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Sung-Won Jung

dblp:85/5742 · DBLP profile ↗
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7ranked-venue papers
6as first author
0since 2021 · last 2007
—ORCID · none

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

Artificial intelligence and machine learning · 6 · 5 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-authorDatabases, data management, data science and information retrieval · 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.

Databases, data mining, and information retrieval
1 paper
Data mining · 87% Web and social media mining · 13%
Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › document understanding › table recognition
web table extraction
0.112006
A Scalable Hybrid Approach for Extracting Head Components from Web Tables · IEEE Trans. Knowl. Data Eng. 2006
Data mining › predictive modeling
classification
0.112006
A Scalable Hybrid Approach for Extracting Head Components from Web Tables · IEEE Trans. Knowl. Data Eng. 2006
Data mining › predictive modeling › classification
decision tree learning
0.112006
A Scalable Hybrid Approach for Extracting Head Components from Web Tables · IEEE Trans. Knowl. Data Eng. 2006
Web and social media mining
web mining
0.012006
A Scalable Hybrid Approach for Extracting Head Components from Web Tables · IEEE Trans. Knowl. Data Eng. 2006

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

heuristics · 0.1decision tree · 0.1
YearPublicationVenuePosition
2007 Part-of-Speech Tagging Using Word Probability Based on Category Patterns
Mi-young Kang, Sung-Won Jung, Kyung-soon Park, Hyuk-Chul Kwon
CICLing2
2007 Constructing Domain Ontology Using Structural and Semantic Characteristics of Web-Table Head
Sung-Won Jung, Mi-young Kang, Hyuk-Chul Kwon
IEA/AIE1
2006 A Machine Learning Based Approach for Separating Head from Body in Web-Tables
Sung-Won Jung, Hyuk-Chul Kwon
CICLing1
2006 A Scalable Hybrid Approach for Extracting Head Components from Web Tables
abstract
We have established a preprocessing method for determining the meaningfulness of a table to allow for information extraction from tables on the Internet. A table offers a preeminent clue in text mining because it contains meaningful data displayed in rows and columns. However, tables are used on the Internet for both knowledge structuring and document design. Therefore, we were interested in determining whether or not a table has meaningfulness that is related to the structural information provided at the abstraction level of the table head. Accordingly, we: 1) investigated the types of tables present in HTML documents, 2) established the features that distinguished meaningful tables from others, 3) constructed a training data set using the established features after having filtered any obvious decorative tables, and 4) constructed a classification model using a decision tree. Based on these features, we set up heuristics for table head extraction from meaningful tables, and obtained an F-measure of 95.0 percent in distinguishing meaningful tables from decorative tables and an accuracy of 82.1 percent in extracting the table head from the meaningful tables.
Sung-Won Jung, Hyuk-Chul Kwon
IEEE Trans. Knowl. Data Eng.1
2004 Mining Table Information on the Internet
Sung-Won Jung, Gi-deuk Han, Hyuk-Chul Kwon
IJCNLP1
2003 Extraction of Meaningful Tables from the Internet Using Decision Trees
Sung-Won Jung, Won-Hee Lee, Sang-Kyu Park, Hyuk-Chul Kwon
IEA/AIE1
2002 Effective Retrieval of Information in Tables on the Internet
Sung-Won Jung, Kyung-Hee Sung, Tae-Won Park, Hyuk-Chul Kwon
IEA/AIE1