University of Illinois Urbana-Champaign

Object search: supporting structured queries in web search engines

Pham, Cuong K.

Content Files
1_Pham_KimCuong.pdf

Permalink

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

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
Date of Ingest
2010-08-20T18:00:32Z
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
Permalink
http://hdl.handle.net/2142/16875
Copyright and License Information
Copyright 2010 by Cuong Kim Pham. All rights reserved.

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