Physical Sciences and Mathematics Commons^™

Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim

Research Collection School Of Computing and Information Systems

What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …

Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta

Research Collection School Of Computing and Information Systems

IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes …

The Factors Behind A Successful Implementation Of Electronic Health Records Systems, Anjee Gorkhali

Engineering Management & Systems Engineering Theses & Dissertations

This research explores the role that budget for Information System (IS) and technical expertise of healthcare service provider staff play on the successful leap from a partial to exhaustive implementation of Electronic Health Records (EHR) Systems. Technical expertise in Information Systems might not be easily measurable directly, but there are a number of indicators that could be used as a proxy, such as: Information System (IS) Department Budget, number of IS staff and the extent of technical trainings provided by the IS department to the clinical staff. This research study hypothesizes that quality technical trainings conducted by an IS department …

A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang

Research Collection School Of Computing and Information Systems

Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …

Proceedings Of The Oss 2012 Doctoral Consortium, Klaas-Jan Stol, Charles M. Schweik, Imed Hammouda

Charles M. Schweik

Papers accepted (and revised) by doctoral students who participated in the Open Source Systems (OSS) 2012 Doctoral Consortium, Hammamet, Tunisia

Enterprise Systems Manager, Edward Aractingi

Edward Aractingi

Presentation on the need of remote systems administration.

Linux 101: Ci-Trainseminar, Edward Aractingi

Edward Aractingi

An overview of how the Linux operating system.

Student Interactive Campus Map At Marshall University, Edward Aractingi, Jamie Wolfe

Edward Aractingi

Marshall University is a state-funded university in Huntington, West Virginia. Like many universities, it is a large organization with multiple and diverse units (colleges, departments, centers, etc.) and depends on data to run efficiently. Much of this data is used by multiple entities. To better manage the needed data collected by the university, the Marshall University Geographic Information System (MUGIS) has been developed. MUGIS will address several needs of Marshall University’s principal stakeholders. Stakeholders include the university administration, faculty, and students. One of the first applications developed for MUGIS was an interactive campus map. This Web-based application is intended to …

Adopting Virtualized 10gbe Ethernet Iscsi San For Mission Critical Applications, Edward Aractingi, Allen Taylor, David Griggs

Edward Aractingi

The presentation will provide insight into the decision to move from a fibre channel SAN solution, the resulting performance metrics and financial savings seen by Marshall University. Presented at The Ohio Higher Education Computing Council (OHECC) March 23, 2011.

Adopting Virtualized 10gbe Ethernet Iscsi San For Mission Critical Applications, Edward Aractingi, Allen Taylor, David Griggs

Allen Taylor

The presentation will provide insight into the decision to move from a fibre channel SAN solution, the resulting performance metrics and financial savings seen by Marshall University. Presented at The Ohio Higher Education Computing Council (OHECC) March 23, 2011.

Recent Advances In Integrating Owl And Rules, Matthias Knorr, David Carral Martinez, Pascal Hitzler, Adila A. Krisnadhi, Frederick Maier, Cong Wang

Computer Science and Engineering Faculty Publications

As part of the quest for a unifying logic for the Semantic Web Technology Stack, a central issue is finding suitable ways of integrating description logics based on the Web Ontology Language (OWL) with rule-based approaches based on logic programming. Such integration is difficult since naive approaches typically result in the violation of one or more desirable design principles. For example, while both OWL 2 DL and RIF Core (a dialect of the Rule Interchange Format RIF) are decidable, their naive union is not, unless carefully chosen syntactic restrictions are applied.

We report on recent advances and ongoing work by …

A Tableau Algorithm For Description Logics With Nominal Schema, Adila Krisnadhi, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a tableau algorithm for the description logic ALCOV. This description logic is obtained by extending the description logic ALCO with the expressive nominal schema construct that enables DL-safe datalog with predicates of arbitrary arity to be covered within the description logic framework. The tableau algorithm provides a basis to implement a delayed grounding strategy which was not facilitated by earlier versions of decision procedures for satisfiability in expressive description logics with nominal schemas.

