Date of Award
Summer 8-2010
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Committee Director
Mohammad Zubair
Committee Member
Harris Wu
Committee Member
Kurt Maly
Call Number for Print
Special Collections LD4331.C65 L5 2010
Abstract
We have developed a system that improves access to a large, growing image collection by allowing users to collaboratively build a global faceted (multi-perspective) classification schema. We are extending our system to support both global and local schemas, where global schema provides a complete and uniform view of the collection whereas local schema provides a personal, possibly incomplete and idiosyncratic view of the collection. We argue that although users usually focus on their personal schemas, it is still desirable to have a global schema for the entire collection even if such local schemas are available. In order to keep the global schema updated in time. there is a need to develop a way to merge latest local schemas into the global one. This study focuses on such schema merging problem. To the best of our knowledge, it is the first attempt to solve the problem. We present a general standard of characterizing good schema merging algorithms and argue that three types of information, i.e., document content information, document categorization information and category linguistic information, must be considered in a good schema merging algorithm. We discuss the feasibility of applying existing data integration methods to solve the schema merging problem and provide ways to turn these methods into schema merging algorithms. We also propose a new, potentially good schema merging algorithm.
Rights
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DOI
10.25777/5z27-vy33
Recommended Citation
Li, Jianxiang.
"Merging Schemas in a Collaborative Faceted Classification System"
(2010). Master of Science (MS), Thesis, Computer Science, Old Dominion University, DOI: 10.25777/5z27-vy33
https://digitalcommons.odu.edu/computerscience_etds/162