Databases and Information Systems Commons^™

Sa-Rest: Semantically Interoperable And Easier-To-Use Services And Mashups, Amit P. Sheth, Karthik Gomadam, Jonathan Lathem

Kno.e.sis Publications

Services based on the representational state transfer (REST) paradigm, a lightweight implementation of a service-oriented architecture, have found even greater success than their heavyweight siblings, which are based on the Web Services Description Language (WSDL.) and SOAP. By using XML-based messaging, RESTful services can bring together discrete data from different services to create meaningful data sets; mashups such as these are extremely popular today.

Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Li

Computer Science and Engineering Faculty Publications

In this paper, we present an approach for measuring inconsistency in a knowledge base. We first define the degree of inconsistency using a four-valued semantics for the description logic ALC. Then an ordering over knowledge bases is given by considering their inconsistency degrees. Our measure of inconsistency can provide important information for inconsistency handling.

Searching And Tagging: Two Sides Of The Same Coin?, Qiaozhu Mei, Jing Jiang, Hang Su, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

This paper presents the duality hypothesis of search and tagging, two important behaviors of web users. The hypothesis states that if a user views a document D in the search results for query Q, the user would tend to assign document $D$ a tag identical to or similar to Q; similarly, if a user tags a document D with a tag T, the user would tend to view document D if it is in the search results obtained using T as a query. We formalize this hypothesis with a unified probabilistic model for search and tagging, and show that empirical …

A Study Of Out-Of-Turn Interaction In Menu-Based, Ivr, Voicemail Systems, Saverio Perugini, Taylor J. Anderson, William F. Moroney

Computer Science Faculty Publications

We present the first user study of out-of-turn interaction in menu-based, interactive voice-response systems. Out-ofturn interaction is a technique which empowers the user (unable to respond to the current prompt) to take the conversational initiative by supplying information that is currently unsolicited, but expected later in the dialog. The technique permits the user to circumvent any flows of navigation hardwired into the design and navigate the menus in a manner which reflects their model of the task. We conducted a laboratory experiment to measure the effect of the use of outof- turn interaction on user performance and preference in a …

Characteristics Of Facilities With Specialized Programming For Drinking Drivers And For Other Criminal Justice Involved Clients: Analysis Of A National Database, Cynthia L. Arfken, Sheryl Kubiak

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Offering specialized programming at substance abuse treatment facilities can help diversify clientele and funding sources, potentially enhancing the facilities' ability to survive and/or expand. Past research has shown that facilities only offering specialized programming for driving under the influence/driving while intoxicated offenders (DUI) are predominately private-for-profit owned. As criminal justice populations, both DUI and other criminal justice offenders, comprise a large proportion of those in community-based substance abuse treatment knowing facilities' characteristics would be important for administrators and policymakers to consider when updating programming, training staff or expanding capacity to ensure efficient use of scarce resources. However, while …

Semantic Matchmaking Of Web Resources With Local Closed-World Reasoning, Stephan Grimm, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Ontology languages like OWL allow for semantically rich annotation of resources (e.g., products advertised at on-line electronic marketplaces). The description logic (DL) formalism underlying OWL provides reasoning techniques that perform match-making on such annotations. This paper identifies peculiarities in the use of DL inferences for matchmaking that derive from OWL's open-world semantics, analyzes local closed-world reasoning for its applicability to matchmaking, and investigates the suitability of two nonmonotonic extensions to DL, autoepistemic DLs and DLs with circumscription, for local closed-world reasoning in the matchmaking context. An elaborate example of an electronic marketplace for PC product catalogs from the e-commerce domain …

Sustainability Of Information Technology Therapy On Micro-Enterprise Development., Sajda Qureshi, Mehruz Kamal, Peter Wolcott

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The use of information technology in microenterprises has been shown to bring about improvements in accessing new markets, in achieving administrative efficiencies, increased productivity and competitiveness. To benefit from IT, micro-enterprises require specialized intervention and support. At the same time these micro-enterprises require skill sets that can translate their unique needs to IT solutions. This paper provides an IT Therapy approach to addressing micro-enterprise needs through IT. Following an action research approach to investigating micro-enterprises, this paper provides insights into how IT can bring about sustained improvements in micro-enterprises. The contribution of this paper is in guidelines of how IT …

From “Glycosyltransferase” To “Congenital Muscular Dystrophy”: Integrating Knowledge From Ncbi Entrez Gene And The Gene Ontology, Satya S. Sahoo, Kelly Zeng, Olivier Bodenreider, Amit P. Sheth

Kno.e.sis Publications

Entrez Gene (EG), Online Mendelian Inheritance in Man (OMIM) and the Gene Ontology (GO) are three complementary knowledge resources that can be used to correlate genomic data with disease information. However, bridging between genotype and phenotype through these resources currently requires manual effort or the development of customized software. In this paper, we argue that integrating EG and GO provides a robust and flexible solution to this problem. We demonstrate how the Resource Description Framework (RDF) developed for the Semantic Web can be used to represent and integrate these resources and enable seamless access to them as a unified resource. …

What, Where And When: Supporting Semantic, Spatial And Temporal Queries In A Dbms, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain

Kno.e.sis Publications

Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. The outcome of the analytical process in these applications often hinges on uncovering and analyzing complex 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 in these applications. However, these analysis mechanisms are primarily intended for thematic relationships. We describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between …

Collecting Expertise Of Researchers For Finding Relevant Experts In A Peer-Review Setting, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar

Kno.e.sis Publications

We present ideas for determining the expertise of researchers across various areas of computer science and for finding relevant experts/reviewers in a peer review setting. We explain how Semantic Web techniques for data collection and data representation using ontologies can be used in addressing this specific 'ExpertFinder' problem.

