This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81863
Description
Title
Challenges in Managing Information Extraction
Author(s)
Shen, Warren H.
Issue Date
2009
Doctoral Committee Chair(s)
Doan, AnHai
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
In this dissertation, we develop solutions to the key challenges mentioned above. First, we develop a declarative framework that can help make it easier for developers to write and understand IE programs, and show how to automatically optimize IE programs written in this framework to reduce runtime. Next, given that relational database systems (RDBMSs) were designed to store and process large data sets, we study the benefits and limitations of employing RDBMSs for storing and processing data in IE applications. Finally, we extend our declarative framework to enable best-effort IE, allowing developers to more easily write and refine approximate IE programs. A key idea underlying these solutions is that many of the principles behind RDBMSs for managing structured data can be extended to IE for managing unstructured data.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
