UMBC ebiquity

OWLIR: Information Retrieval On The Semantic Web

Status: Past project

Project Description:

Information in the web is presented in human understandable form .Current search engines operate on huge databases and the information retrieval techniques are keyword based indexes on Textual Data.So,not all retrieved documents answer a user's query and is limited in its automated inference capability.

We envision the future web as pages containing both text and semantic markup.We describe an approach for information retrieval over documents that consist of both free text and semantically enriched markup statements in DAML+OIL. These statements provide both structured and semi-structured information about the documents and their content. Our approach allows inferencing to be done over this information at several points: when a document is indexed, when a query is processed and when query results are evaluated. To validate our approach we have implemented a working prototype, which is based on a version of the SIRE information retrieval system and uses a semantic web inferencing system implemented using DAMLJessKB.

Start Date: December 2000

End Date: May 2003

Faculty:
R. Scott Cost
Anupam Joshi
Yun Peng

Students:
Haripriya Purushothaman
Urvi Shah

Collaborators:
James Mayfield

Sponsors:
DARPA

 

There is 1 associated publication:  Hide the list...

1 Refereed Publication

2002

1. Urvi Shah et al., "Information retrieval on the semantic web", InProceedings, The ACM Conference on Information and Knowledge Management, November 2002, 2731 downloads.

 

There are 0 associated resources:  Hide the list...

 

Research Areas:
 Semantic Web