A clustering approach to extract data from HTML tables

نویسندگان

چکیده

HTML tables have become pervasive on the Web. Extracting their data automatically is difficult because finding relationships between cells not trivial due to many different layouts, encodings, and formats available. In this article, we introduce Melva, which an unsupervised domain-agnostic proposal extract from without requiring any external knowledge bases. It relies a clustering approach that helps make label apart value establish relationships. We compared Melva four competitors more than 3000 Wikipedia Dresden Web Table Corpus. The conclusion our 21.70% better best competitor equals supervised regarding effectiveness, but it 99.14% efficiency.

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ژورنال

عنوان ژورنال: Information Processing and Management

سال: 2021

ISSN: ['0306-4573', '1873-5371']

DOI: https://doi.org/10.1016/j.ipm.2021.102683