By ANDREW ZITZELBERGER A Framework for Extraction Ontology Based Information Management.

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Presentation transcript:

by ANDREW ZITZELBERGER A Framework for Extraction Ontology Based Information Management

Problem Scientific Research  Wide range of documents  Require high precision (on extraction)

Solution Proposed Solution  Develop a tool for semi-automatic “pay-as-you-go” information extraction and integration that provides incrementally improved querying. Evaluation  Compute accuracy of the suggestions  Time saved using bootstrapped ontologies

Data Co-existence Data Integration Systems  Require semantic integration Dataspace Systems  Data co-existence approach  Immediate functionality  “pay-as-you-go” improvement

Dataspaces User Interface -Form Builder -Suggestions -Queries -Ontos -FOCIH -Schema Mapping - Meta-data - Keyword Search

System Local Storage - Set of Extraction Ontologies Form Builder – Hand annotation Personal Assistant - Suggestions for improvement Querying - Free form queries

Ontology

Forms Structure Keywords Values

Suggestions WordNet Data Frame Library RegExLib

Suggestions Reuse extraction ontology set (Ontos, FOCIH) Possible schema matching (Li Xu)

Contributions Framework for research focused semi-supervised data extraction and management Heuristics for computing suggestions based on regular expressions

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