being implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups.
Miron Livny, Raghu Ramakrishnan 0001, Kevin S. Beyer, Guangshun Chen, Donko Donjerkovic, Shilpa Lawande, Jussi Myllymaki, R. Kent Wenger
SIGMOD Conference4
1997 DEVise: Integrated Querying and Visual Exploration of Large Datasets (Demo Abstract)
abstract
DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework, implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups, makes several contributions. In particular, it combines support for extended relational queries with powerful data visualization features. Datasets much larger than available main memory can be handled—DEVise is currently being used to visualize datasets well in excess of 100MB—and data can be interactively examined at several levels of detail: all the way from meta-data summarizing the entire dataset, to large subsets of the actual data, to individual data records. Combining querying (in general, data processing) with visualizations gives us a very versatile tool, and presents several novel challenges.
Miron Livny, Raghu Ramakrishnan 0001, Kevin S. Beyer, Guangshun Chen, Donko Donjerkovic, Shilpa Lawande, Jussi Myllymaki, R. Kent Wenger
SIGMOD Conference4