Principles For Conducting Critical Realist Case Study Research In Information Systems, Donald E. Wynn, Clay K. Williams

MIS/OM/DS Faculty Publications

Critical realism is emerging as a viable philosophical paradigm for conducting social science research, and has been proposed as an alternative to the more prevalent paradigms of positivism and interpretivism. Few papers, however, have offered clear guidance for applying this philosophy to actual research methodologies. Under critical realism, a causal explanation for a given phenomenon is inferred by explicitly identifying the means by which structural entities and contextual conditions interact to generate a given set of events. Consistent with this view of causality, we propose a set of methodological principles for conducting and evaluating critical realism-based explanatory case study research …

Guest Editors’ Introduction: Methods Innovations For The Empirical Study Of Technology Adoption And Diffusion, Robert John Kauffman, Angsana A. Techatassanasoontorn

Research Collection School Of Computing and Information Systems

The literature on technology adoption and diffusion is ahighly mature area of Information Systems (IS) research,which requires a deft hand in research to support the creationof new contributions of knowledge. In this specialissue, we focus on the application of various methods,including new ones, to shed light on research questions thathave not been understood fully in prior research. In particular,we will showcase research that involves theapplication of event history analysis and spatial econometrics,as well as count data models to study frequencyrelatedphenomena for changes and development in technologyadoption and diffusion. We also include an articlethat employs game theory, as well as another …

In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as …

Bduol: Double Updating Online Learning On A Fixed Budget, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Kernel-based online learning often exhibits promising empirical performance for various applications according to previous studies. However, it often suffers a main shortcoming, that is, the unbounded number of support vectors, making it unsuitable for handling large-scale datasets. In this paper, we investigate the problem of budget kernel-based online learning that aims to constrain the number of support vectors by a predefined budget when learning the kernel-based prediction function in the online learning process. Unlike the existing studies, we present a new framework of budget kernel-based online learning based on a recently proposed online learning method called “Double Updating Online Learning” …

Analysis Of Median Household Income Differences Between Election Day-Vbm And Eip Voters, Mark Salling, Norman Robbins

All Maxine Goodman Levin School of Urban Affairs Publications

Analysis of early in-person (EIP) voting in 2008 in Cuyahoga County shows that African-American, white, and Hispanic voters who used EIP voting had significantly lower incomes than members of those same groups who voted on election day or by mail. This result applies to those voting EIP on weekdays, extended weekday hours, weekends, and the three days before election day.

Reconciling Owl And Non-Monotonic Rules For The Semantic Web, Matthias Knorr, Pascal Hitzler, Frederick Maier

Computer Science and Engineering Faculty Publications

We propose a description logic extending SROIQ (the description logic underlying OWL 2 DL) and at the same time encompassing some of the most prominent monotonic and nonmonotonic rule languages, in particular Datalog extended with the answer set semantics. Our proposal could be considered a substantial contribution towards fulfilling the quest for a unifying logic for the Semantic Web. As a case in point, two non-monotonic extensions of description logics considered to be of distinct expressiveness until now are covered in our proposal. In contrast to earlier such proposals, our language has the 'look and feel' of a description logic …

The Return Of Dr. Strangelove, Jan Kallberg, Adam Lowther

Jan Kallberg

With the prospect of sequestration looming, the United States may find itself increasingly rely ing on nuclear and cy ber deterrence as an affordable means of guaranteeing national sovereignty and preventing major conflict between the U.S. and potential adversaries in the Asia-Pacific. While earlier defense planning and acquisition were based on economic conditions that no longer ex ist, Congress’s options to balance the budget by cutting defense spending are politically palatable because far fewer American are “defense v oters” relative to “social welfare voters,” according to a number of recent public opinion surveys. The simple fact is China’s rise has …

A Survey Of Schema Matching Research, Roger Blake

Roger H. Blake

Schema matching is the process of developing semantic matches between two or more schemas. The purpose of schema matching is generally either to merge two or more databases, or to enable queries on multiple, heterogeneous databases to be formulated on a single schema (Doan and Halevy 2005). This paper develops a taxonomy of schema matching approaches, classifying them as being based on a combination schema matching technique and the type of data used by those techniques. Schema matching techniques are categorized as being based on rules, learning, or ontology, and the type of data used is categorized as being based …

Ethical Considerations For Virtual Worlds, Alanah Mitchell, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Metaverses, like Second Life and Teleplace, and the inherent technology capabilities that they offer continue to be of interest for researchers, practitioners, and educators. Due to this trend, and the uncertainty regarding immersive virtual experiences as contrasted with face-to-face experiences, there is a need to further understand the ethical challenges associated with this virtual context. This paper presents a starting point for discussing ethics in virtual worlds. Specifically, we review virtual worlds and their unique technology capabilities as well as the ethical considerations that arise due to these unique capabilities.

