Databases and Information Systems Commons^™

Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth

Kno.e.sis Publications

In this paper we discuss the collection, semantic annotation and analysis of real-time social signals from micro-blogging data. We focus on users interested in analyzing social signals collectively for sensemaking. Our proposal enables flexibility in selecting subsets for analysis, alleviating information overload. We define an architecture that is based on state-of-the-art Semantic Web technologies and a distributed publish subscribe protocol for real time communication. In addition, we discuss our method and application in a scenario related to the health care reform in the United States.

Continuous Semantics To Analyze Real-Time Data, Amit P. Sheth, Christopher Thomas, Pankaj Mehra

Kno.e.sis Publications

Increasingly we are presented with dynamic domains involved in social, mobile, and sensor webs. Such domains are spontaneous (arising suddenly), follow a period of rapid evolution, involving real-time or near real-time data, involve many distributed participants and diverse viewpoints involving topical or contentious subjects, and involve feature context colored by local knowledge and sociocultural backgrounds. This article present continuous semantics can help us model such dynamic domains and analyze the related real-time data. Capabilities include crating dynamic domain model by mining social data, and using dynamic models for semantic analysis of real-time data.

The Role Of An Effective It Intervention For Microenterprises, Changsoo Song, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Information technology (IT) interventions for micro-enterprises are fragmented and their approach lacks theoretical foundations. While various researchers have conducted studies on the effects of IT adoption in micro-enterprises, little research has been conducted to explain critical aspects of an effective IT intervention for micro-enterprises from a theoretical perspective. This study aims to fill this gap and empirically investigate how IT interventions can effectively facilitate the process of IT adoption by micro-enterprises. This paper suggests that effective IT interventions may have considerable potential for facilitating IT adoption among micro-enterprises across the United States and the world. Following an analysis of four …

Information Technology Adoption In Latin American Microenterprises, Travis Good, Mehruz Kamal, Sajda Qureshi, Nancy Jimenez

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The majority of businesses in developing regions across the world are microenterprises. In recent years, this form of business has been particularly resilient to economic downturns. While microenterprises are the least likely to succeed, when they do, their growth increases by a factor of 3.4% when they adopt technology. However, the challenges faced by microenterprises make it very difficult for them to adopt technology successfully. Existing theoretical models of ICT adoption have centered on intent to adopt in large organizations, and thus lack applicability to microenterprises, wherein the intent to adopt is an individual decision. This paper builds on prior …

Racial/Ethnic Health Disparities In Northeast Ohio, Mark Salling, Joseph Ahern

All Maxine Goodman Levin School of Urban Affairs Publications

Racial/Ethnic Health Disparities in Northeast Ohio, Planning & Action, The Center for Community Solutions, Vol. 63, No. 4 (July), 2010, pp. 12-15.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 1: Summary Report, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Census 2010 And Human Services And Community Development, Mark Salling, Jenita Mcgowan

All Maxine Goodman Levin School of Urban Affairs Publications

Census 2010 and Human Services and Community Development, Planning & Action, The Center for Community Solutions, Vol. 63, No. 2 (March), 2010, pp 1-4.

Recommender System For Audio Recordings, Jong Seo Lee

Master's Theses

Nowadays the largest E-commerce or E-service websites offer millions of products for sale. A Recommender system is defined as software used by such websites for recommending commercial or noncommercial product items to users according to the users’ tastes. In this project, we develop a recommender system for a private multimedia web service company. In particular, we devise three recommendation engines using different data filtering methods – named weighted-average, K-nearest neighbors, and item-based – which are based on collaborative filtering techniques, which work by recording user preferences on items and by anticipating the future likes and dislikes of users by comparing …

Genbank, Dennis A. Benson, Ilene Karasch-Mizrachi, David J. Lipman, James Ostell, Eric W. Sayers

Harold W. Manter Laboratory of Parasitology: Library Materials

GenBank(R) is a comprehensive database that contains publicly available nucleotide sequences for more than 380,000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system that integrates data …

Mining Antagonistic Communities From Social Networks, Kuan Zhang

Dissertations and Theses Collection (Open Access)

In this thesis, we examine the problem of mining antagonistic communities from social networks. In social networks, people with opposite opinions normally behave differently and form sub-communities each of which containing people sharing some common behaviors. In one scenario, people with opposite opinions show differences in their views on a set of items. Another scenario is people explicitly expressing whom they agree with, like or trust as well as whom they disagree with, dislike or distrust. We defined the indirect and direct antagonistic groups based on the two scenarios. We have developed algorithms to mine the two types of antagonistic …

Applying Soft Cluster Analysis Techniques To Customer Interaction Information, Randall E. Duran, Li Zhang, Tom Hayhurst

Research Collection School Of Computing and Information Systems

The number of channels available for companies and customers to communicate with one another has increased dramatically over the past several decades. Although some market segmentation efforts utilize high-level customer interaction statistics, in-depth information regarding customers’ use of different communication channels is often ignored. Detailed customer interaction information can help companies improve the way that they market to customers by taking into consideration customers’ behaviour patterns and preferences. However, a key challenge of interpreting customer contact information is that many channels have only been in existence for a relatively short period of time, and thus, there is limited understanding and …

