ITEM METADATA RECORD
Title: Information extraction from structured documents using k-testable tree automaton inference
Authors: Kosala, Raymondus ×
Blockeel, Hendrik
Bruynooghe, Maurice
Van den Bussche, Jan #
Issue Date: Aug-2006
Publisher: Elsevier science bv
Series Title: Data & knowledge engineering vol:58 issue:2 pages:129-158
Abstract: Information extraction (IE) addresses the problem of extracting specific information from a collection of documents. Much of the previous work on IE from structured documents, such as HTML or XML, uses learning techniques that are based on strings, such as finite automata induction. These methods do not exploit the tree structure of the documents. A natural way to do this is to induce tree automata, which are like finite state automata but parse trees instead of strings. In this work, we explore induction of k-testable ranked tree automata from a small set of annotated examples. We describe three variants which differ in the way they generalize the inferred automaton. Experimental results on a set of benchmark data sets show that our approach compares favorably to string-based approaches. However, the quality of the extraction is still suboptimal. (c) 2005 Elsevier B.V. All rights reserved.
ISSN: 0169-023X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

Files in This Item:
File Status SizeFormat
41765.pdf Published 408KbAdobe PDFView/Open

 


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science