Creating a Large-Scale Digital Library for Georeferenced Information

Persistent Link:
http://hdl.handle.net/10150/105172
Title:
Creating a Large-Scale Digital Library for Georeferenced Information
Author:
Zhu, Bin; Ramsey, Marshall C.; Ng, Tobun Dorbin; Chen, Hsinchun; Schatz, Bruce R.
Citation:
Creating a Large-Scale Digital Library for Georeferenced Information 1999-07, 5(7/8) D-Lib Magazine
Journal:
D-Lib Magazine
Issue Date:
Jul-1999
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105172
Submitted date:
2004-09-04
Abstract:
Digital libraries with multimedia geographic content present special challenges and opportunities in today's networked information environment. One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, concept-based, geographic information retrieval. Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype that integrates multiple knowledge sources (textual, image, and numerical) to support concept-based geographic information retrieval. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This paper suggests a framework for developing a complete GKRS-based system and describes in detail the prototype system that has been developed so far.
Type:
Journal Article (On-line/Unpaginated)
Language:
en
Keywords:
Geographic Digital Libraries; Geographic Information Science; Digital Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; Geospatial Knowledge Representation System; GKRS

Full metadata record

DC FieldValue Language
dc.contributor.authorZhu, Binen_US
dc.contributor.authorRamsey, Marshall C.en_US
dc.contributor.authorNg, Tobun Dorbinen_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorSchatz, Bruce R.en_US
dc.date.accessioned2004-09-04T00:00:01Z-
dc.date.available2010-06-18T23:20:34Z-
dc.date.issued1999-07en_US
dc.date.submitted2004-09-04en_US
dc.identifier.citationCreating a Large-Scale Digital Library for Georeferenced Information 1999-07, 5(7/8) D-Lib Magazineen_US
dc.identifier.urihttp://hdl.handle.net/10150/105172-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractDigital libraries with multimedia geographic content present special challenges and opportunities in today's networked information environment. One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, concept-based, geographic information retrieval. Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype that integrates multiple knowledge sources (textual, image, and numerical) to support concept-based geographic information retrieval. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This paper suggests a framework for developing a complete GKRS-based system and describes in detail the prototype system that has been developed so far.en_US
dc.format.mimetypetext/htmlen_US
dc.language.isoenen_US
dc.subjectGeographic Digital Librariesen_US
dc.subjectGeographic Information Scienceen_US
dc.subjectDigital Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherGeospatial Knowledge Representation Systemen_US
dc.subject.otherGKRSen_US
dc.titleCreating a Large-Scale Digital Library for Georeferenced Informationen_US
dc.typeJournal Article (On-line/Unpaginated)en_US
dc.identifier.journalD-Lib Magazineen_US
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