Keep It Simple With Time: A Reexamination Of Probabilistic Topic Detection Models, Qi He, Kuiyu Chang, Ee Peng Lim, Arindam Banerjee

Research Collection School Of Computing and Information Systems

Topic detection (TD) is a fundamental research issue in the Topic Detection and Tracking (TDT) community with practical implications; TD helps analysts to separate the wheat from the chaff among the thousands of incoming news streams. In this paper, we propose a simple and effective topic detection model called the temporal Discriminative Probabilistic Model (DPM), which is shown to be theoretically equivalent to the classic vector space model with feature selection and temporally discriminative weights. We compare DPM to its various probabilistic cousins, ranging from mixture models like von-Mises Fisher (vMF) to mixed membership models like Latent Dirichlet Allocation (LDA). …

A Primer On Digital Object Identifiers For Law Librarians, Benjamin J. Keele

Library Staff Publications

No abstract provided.

Early Detection Of Online Auction Opportunistic Sellers Through The Use Of Negative-Positive Feedback, Gregory J. Reinert

CCAC Theses and Dissertations

Apparently fraud is a growth industry. The monetary losses from Internet fraud have increased every year since first officially reported by the Internet Crime Complaint Center (IC3) in 2000. Prior research studies and third-party reports of fraud show rates substantially higher than eBay’s reported negative feedback rate of less than 1%. The conclusion is most buyers are withholding reports of negative feedback.

Researchers Nikitov and Stone in a forensic case study of a single opportunistic eBay seller found buyers sometimes embedded negative comments in positive feedback as a means of avoiding retaliation from sellers and damage to their reputation. This …

Database Security: What Students Need To Know, Meg C. Murray

Faculty Articles

Database security is a growing concern evidenced by an increase in the number of reported incidents of loss of or unauthorized exposure to sensitive data. As the amount of data collected, retained and shared electronically expands, so does the need to understand database security. The Defense Information Systems Agency of the US Department of Defense (2004), in its Database Security Technical Implementation Guide, states that database security should provide controlled, protected access to the contents of a database as well as preserve the integrity, consistency, and overall quality of the data. Students in the computing disciplines must develop an …

Cbtv: Visualising Case Bases For Similarity Measure Design And Selection, Brian Mac Namee, Sarah Jane Delany

Conference papers

In CBR the design and selection of similarity measures is paramount. Selection can benefit from the use of exploratory visualisation- based techniques in parallel with techniques such as cross-validation ac- curacy comparison. In this paper we present the Case Base Topology Viewer (CBTV) which allows the application of different similarity mea- sures to a case base to be visualised so that system designers can explore the case base and the associated decision boundary space. We show, using a range of datasets and similarity measure types, how the idiosyncrasies of particular similarity measures can be illustrated and compared in CBTV allowing …

Inside The Selection Box: Visualising Active Learning Selection Strategies, Brian Mac Namee, Rong Hu, Sarah Jane Delany

Conference papers

Visualisations can be used to provide developers with insights into the inner workings of interactive machine learning techniques. In active learning, an inherently interactive machine learning technique, the design of selection strategies is the key research question and this paper demonstrates how spring model based visualisations can be used to provide insight into the precise operation of various selection strategies. Using sample datasets, this paper provides detailed examples of the differences between a range of selection strategies.

Trust-Oriented Composite Service Selection With Qos Constraints, Lei Li, Yang Wang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In Service-Oriented Computing (SOC) environments, service clients interact with service providers for consuming services. From the viewpoint of service clients, the trust level of a service or a service provider is a critical factor to consider in service selection, particularlywhen a client is looking for a service from a large set of services or service providers. However, a invoked service may be composed of other services. The complex invocations in composite services greatly increase the complexity of trust-oriented service selection. In this paper, we propose novel approaches for composite service representation, trust evaluation and trust-oriented com-posite service selection (with QoS …

Information Integration For Graph Databases, Ee Peng Lim, Aixin Sun, Anwitaman Datta, Chang Kuiyu

Research Collection School Of Computing and Information Systems

With increasing interest in querying and analyzing graph data from multiple sources, algorithms and tools to integrate different graphs become very important. Integration of graphs can take place at the schema and instance levels. While links among graph nodes pose additional challenges to graph information integration, they can also serve as useful features for matching nodes representing real-world entities. This chapter introduces a general framework to perform graph information integration. It then gives an overview of the state-of-the-art research and tools in graph information integration.

On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn

Conference papers

Cloud computing is expected to grow considerably in the future because it has so many advantages with regard to sale and cost, change management, next generation architectures, choice and agility. However, one of the principal concerns for users of the Cloud is lack of control and above all, data security. This paper considers an approach to encrypting information before it is ‘place’ on the Cloud where each user has access to their own encryption algorithm, an algorithm that is based on a set of Iterative Function Systems that outputs a chaotic number stream, designed to produce a cryptographically secure cipher. …