Date of Award
Spring 2014
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
Committee Director
Michael L. Nelson
Committee Member
Michele C. Weigle
Committee Member
Hussein Abdel-Wahab
Committee Member
M'Hammed Abdous
Committee Member
Herbert Van de Sompel
Abstract
Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users' needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build ArcSys, a new service framework that extracts, preserves, and exposes APIs for the web archive corpus. The dissertation introduces a novel categorization technique to divide the archived corpus into four levels. For each level, we will propose suitable services and APIs that enable both users and third-party developers to build new interfaces. The first level is the content level that extracts the content from the archived web data. We develop ArcContent to expose the web archive content processed through various filters. The second level is the metadata level; we extract the metadata from the archived web data and make it available to users. We implement two services, ArcLink for temporal web graph and ArcThumb for optimizing the thumbnail creation in the web archives. The third level is the URI level that focuses on using the URI HTTP redirection status to enhance the user query. Finally, the highest level in the web archiving service framework pyramid is the archive level. In this level, we define the web archive by the characteristics of its corpus and building Web Archive Profiles. The profiles are used by the Memento Aggregator for query optimization.
Rights
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DOI
10.25777/fhmq-0e07
ISBN
9781303997006
Recommended Citation
AlSum, Ahmed.
"Web Archive Services Framework for Tighter Integration Between the Past and Present Web"
(2014). Doctor of Philosophy (PhD), Dissertation, Computer Science, Old Dominion University, DOI: 10.25777/fhmq-0e07
https://digitalcommons.odu.edu/computerscience_etds/27