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Description
Title: | Object search: supporting structured queries in web search engines |
Author(s): | Pham, Cuong K. |
Advisor(s): | Chang, Kevin C-C. |
Department / Program: | Computer Science |
Discipline: | Computer Science |
Degree Granting Institution: | University of Illinois at Urbana-Champaign |
Degree: | M.S. |
Genre: | Thesis |
Subject(s): | semantics
web search engines learning to rank information retrieval structured query object search |
Abstract: | As the web evolves, increasing quantities of structured information is embedded in web pages in disparate formats. For example, a digital camera’s description may include its price and megapixels whereas a professor’s description may include her name, university, and research interests. Both types of pages may include additional ambiguous information. General search engines (GSEs) do not support queries over these types of data because they ignore the web document semantics. Conversely, describing requisite semantics through structured queries into databases populated by information extraction (IE) techniques are expensive and not easily adaptable to new domains. This paper describes a methodology for rapidly developing search engines capable of answering structured queries over unstructured corpora by utilizing machine learning to avoid explicit IE. We empirically show that with minimum additional human effort, our system outperforms a GSE with respect to structured queries with clear object semantics. |
Issue Date: | 2010-08-20 |
URI: | http://hdl.handle.net/2142/16875 |
Rights Information: | Copyright 2010 by Cuong Kim Pham. All rights reserved. |
Date Available in IDEALS: | 2010-08-20 |
Date Deposited: | 2010-08 |
This item appears in the following Collection(s)
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Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois -
Dissertations and Theses - Computer Science
Dissertations and Theses from the Dept. of Computer Science