Brief Announcement: Space Adaptation: Privacy-Preserving Multiparty Collaborative Mining With Geometric Perturbation, Keke Chen, Ling Liu

Kno.e.sis Publications

No abstract provided.

Evolution And Maintenance Of Frequent Pattern Space When Transactions Are Removed, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong

Kno.e.sis Publications

This paper addresses the maintenance of discovered frequent patterns when a batch of transactions are removed from the original dataset. We conduct an in-depth investigation on how the frequent pattern space evolves under transaction removal updates using the concept of equivalence classes. Inspired by the evolution analysis, an effective and exact algorithm TRUM is proposed to maintain frequent patterns. Experimental results demonstrate that our algorithm outperforms representative state-of-the-art algorithms.

Best Practices For Implementing Agile Methods: A Guide For Department Of Defense Software Developers, Ann L. Fruhling, Alvin E. Tarrell

Information Systems and Quantitative Analysis Faculty Publications

Traditional plan-driven software development has been widely used in the government because it's considered to be less risky, more consistent, and structured. But there has been a shift from this approach to Agile methods which are more flexible, resulting in fast releases by working in an incremental fashion to adapt to the reality of the changing or unclear requirements.

This report describes the Agile software development philosophy, methods, and best practices in launching software design projects using the Agile approach. It is targeted to Defense Department software developers because they face broad challenges in creating enterprise-wide information systems, where Agile …

Brief Description And Analysis Of The Census Bureau's 2006 Population Estimates For Incorporated Places For Cleveland And Other Ohio Cities, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Factors Influencing Speed Of Cancer Diagnosis In Rural Wa, Moyez Jiwa, Georgia Halkett, Samar Aoun, Hayley Arnet, Marthe Smith, Megan Pilkington, Cheryl Mcmullen

Research outputs pre 2011

Introduction: The speed of diagnosis impacts on prognosis and survival in all types of cancer. In most cases survival and prognosis are significantly worse in rural and remote Australian populations who have less access to diagnostic and therapeutic services than metropolitan communities in this country. Research suggests that in general delays in diagnosis were a factor of misdiagnosis, the confounding effect of existing conditions and delayed or misleading investigation of symptoms. The aim of this study is to further explore the factors that impact on the speed of diagnosis in rural Western Australia with direct reference to General Practitioners (GPs) …

Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for …

National Culture And Its Effects On Knowledge Communication In Online Virtual Communities, Keng Siau, Fiona Fui-Hoon Nah, Min Ling

Research Collection School Of Computing and Information Systems

Online virtual communities provide a powerful means of knowledge sharing. Despite the prevalence of online virtual communities, there is a paucity of research to investigate the effect of national culture differences on knowledge sharing in online virtual communities. Are there differences between online virtual communities from different national cultures? This research studies the differences in knowledge-sharing activities between US-based and China-based online virtual communities. Hofstede's dimensions of national culture serve as the theoretical foundation for this research.

Mining Multiple Visual Appearances Of Semantics For Image Annotation, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single concept point of a category are limited in their effectiveness for image annotation. We propose to use data mining techniques to mine multiple concepts, where each concept may consist of one or more visual parts, to capture the diverse visual appearances of a single keyword category. For training, we use the Apriori principle to efficiently mine a set of frequent blobsets to capture the semantics of a rich and diverse visual category. Each concept is …

Direct Code Access In Self-Organizing Neural Networks For Reinforcement Learning, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD-FALCON still relies on an iterative process to evaluate each available action in a decision cycle. To remove this deficiency, this paper presents a direct code access procedure whereby TD-FALCON conducts instantaneous searches for cognitive nodes that match with the current states and at the same time provide maximal reward values. Our comparative experiments show that TD-FALCON with direct code access produces comparable performance with the original TD-FALCON while improving significantly in computation efficiency and network complexity.

Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Decision tree (DT) has great potential in image semantic learning due to its simplicity in implementation and its robustness to incomplete and noisy data. Decision tree learning naturally requires the input attributes to be nominal (discrete). However, proper discretization of continuous-valued image features is a difficult task. In this paper, we present a decision tree based image semantic learning method, which avoids the difficult image feature discretization problem by making use of semantic template (ST) defined for each concept in our database. A ST is the representative feature of a concept, generated from the low-level features of a collection of …