Li, Xin
(2006)
INCREMENTAL QUERY PROCESSING IN INFORMATION FUSION SYSTEMS.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
This dissertation studies the methodology and techniques of information retrieval in fusion systems where information referring to same objects is assessed on the basis of data from multiple heterogeneous data sources. A wide range of important applications can be categorized as information fusion systems e.g. multisensor surveillance system, local search system, multisource medical diagnose system, and so on. Up to the time of this dissertation, most information retrieval methods in fusion systems are highly domain specific, and most query systems do not address fusion problem with enough efforts. In this dissertation, I describe a broadly applicable query based information retrieval approach in general fusion systems: user information needs are interpreted as fusion queries, and the query processing techniques e.g. source dependence graph (SDG), query refinement and optimization are described. Aiming to remove the query building bottleneck, a novel incremental query method is proposed, which can eliminate the accumulated complexity in query building as well as in query execution. Query pattern is defined to capture and reuse repeated structures in the incremental queries. Several new techniques for query pattern matching and learning are described in detail. Some important experiments in a real-world multisensor fusion system, i.e. the intelligent vehicle tracking (IVET) system, have been presented to validate the proposed methodology and techniques.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
2 June 2006 |
Date Type: |
Completion |
Defense Date: |
23 February 2006 |
Approval Date: |
2 June 2006 |
Submission Date: |
5 April 2006 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Computer Science |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
Incremental Query; Information Fusion; Query Pattern; Query Processing |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-04052006-145601/, etd-04052006-145601 |
Date Deposited: |
10 Nov 2011 19:34 |
Last Modified: |
15 Nov 2016 13:38 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/6767 |
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