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초록
Tables in Web pages are the main source of knowledge graphs because they contain summarised information. Since there are various ways to represent information in web tables, it is not easy to extract information efficiently. This paper proposes a method for extracting information from structured and unstructured web pages and a method for converting the extracted information into a knowledge graph. In particular, in order to construct a Korean knowledge graph, this paper introduces a method for extracting large table data from web pages that are written in Korean and expressing it in a graph. © 2020, Springer Nature Switzerland AG.
키워드
Knowledge creation; Knowledge extraction; Knowledge graph; Tabular data; Knowledge representation; Websites; Extract informations; Extracting information; Knowledge exploration; Knowledge graphs; Web tables; Data mining
- 제목
- Knowledge Exploration from Tables on the Web
- 저자
- Kim, H.
- 발행일
- 2020
- 유형
- Conference Paper
- 권
- 11609 LNCS
- 페이지
- 27 ~ 30
- 언어
- ENG
- 출판사
- Springer
- 발행국가
- 독일
- 분량
- 4 페이지
- ISSN
- P 0302-9743