Publication Details
Information Extraction from the Web by Matching Visual Presentation Patterns
web data integration, information extraction, structured record extraction, page
segmentation, content classification, ontology mapping
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.
@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"
}