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Keunjoo Kwon

dblp:32/1141 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Databases, data management, data science and information retrieval · 3Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 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.

Artificial intelligence
1 paper
Representation and self-supervised learning · 50% Image recognition and object detection · 50%
Databases, data mining, and information retrieval
2 papers
Indexing and storage engines · 81% Transaction processing and concurrency control · 19%

Topics — the 7 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Representation and self-supervised learning › representation learning › metric learning
deep metric learning
0.312018
Attention-Based Ensemble for Deep Metric Learning · ECCV (1) 2018
Computer vision › Image recognition and object detection
image retrieval
0.312018
Attention-Based Ensemble for Deep Metric Learning · ECCV (1) 2018
Indexing and storage engines
in-memory index
0.022001
Optimizing Multidimensional Index Trees for Main Memory Access · SIGMOD Conference 2001
Cache-Conscious Concurrency Control of Main-Memory Indexes on Shared-Memory Multiprocessor Systems · VLDB 2001
Indexing and storage engines › in-memory index
cache-efficient index
0.012001
Optimizing Multidimensional Index Trees for Main Memory Access · SIGMOD Conference 2001
Indexing and storage engines
multidimensional indexing
0.012001
Optimizing Multidimensional Index Trees for Main Memory Access · SIGMOD Conference 2001
Indexing and storage engines › spatial index
r-tree
0.012001
Optimizing Multidimensional Index Trees for Main Memory Access · SIGMOD Conference 2001
Memory systems
memory-efficient data structures
0.012001
Cache-Conscious Concurrency Control of Main-Memory Indexes on Shared-Memory Multiprocessor Systems · VLDB 2001

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

ensemble learning · 0.3attention mechanism · 0.3shared-memory multiprocessors · 0.1cache-conscious indexing · 0.1
YearPublicationVenuePosition
2018 Attention-Based Ensemble for Deep Metric Learning
Wonsik Kim, Bhavya Goyal, Kunal Chawla, Keunjoo Kwon
ECCV (1)5
2003 Performance Evaluation of Main-Memory R-tree Variants
Sangyong Hwang, Keunjoo Kwon, Sang Kyun Cha, Byung Suk Lee 0001
SSTD2
2001 Optimizing Multidimensional Index Trees for Main Memory Access
abstract
Recent studies have shown that cache-conscious indexes such as the CSB+-tree outperform conventional main memory indexes such as the T-tree. The key idea of these cache-conscious indexes is to eliminate most of child pointers from a node to increase the fanout of the tree. When the node size is chosen in the order of the cache block size, this pointer elimination effectively reduces the tree height, and thus improves the cache behavior of the index. However, the pointer elimination cannot be directly applied to multidimensional index structures such as the R-tree, where the size of a key, typically, an MBR (minimum bounding rectangle), is much larger than that of a pointer. Simple elimination of four-byte pointers does not help much to pack more entries in a node.
Sang Kyun Cha, Keunjoo Kwon
SIGMOD Conference3
2001 Cache-Conscious Concurrency Control of Main-Memory Indexes on Shared-Memory Multiprocessor Systems
Sang Kyun Cha, Sangyong Hwang, Keunjoo Kwon
VLDB4