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Hyunki Kim

dblp:50/351 · DBLP profile ↗
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10ranked-venue papers
4as first author
0since 2021 · last 2018
0000-0003-2292-5584ORCID · corroborated

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

Databases, data management, data science and information retrieval · 5 · 1 first-authorArtificial intelligence and machine learning · 3 · 1 first-authorSystems, architecture and hardware · 1Software engineering, systems software and programming languages · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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
Information extraction and text analysis · 100%
Databases, data mining, and information retrieval
1 paper
Machine learning and data management · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning and data management
optimization for machine learning
0.112008
Fixed-threshold SMO for Joint Constraint Learning Algorithm of Structural SVM · SIGIR 2008
Mathematical optimization › continuous optimization › nonlinear optimization
quadratic programming
0.012008
Fixed-threshold SMO for Joint Constraint Learning Algorithm of Structural SVM · SIGIR 2008

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

structural SVM · 0.2joint constraint learning · 0.2fixed-threshold SMO · 0.2
YearPublicationVenuePosition
2018 Risk assessment of mobile applications based on machine learned malware dataset
Hyunki Kim, Taejoo Cho, Gail-Joon Ahn, Jeong Hyun Yi
Multim. Tools Appl.1
2016 Anti-debugging scheme for protecting mobile apps on android platform
Haehyun Cho, Jongsu Lim, Hyunki Kim, Jeong Hyun Yi
J. Supercomput.3
2014 Balanced Korean Word Spacing with Structural SVM
abstract
Most studies on statistical Korean word spacing do not utilize the information provided by the input sentence and assume that it was completely concatenated.This makes the word spacer ignore the correct spaced parts of the input sentence and erroneously alter them.To overcome such limit, this paper proposes a structural SVM-based Korean word spacing method that can utilize the space information of the input sentence.The experiment on sentences with 10% spacing errors showed that our method achieved 96.81% F-score, while the basic structural SVM method only achieved 92.53% F-score.The more the input sentence was correctly spaced, the more accurately our method performed.
Changki Lee, Edward Choi 0003, Hyunki Kim
EMNLP3
2014 Open domain question answering using Wikipedia-based knowledge model
Pum-Mo Ryu, Myung-Gil Jang, Hyunki Kim
Inf. Process. Manag.3
2013 Automatic Korean word spacing using Pegasos algorithm
Changki Lee, Hyunki Kim
Inf. Process. Manag.2
2011 Named entity recognition using a modified Pegasos algorithm
abstract
In this paper, we describe a named entity recognition using a modified Pegasos algorithm for structural SVMs. We show the modified Pegasos algorithm significantly outperformed CRFs and the training time for the modified Pegasos algorithm is reduced 17-26 times compared to CRFs.
Changki Lee, Pum-Mo Ryu, Hyunki Kim
CIKM3
2010 Generating a meta-DL by federating search on OAI and non-OAI servers
Hyunki Kim, Chee-Yoong Choo, Su-Shing Chen
J. Intell. Inf. Syst.1
2009 Associative Naïve Bayes classifier: Automated linking of gene ontology to medline documents
Hyunki Kim, Su-Shing Chen
Pattern Recognit.1
2008 Fixed-threshold SMO for Joint Constraint Learning Algorithm of Structural SVM
abstract
In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for a joint constraint learning algorithm of structural classification SVM problems. Because FSMO uses the fact that the joint constraint formulation of structural SVM has b=0, FSMO breaks down the quadratic programming (QP) problems of structural SVM into a series of smallest QP problems, each involving only one variable. By using only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection.
Changki Lee, Hyunki Kim, Myung-Gil Jang
SIGIR2
1996 OOHS: an Object-Oriented Hypermedia System
abstract
In this paper, we design a new hypermedia markup language using SGML and implement an object-oriented hypermedia system on top of the Postgres. Compared with the conventional systems, our hypermedia system has some advantages. First, since our hypermedia markup language is designed using SGML, the language can interchange documents in a system-independent manner and can support content-based and structure-based retrieval. Second, since we apply an object-oriented paradigm to modeling hypermedia data and links, we can inherit the properties and methods of the object-oriented model. Finally, our hypermedia system can provide database management system functions such as query processing, transaction management, storage management, security, crash recovery, and version control of structured document components as separate objects.
Hyunki Kim, Hakgene Shin, Jae-Woo Chang
COMPSAC1