Object search: supporting structured queries in web search engines

Pham, Cuong K.

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https://hdl.handle.net/2142/16875 Copy

Description

Title

Object search: supporting structured queries in web search engines

Author(s)

Pham, Cuong K.

Issue Date

2010-08-20T18:00:32Z

Director of Research (if dissertation) or Advisor (if thesis)

Chang, Kevin C-C.

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(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.

Graduation Semester

2010-08

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http://hdl.handle.net/2142/16875

Copyright and License Information

Copyright 2010 by Cuong Kim Pham. All rights reserved.

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