Computer Sciences Commons^™

Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo

Kno.e.sis Publications

Blogs, discussion forums and social networking sites are an excellent source for people's opinions on a wide range of topics. We examine the application of voting theory to "information mashups" - the combining and summarizing of data from the multitude of often-conflicting sources. This paper presents an information mashup in the music domain: a Top 10 artist chart based on user comments and listening behavior from several Web communities. We consider different voting systems as algorithms to combine opinions from multiple sources and evaluate their effectiveness using social welfare functions. Different voting schemes are found to work better in some …

Predicting The Longevity Of Dvdr Media By Periodic Analysis Of Parity, Jitter, And Ecc Performance Parameters, Daniel Patrick Wells

Theses and Dissertations

For the last ten years, DVD-R media have played an important role in the storage of large amounts of digital data throughout the world. During this time it was assumed that the DVD-R was as long-lasting and stable as its predecessor, the CD-R. Several reports have surfaced over the last few years questioning the DVD-R's ability to maintain many of its claims regarding archival quality life spans. These reports have shown a wide range of longevity between the different brands. While some DVD-Rs may last a while, others may result in an early and unexpected failure. Compounding this problem is …

Tools For A Preservation-Ready Web, Joan A. Smith, Michael L. Nelson

Computer Science Presentations

PDF of a powerpoint presentation from the National Digital Information Infrastructure and Preservation Program (NDIIPP) Partners Meeting, Washington D.C., July 9, 2008. Also available on Slideshare.

Dependence Of Binary Associations On Co-Occurrence Granularity In News Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik

Kno.e.sis Publications

We describe and formalize an approach to correlate binary associations (such as between entities and events, between persons and events, etc.) implied by News documents on the co-occurrence granularity (such as document-level, paragraph-level, sentence-level, etc.) of the corresponding text phrases in the documents. Specifically, we present both qualitative and quantitative characterization of searching News documents: former in terms of the nature of the content and the queries, and latter in terms of a metric obtained by adapting the notions of precision and recall. Specifically, the approach tries to reduce the manual effort required to analyze the News documents to compare …

Semantic Web: Promising Technologies, Current Applications & Future Directions, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Description Logic Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ – the basis for the ongoing standardisation of OWL 2 – can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ …

Boosting With Incomplete Information, Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao

Kno.e.sis Publications

In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we present a boosting approach that integrates features with incomplete information and those with complete information to form a strong classifier. By introducing hidden variables to model missing information, we form loss functions that combine fully labeled data with partially labeled data to effectively learn normalized and unnormalized models. The primal problems of the proposed optimization problems with these loss functions are provided to show their close relationship and the motivations behind them. …

On Profiling Blogs With Representative Entries, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun

Research Collection School Of Computing and Information Systems

With an explosive growth of blogs, information seeking in blogosphere becomes more and more challenging. One example task is to find the most relevant topical blogs against a given query or an existing blog. Such a task requires concise representation of blogs for effective and efficient searching and matching. In this paper, we investigate a new problem of profiling a blog by choosing a set of m most representative entries from the blog, where m is a predefined number that is application-dependent. With the set of selected representative entries, applications on blogs avoid handling hundreds or even thousands of entries …

Mapping The Multi-Tiered Impacts Of The Growth Of It Industries In India: A Combined Scale-And-Scope Externalities Perspective, Robert J. Kauffman, Ajay Kumar

Research Collection School Of Computing and Information Systems

Externalities occur among agglomerated firms. Scale externalities occur between firms in the same industry. Scope externalities occur when heterogeneous industries are collocated. Combined scale-and-scope externalities exist when the scale of one industry is beneficial to the growth of another collocated industry. In the Sein and Haridranath (2004) framework of information technology (IT) impacts on development, scale externalities correspond to second-order impacts, while combined scale and scope eternalities correspond to third-order impacts. We use an agglomeration perspective to explain the growth of IT industries in India. We study growth patterns of four specific IT industries: computer and peripheral equipment manufacturing, semiconductor …

A Framework For Trust And Distrust Networks, Krishnaprasad Thirunarayan

Kno.e.sis Publications

In this age of internet and electronic commerce it is becoming increasingly important to have and to manipulate information about the trustworthiness of the content or service providers in order to make informed decisions. This paper explores realistic models of trust and distrust based on partially ordered discrete values and proposes a framework, which is sensitive to local, relative ordering of values rather than their magnitudes. The framework distinguishes between direct and inferred trust, preferring direct information over possibly conflicting inferred information. It also represents ambiguity or inconsistency explicitly. The framework is capable of handling general trust and belief networks …

A Forgetting-Based Approach For Reasoning With Inconsistent Distributed Ontologies, Guilin Qi, Yimin Wang, Peter Haase, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In the context of multiple distributed ontologies, we are often confronted with the problem of dealing with inconsistency. In this paper, we propose an approach for reasoning with inconsistent distributed ontologies based on concept forgetting. We firstly define concept forgetting in description logics. We then adapt the notions of recoveries and preferred recoveries in propositional logic to description logics. Two consequence relations are then defined based on the preferred recoveries.

