Tree pattern inference and matching for wrapper induction on the World Wide Web
Name
56985415-MIT.pdf
Description
Full printable version
Size
7.35 MB
Format
Adobe PDF
Checksum (MD5)
ae07d7ff7b08b27b34c0927ee289a9d6
Author(s)
Hogue, Andrew William, 1978-
Advisor(s)
David R. Karger.
Date Issued
2004
Publisher
Massachusetts Institute of Technology
Abstract
We develop a method for learning patterns from a set of positive examples to retrieve semantic content from tree-structured data. Specifically, we focus on HTML documents on the World Wide Web, which contain a wealth of semantic information and have a useful underlying tree structure. A user provides examples of relevant data they wish to extract from a web site through a simple user interface in a web browser. To construct patterns, we use the notion of the edit distance between the subtrees represented by these examples to distill them into a more general pattern. This pattern may then be used to retrieve other instances of the selected data from the same page or other similar pages. By linking patterns and their components with semantic labels using RDF, we can create semantic "overlays" for Web information which are useful in such projects as the Semantic Web and the Haystack information management environment.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 103-106).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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