Physical Sciences and Mathematics Commons^™

Survey Of Current Sensor Network Data Management Frameworks, Cory Henson, Satya S. Sahoo

Kno.e.sis Publications

No abstract provided.

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 …

Learning To Model Spatial Dependency: Semi-Supervised Discriminative Random Fields, Chi-Hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner

Kno.e.sis Publications

We present a novel, semi-supervised approach to training discriminative random fields (DRFs) that efficiently exploits labeled and unlabeled training data to achieve improved accuracy in a variety of image processing tasks. We formulate DRF training as a form of MAP estimation that combines conditional loglikelihood on labeled data, given a data-dependent prior, with a conditional entropy regularizer defined on unlabeled data. Although the training objective is no longer concave, we develop an efficient local optimization procedure that produces classifiers that are more accurate than ones based on standard supervised DRF training. We then apply our semi-supervised approach to train DRFs …

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.

Glycoo Ontology, Christopher Thomas

Kno.e.sis Publications

No abstract provided.

A Unified Approach To Retrieving Web Documents And Semantic Web Data, Trivikram Immaneni, Krishnaprasad Thirunarayan

Kno.e.sis Publications

The Semantic Web seems to be evolving into a property-linked web of RDF data, conceptually divorced from (but physically housed in) the hyperlinked web of HTML documents. We discuss the Unified Web model that integrates the two webs and formalizes the structure and the semantics of interconnections between them. We also discuss the Hybrid Query Language which combines the Data and Information Retrieval techniques to provide a convenient and uniform way to retrieve data and documents from the Unified Web. We present the retrieval system SITAR and some preliminary results.

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.

Semantically Annotating A Web Service, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

In the past few years, service-oriented architecture (SOA) has transitioned from a partially formed vision into a widely implemented paradigm, with Web services (WS) being the forerunners to implementing SOA-based solutions. But even though the current trend is to use Web services' standards-based nature to establish static connections between various components, businesses are starting to explore dynamic value-added propositions, such as reuse, interoperability, and agility.

Role Of Semantics In Autonomic & Adaptive Web Services And Processes, Amit P. Sheth

Kno.e.sis Publications

The emergence of Service Oriented Architectures (SOA) has created a new paradigm of loosely coupled distributed systems. In the METEOR-S project, we have studied the comprehensive role of semantics in all stages of the life cycle of service and process-- including annotation, publication, discovery, interoperability/data mediation, and composition. In 2002-2003, we had offered a broad framework of semantics consisting of four types:1) Data semantics, 2) Functional semantics, 3) Non-Functional semantics and 4) Execution semantics. This talk describes the need for the four types of semantics, its standards-based support through WSDL-S/SAWSDL, and the need for such semantic representation to dynamic and …

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 …

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) …

Predicting Crime Reporting With Decision Trees And The National Crime Victimization Survey, Gondy Leroy, Juliette Gutierrez '13

CGU Faculty Publications and Research

Crime reports are used by law enforcement to find criminals, prevent further violations, identify problems causing crimes and allocate government resources. Unfortunately, many crimes go unreported. This may lead to an incorrect crime picture and suboptimal responses to the existing situation. Our goal is to use a data mining approach to increase understanding of when crime is reported or not. An increased understanding could lead to new, more effective programs to fight crime or changes to existing programs. We use the National Crime Victimization Survey (NCVS) which comprises data collected from 45,000 households about incidents, victims, suspects and if the …

Natural Language Processing And E-Government: Extracting Reusable Crime Report Information, Gondy A. Leroy, Alicia Iriberri '06

CGU Faculty Publications and Research

Crime reporting needs to be possible 24/7. Although 911 and tip-lines are the most publicized reporting mechanisms, several other options exist, ranging from in-person reporting to online submissions. Internet-based crime reporting systems allow victims and witnesses of crime to report incidents to police 24/7 from any location. However, these existing e-mail and text-based systems provide little support for witnesses' memory recall leading to reports with less information and lower accuracy. These systems also do not facilitate reuse and integration of the reported information with other information systems. We are developing an anonymous Online Crime Reporting System that is designed to …

A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09

CGU Faculty Publications and Research

Consumer health information written by health care professionals is often inaccessible to the consumers it is written for. Traditional readability formulas examine syntactic features like sentence length and number of syllables, ignoring the target audience's grasp of the words themselves. The use of specialized vocabulary disrupts the understanding of patients with low reading skills, causing a decrease in comprehension. A naive Bayes classifier for three levels of increasing medical terminology specificity (consumer/patient, novice health learner, medical professional) was created with a lexicon generated from a representative medical corpus. Ninety-six percent accuracy in classification was attained. The classifier was then applied …

Revealing The Antecedents And Benefits Of Kms Use: An Exploratory Study In A Petroleum Company In Oman, Kamla Al-Busaidi '05, Lorne Olfman, Terry Ryan, Gondy Leroy

CGU Faculty Publications and Research

This pilot study aimed to explore technical and social antecedents and benefits of KMS use in a petroleum company in Oman. Data was collected through questionnaire given to KMS users. From the technical perspective, results uncovered that both knowledge utilizers and contributors were concerned about the system ease of use, speed and integration. Knowledge utilizers also valued knowledge richness in terms of relevancy and timeliness. From the social perspective, both knowledge utilizers and contributors considered time/availability as the major determinant of their behaviors. The results also suggested that knowledge utillizers valued the technical factors more than the social factors, whereas, …

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.