Graph Summaries For Subgraph Frequency Estimation, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman

Kno.e.sis Publications

A fundamental problem related to graph structured databases is searching for substructures. One issue with respect to optimizing such searches is the ability to estimate the frequency of substructures within a query graph. In this work, we present and evaluate two techniques for estimating the frequency of subgraphs from a summary of the data graph. In the first technique, we assume that edge occurrences on edge sequences are position independent and summarize only the most informative dependencies. In the second technique, we prune small subgraphs using a valuation scheme that blends information about their importance and estimation power. In both …

Defeasible Inference With Circumscriptive Owl Ontologies, Stephan Grimm, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The Web Ontology Language (OWL) adheres to the openworld assumption and can thus not be used for forms of nonmonotonic reasoning or defeasible inference, an acknowledged desirable feature in open Semantic Web environments. We investigate the use of the formalism of circumscriptive description logics (DLs) to realise defeasible inference within the OWL framework. By example, we demonstrate how reasoning with (restricted) circumscribed OWL ontologies facilitates various forms of defeasible inference, also in comparison to alternative approaches. Moreover, we sketch an extension to DL tableaux for handling the circumscriptive case and report on a preliminary implementation.

Empowering Translational Research Using Semantic Web Technologies, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Sa-Rest: Using Semantics To Empower Restful Services And Smashups With Better Interoperability And Mediation, Karthik Gomadam, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Dynamic And Agile Soa Using Sawsdl, Karthik Gomadam, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

A Framework To Support Spatial, Temporal And Thematic Analytics Over Semantic Web Data, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

Spatial and temporal data are critical components in many applications. This is especially true in analytical applications ranging from scientific discovery to national security and criminal investigation. The analytical process often requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF data model for analysis of thematic, spatial and temporal relationships between …

Automated Vector-To-Raster Image Registration, Boris Kovalerchuk, Peter Doucette, Gamal Seedahmed, Robert Brigantic, Michael Kovalerchuk, Brian Graff

Computer Science Faculty Scholarship

The variability of panchromatic and multispectral images, vector data (maps) and DEM models is growing. Accordingly, the requests and challenges are growing to correlate, match, co-register, and fuse them. Data to be integrated may have inaccurate and contradictory geo-references or not have them at all. Alignment of vector (feature) and raster (image) geospatial data is a difficult and time-consuming process when transformational relationships between the two are nonlinear. The robust solutions and commercial software products that address current challenges do not yet exist. In the proposed approach for Vector-to-Raster Registration (VRR) the candidate features are auto-extracted from imagery, vectorized, and …

Stress Test, M. Thulasidas

Research Collection School Of Computing and Information Systems

Ultimately, the risk factors that create stress in professional life do not generate any reward

The Cyber-Workplace – Identifying Liability Issues In The Information Age And Managing E-Risk, Nigel Wilson

Annual ADFSL Conference on Digital Forensics, Security and Law

The information age provides numerous opportunities for modern society but also presents significant challenges in identifying liability issues and in managing risk. Technological change has occurred rapidly and is continuing at the same time as other major trends and changes are taking place in society and, in particular, in the workplace. The prospect of global liability and the complexity of jurisdictional differences present a considerable hurdle to the uniform regulation of liability issues. General legislation and legal principles have been readily applied to the cyber-world and to modern business practices and the workplace. Where necessary, legislatures have introduced specific legislation …

Data Mining Techniques For Fraud Detection, Rekha Bhowmik

Annual ADFSL Conference on Digital Forensics, Security and Law

The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision tree-based algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models.

Keywords: Data Mining, Decision Tree, Bayesian Network, ROC …

Simple - Rethinking The Monolithic Approach To Digital Forensic Software, Craig Valli

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper outlines a collaborative project nearing completion between the sec.au Security Research Group at Edith Cowan University and Western Australian Police Computer Crime Squad. The primary goal of this project is to create a software tool for use by non-technical law enforcement officers during the initial investigation and assessment of an electronic crime scene. This tool will be designed as an initial response tool, to quickly and easily find, view and export any relevant files stored on a computer, establishing if further expert investigation of that computer is warranted. When fully developed, the tool will allow investigators unprecedented real …

How Virtualized Environments Affect Computer Forensics, Diane Barrett

Annual ADFSL Conference on Digital Forensics, Security and Law

Virtualized environments can make forensics investigation more difficult. Technological advances in virtualization tools essentially make removable media a PC that can be carried around in a pocket or around a neck. Running operating systems and applications this way leaves very little trace on the host system. This paper will explore all the newest methods for virtualized environments and the implications they have on the world of forensics. It will begin by describing and differentiating between software and hardware virtualization. It will then move on to explain the various methods used for server and desktop virtualization. Next, it will describe the …

