Publication detail

Information Extraction from the Web by Matching Visual Presentation Patterns

BURGET, R.

Original Title

Information Extraction from the Web by Matching Visual Presentation Patterns

Type

conference paper

Language

English

Original Abstract

The documents available in the World Wide Web contain large amounts of information presented in tables, lists or other visually regular structures. The published information is however usually not annotated explicitly or implicitly and its interpretation is left on a human reader. This makes the information extraction from web documents a challenging problem. Most existing approaches are based on a top-down approach that proceeds from the larger page regions to individual data records, which depends on different heuristics. We present an opposite bottom-up approach. We roughly identify the smallest data fields in the document and later, we refine this approximation by matching the discovered visual presentation patterns with the expected semantic structure of the extracted information. This approach allows to efficiently extract structured data from heterogeneous documents without any kind of additional annotations as we demonstrate experimentally on various application domains.

Keywords

web data integration, information extraction, structured record extraction, page segmentation, content classification, ontology mapping

Authors

BURGET, R.

Released

29. 10. 2017

Publisher

Springer International Publishing

Location

Kobe

ISBN

978-3-319-68722-3

Book

Knowledge Graphs and Language Technology: ISWC 2016 International Workshops: KEKI and NLP&DBpedia

Edition

Lecture Notes in Computer Science vol. 10579

Pages from

10

Pages to

26

Pages count

17

URL

BibTex

@inproceedings{BUT144386,
  author="Radek {Burget}",
  title="Information Extraction from the Web by Matching Visual Presentation Patterns",
  booktitle="Knowledge Graphs and Language Technology: ISWC 2016 International Workshops: KEKI and NLP&DBpedia",
  year="2017",
  series="Lecture Notes in Computer Science vol. 10579",
  pages="10--26",
  publisher="Springer International Publishing",
  address="Kobe",
  doi="10.1007/978-3-319-68723-0\{_}2",
  isbn="978-3-319-68722-3",
  url="https://link.springer.com/chapter/10.1007/978-3-319-68723-0_2"
}

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