Exploiting a Web of Semantic Data for Interpreting Tables

No Thumbnail Available

Files

486.ppt (771 KB)

Links to Files

https://ebiquity.umbc.edu/paper/html/id/474/Exploiting-a-Web-of-Semantic-Data-for-Interpreting-Tables

Permanent Link

http://hdl.handle.net/11603/11958

Collections

UMBC Computer Science and Electrical Engineering Department
UMBC Faculty Collection
UMBC Student Collection

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0002-6593-1792
 https://orcid.org/0000-0002-8641-3193

Date

2010-04-26

Type of Work

conference papers and proceedings
presentations (communicative events)
Text

Department

Program

Citation of Original Publication

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Semantic Web
linked data
human language technology
information retrieval
UMBC Ebiquity Research Group

Abstract

Much of the world’s knowledge is contained in structured documents like spreadsheets, database relations and tables in documents found on the Web and in print. The information in these tables might be much more valuable if it could be appropriately exported or encoded in RDF, making it easier to share, understand and integrate with other information. This is especially true if it could be linked into the growing linked data cloud. We describe techniques to automatically infer a (partial) semantic model for information in tables using both table headings, if available, and the values stored in table cells and to export the data the table represents as linked data. The techniques have been prototyped for a subset of linked data that covers the core of Wikipedia.