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Permanent link (DOI): https://doi.org/10.7939/R36Q1SR16

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Offline Strategies for Online Set Expansion Open Access

Descriptions

Other title
Subject/Keyword
database
index
set expansion
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhou, Kai
Supervisor and department
Rafiei, Davood (Computing Science)
Examining committee member and department
Rafiei, Davood (Computing Science)
Sander, Joerg (Computing Science)
Lu, Paul (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2016-01-19T09:04:07Z
Graduation date
2016-06
Degree
Master of Science
Degree level
Master's
Abstract
Set expansion aims at expanding a given query seed set into a larger and more complete set by adding elements that are likely to belong to the same grouping as the elements of the query set. This thesis studies the problem of efficient set expansion; in particular, given a collection of data sets, each corresponding to an object grouping, and a query set, we develop offline strategies to preprocess and organize the data sets such that online set expansion queries can be answered efficiently. We show how those strategies can be tuned for different set expansion semantics. We also evaluate our algorithms on a real dataset, constructed from the Wikipedia tables.
Language
English
DOI
doi:10.7939/R36Q1SR16
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
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File title: Introduction
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