An Analysis Of Services Provided By Faith-Based Organizations To Cleveland’S Ward 17 Community, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Creation Of A Web Site To Provide Technical Support And Training, Ricky Lee Hrdlicka

Theses Digitization Project

The project, presented in this paper, developed a web-based tool that provides training and technical support in the use of computers to employees at the San Bernardino Community College District. The purpose of this project was with the lack of one support system it has become necessary to create one place for support entities to share their expertise with one another and with the campus community. This project creates a web presence that all of these groups can contribute to. This system starts out small and creates a skeletal system that will allow for continued development after the project is …

Ebay Learning Center System, Jessica Chen

Theses Digitization Project

The project developed eBay Learning Center System (ELCS), a web-based application that provides current and potential eBay users a way to learn about the many functions of the popular online auction and shopping web site and be successful eBay traders. ELCS provides end users with online tutorials, available both in multimedia and text formats, and methods of communicating with system administrators and other users by means of a message box and a discussion forum to facilitate learning and collaborative problem solving. The system employs current technologies such as SQL, HTML, ASP.NET, VBScript, XML, ODBC, and ADO.

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.

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 …

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 …

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 …

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 …

Itr/Im: Enabling The Creation And Use Of Geogrids For Next Generation Geospatial Information, Peggy Agouris, Mary-Kate Beard-Tisdale, Chaitanya Baru, Sarah Nusser

University of Maine Office of Research Administration: Grant Reports

The objective of this project is to advance science in information management, focusing in particular on geospatial information. It addresses the development of concepts, algorithms, and system architectures to enable users on a grid to query, analyze, and contribute to multivariate, quality-aware geospatial information. The approach consists of three complementary research areas: (1) establishing a statistical framework for assessing geospatial data quality; (2) developing uncertainty-based query processing capabilities; and (3) supporting the development of space- and accuracy-aware adaptive systems for geospatial datasets. The results of this project will support the extension of the concept of the computational grid to facilitate …

Data Management Plans: Stages, Components, And Activities, Abbas S. Tavakoli, Kirby Jackson, Linda Moneyham, Kenneth D. Phillips, Carolyn Murdaugh, Gene Meding

Applications and Applied Mathematics: An International Journal (AAM)

Data management strategies have become increasingly important as new computer technologies allow for larger and more complex data sets to be analyzed easily. As a consequence, data management has become a specialty requiring specific skills and knowledge. Many new investigators have no formal training in management of data sets. This paper describes common basic strategies critical to the management of data as applied to a data set from a longitudinal study. The stages of data management are identified. Moreover, key components and strategies, at each stage are described.

Implicit Online Learning With Kernels, Li Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli

Kno.e.sis Publications

We present two new algorithms for online learning in reproducing kernel Hilbert spaces. Our first algorithm, ILK (implicit online learning with kernels), employs a new, implicit update technique that can be applied to a wide variety of convex loss functions. We then introduce a bounded memory version, SILK (sparse ILK), that maintains a compact representation of the predictor without compromising solution quality, even in non-stationary environments. We prove loss bounds and analyze the convergence rate of both. Experimental evidence shows that our proposed algorithms outperform current methods on synthetic and real data.

Regression Cubes With Lossless Compression And Aggregation, Yixin Chen, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, Jianyong Wang

Kno.e.sis Publications

As OLAP engines are widely used to support multidimensional data analysis, it is desirable to support in data cubes advanced statistical measures, such as regression and filtering, in addition to the traditional simple measures such as count and average. Such new measures will allow users to model, smooth, and predict the trends and patterns of data. Existing algorithms for simple distributive and algebraic measures are inadequate for efficient computation of statistical measures in a multidimensional space. In this paper, we propose a fundamentally new class of measures, compressible measures, in order to support efficient computation of the statistical models. For …

Yellow Tree: A Distributed Main-Memory Spatial Index Structure For Moving Objects, Hariharan Gowrisankar

Electronic Theses and Dissertations

Mobile devices equipped with wireless technologies to communicate and positioning systems to locate objects of interest are common place today, providing the impetus to develop location-aware applications. At the heart of location-aware applications are moving objects or objects that continuously change location over time, such as cars in transportation networks or pedestrians or postal packages. Location-aware applications tend to support the tracking of very large numbers of such moving objects as well as many users that are interested in finding out about the locations of other moving objects. Such location-aware applications rely on support from database management systems to model, …