Award Date

12-2010

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Kazem Taghva, Chair

Second Committee Member

Ajoy K. Datta

Third Committee Member

Laxmi P. Gewali

Graduate Faculty Representative

Muthukumar Venkatesan

Number of Pages

47

Abstract

The World Wide Web is a source of huge amount of unlabeled information spread across different sources in varied formats. This presents us with both opportunities and challenges in leveraging such large amount of unstructured data to build knowledge bases and to extract relevant information.

As part of this thesis, a semi-supervised logistic regression model called “Dual Iterative Pattern Relation Extraction” proposed by Sergey Brin is selected for further investigation. DIPRE presents a technique which exploits the duality between sets of patterns and relations to grow the target relation starting from a small sample.

This project built in JAVA using "Google AJAX Search API" includes designing, implementing and testing DIPRE approach in extracting various relationships from the web.

Keywords

Dual Iterative Pattern Relation Extraction (DIPRE); Machine Learning; Pattern Extraction; Pattern recognition systems; Search engines — Programming

Disciplines

Computer Sciences

File Format

pdf

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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