Using Attribute Behavior Diversity To Build Accurate Decision Tree Committees For Microarray Data, Qian Han, Guozhu Dong

Kno.e.sis Publications

DNA microarrays (gene chips), frequently used in biological and medical studies, measure the expressions of thousands of genes per sample. Using microarray data to build accurate classifiers for diseases is an important task. This paper introduces an algorithm, called Committee of Decision Trees by Attribute Behavior Diversity (CABD), to build highly accurate ensembles of decision trees for such data. Since a committee's accuracy is greatly influenced by the diversity among its member classifiers, CABD uses two new ideas to "optimize" that diversity, namely (1) the concept of attribute behavior–based similarity between attributes, and (2) …

A Non-Parametric Visual-Sense Model Of Images: Extending The Cluster Hypothesis Beyond Text, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia

Research Collection School Of Computing and Information Systems

The main challenge of a search engine is to find information that are relevant and appropriate. However, this can become difficult when queries are issued using ambiguous words. Rijsbergen first hypothesized a clustering approach for web pages wherein closely associated pages are treated as a semantic group with the same relevance to the query (Rijsbergen 1979). In this paper, we extend Rijsbergen’s cluster hypothesis to multimedia content such as images. Given a user query, the polysemy in the return image set is related to the many possible meanings of the query. We develop a method to cluster the polysemous images …

Presynaptic Learning And Memory With A Persistent Firing Neuron And A Habituating Synapse: A Model Of Short Term Persistent Habituation, Kiruthika Ramanathan, Ning Ning, Dhiviya Dhanasekar, Guoqi Li, Luping Shi, Prahlad Vadakkepat

Research Collection School Of Computing and Information Systems

Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show …

Confidence-Aware Graph Regularization With Heterogeneous Pairwise Features, Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

Conventional classification methods tend to focus on features of individual objects, while missing out on potentially valuable pairwise features that capture the relationships between objects. Although recent developments on graph regularization exploit this aspect, existing works generally assume only a single kind of pairwise feature, which is often insufficient. We observe that multiple, heterogeneous pairwise features can often complement each other and are generally more robust in modeling the relationships between objects. Furthermore, as some objects are easier to classify than others, objects with higher initial classification confidence should be weighed more towards classifying related but more ambiguous objects, an …

Online Feature Selection For Mining Big Data, Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin

Research Collection School Of Computing and Information Systems

Most studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or the access to it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which the online learner is only allowed to maintain a classifier involved a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. …

Collective Churn Prediction In Social Network, Richard J. Oentaryo, Ee-Peng Lim, David Lo, Feida Zhu, Philips K. Prasetyo

Research Collection School Of Computing and Information Systems

In service-based industries, churn poses a significant threat to the integrity of the user communities and profitability of the service providers. As such, research on churn prediction methods has been actively pursued, involving either intrinsic, user profile factors or extrinsic, social factors. However, existing approaches often address each type of factors separately, thus lacking a comprehensive view of churn behaviors. In this paper, we propose a new churn prediction approach based on collective classification (CC), which accounts for both the intrinsic and extrinsic factors by utilizing the local features of, and dependencies among, individuals during prediction steps. We evaluate our …

A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In recent years, the Internet of Things (IOT) has drawn considerable attention from the industrial and research communities. Due to the vast amount of data generated through IOT devices and users, there is an urgent need for an effective search engine to help us make sense of this massive amount of data. With this motivation, we begin our initial works on developing a secure and efficient search engine (SecDS) based on EPC Discovery Services (EPCDS) for EPCglobal network, an integral part of IOT. SecDS is designed to provide a bridge between different partners of supply chains to share information while …

Boosting Multi-Kernel Locality-Sensitive Hashing For Scalable Image Retrieval, Hao Xia, Steven C. H. Hoi, Pengcheng Wu, Rong Jin

Research Collection School Of Computing and Information Systems

Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for similarity search in high-dimensional space, Locality-Sensitive Hashing (LSH) is the most popular one, which recently has been extended to Kernelized Locality-Sensitive Hashing (KLSH) by exploiting kernel similarity for better retrieval efficacy. Typically, KLSH works only with a single kernel, which is often limited in real-world multimedia applications, where data may originate from multiple resources or can be represented in several different forms. For example, in content-based multimedia retrieval, a variety of features can be extracted to represent …

Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over …