A Case-Based Recognition of Semantic Structures in HTML Documents

Abstract

The recognition and extraction of semantic/logical structures in HTML documents are substantially important and difficult tasks for intelligent document processing. In this paper, we show that alignment is appropriate for recognizing characteristic semantic/logical structures of a series of HTML documents, within a framework of case-based reasoning. That is, given a series of HTML documents and a sample transformation from an HTML document into an XML format, then the alignment can identify semantic/logical structures in the remaining HTML documents of the series, by matching the text-block sequence of the remaining document with the one of the sample transformation. Several important properties of texts, such as continuity and sequentiality, can naturally be utilized by the alignment. The alignment technology can significantly improve the ability of the case-based transformation method which transforms a spatial/temporal series of HTML documents into machine-readable XML formats. Throughout experimental evaluations, we show that the case-based method with alignment achieved a highly accurate transformation of HTML documents into XML.

This research was supported partly by Grant-in-Aid from The Ministry of Education, Science and Culture of Japan. and also supported by The Telecommunications Advancement Foundation (TAF).