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Publication detail
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
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
https://link.springer.com/chapter/10.1007/978-3-319-68723-0_2
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" }