The Virtual Digital Forensics Lab - Expanding Law Enforcement Capabilities, Mark Mccoy, Sean A. Ensz

Annual ADFSL Conference on Digital Forensics, Security and Law

Law enforcement is attempting to respond to the growing and complex need to examine all manner of digital evidence using stand-alone forensic workstations and limited storage solutions. Digital forensic investigators often find their cases stalled by cumbersome and inflexible technology limiting their effectiveness. The Virtual Digital Forensics Lab (VDFL) is a new concept that applies existing enterprise host, storage, and network virtualization technologies to current forensic investigative methods. This paper details the concept of the VDFL, the technology solutions it employs, and the flexibility it provides for digital forensic investigators.

Keywords: Virtual Digital Forensics, digital forensic investigations, law enforcement, virtual …

Digital Forensic Certification Versus Forensic Science Certification, Nena Lim

Annual ADFSL Conference on Digital Forensics, Security and Law

Companies often rely on certifications to select appropriate individuals in disciplines such as accounting and engineering. The general public also tends to have confidence in a professional who has some kinds of certification because certification implies a standard of excellence and that the individual has expert knowledge in a specific discipline. An interesting question to the digital forensic community is: How is a digital forensic certification compared to a forensic science certification? The objective of this paper is to compare the requirements of a digital forensic certification to those of a forensic science certification. Results of the comparison shed lights …

Ws3: International Workshop On Context-Enabled Source And Service Selection, Integration And Adaptation, Quan Z. Sheng, Ullas Nambiar, Amit P. Sheth, Biplav Srivastava, Zakaria Maamr, Said Elnaffar

Kno.e.sis Publications

This write-up provides a summary of the International Workshop on Context enabled Source and Service Selection, Integration and Adaptation (CSSSIA 2008), organized in conjunction with WWW2008, at Beijing, China on April 22nd 2008. We outline the motivation for organizing the work-shop, briefly describe the organizational details and program of the workshop, and summarize each of the papers accepted by the workshop. More information about the workshop can be found at http://www.cs.adelaide.edu.au/∼csssia08/.

Rdb2rdf: Incorporating Domain Semantics In Structured Data, Satya S. Sahoo

Kno.e.sis Publications

No abstract provided.

Artist Ranking Through Analysis Of On-Line Community Comments, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Christine Robson, Nachiketa Sahoo

Kno.e.sis Publications

We describe an approach to measure the popularity of music tracks, albums and artists by analyzing the comments of music listeners in social networking online communities such as MySpace. This measure of popularity appears to be more accurate than the traditional measure based on album sales figures, as demonstrated by our focus group study. We faced many challenges in our attempt to generate a popularity ranking from the user comments on social networking sites, e.g., broken English sentences, comment spam, etc. We discuss the steps we took to overcome these challenges and describe an end to end system for generating …

After The System Upgrade Or Migration: A Cataloging Checklist, Sheryl Stump, Rick Torgerson

The Southeastern Librarian

At present. integrated library system (ILS) upgrades and migrations seem to be coming faster and more frequently. The reasons for this trend are many. among them being: 1) hardware upgrades are common due to the need for more memory to run the software; 2) software upgrades and migrations are desired because of the promise of new or improved features; 3) changes in system vendor ownership can affect changes in their software; 4) software and hardware upgrades are needed due to the advanced age of either or both; and 5) system upgrades on a yearly basis may be necessary to prevent …

Volume 01, Jessica Fields, Stephanie Neeley, Derek W. Hambright, Mary E. Lehman, Andrew R. Grzankowski, Zachary Johnson, Boone M. Prentice, Ashley M. Swandby, Victoria Morgan, Katie Williamson, Kristine G. Bender, Katelyn N. Romaine, D. Nicole Swann, Jessica Fox, Mike Mcateer, Alex Grabiec, Laura Nodtvedt, Nick Costa, Rachel Wolfe, Zack Dalton

Incite: The Journal of Undergraduate Scholarship

Introduction from Dean Dr. Charles Ross

Three Decades of Digging: Undergraduate Archeology at Longwood by Jessica Fields and Stephanie Neeley

Interactions of Allelopathy and Heat Stress in Plants by Derek W. Hambright and Mary E. Lehman

Inertial Electrostatic Confinement D-D Fusion Device: Construction and Simulation by Andrew R. Grzankowski

Shackled Nim by Zachary Johnson

Development of GC-MS and Chemometric Methods for the Analysis of Accelerants in Arson Cases by Boone M. Prentice

A Comparison of Image Analysis Methods in cDNA Microarrays by Ashley M. Swandby

Perceived Sexual Activity of Short and Long-Term Relationships by Victoria Morgan and Katie Williamson

Elderly …