Implementing Qos Management For Workflow Systems, Jorge Cardoso, Amit P. Sheth, Krzysztof J. Kochut

Kno.e.sis Publications

Workflow management systems (WfMSs) have been used to support various types of business processes. As organizations adopt new working models, such as e-commerce, new challenges arise for workflow systems. One such challenge is that of quality of service (QoS) management. QoS management includes mechanisms that specify, compute, monitor, and control the quality of service of the products or services to be delivered. A good management of QoS directly impacts the success of organizations participating in e-commerce activities by better fulfilling customer expectations and achieving customer satisfaction. In this paper we present an implementation of a comprehensive QoS model for workflows …

Applying Xml/Xslt Technology: A Case Study, Krishnaprasad Thirunarayan

Kno.e.sis Publications

Typically, paper-based semi-structured documents are used to communicate technical requirements in the industry. One approach to improving the efficiency and flexibility of searching and manipulating these documents is to obtain them in electronic form, and then make explicit the technical content in a form amenable to pattern matching and symbol manipulation. This paper explores the role of XML Technology for these purposes: the use of XML language to make explicit the content of a document in a standard fashion, and the use of XSLT to manipulate the content and mediate between applications that need this content. In order to recognize …

Semi-Automatic Content Extraction From Specifications, Krishnaprasad Thirunarayan, Aaron Berkovich, Dan Z. Sokol

Kno.e.sis Publications

Specifications are critical to companies involved in complex manufacturing. The constant reading, reviewing, and analysis of materials and process specifications is extremely labor-intensive, quality impacting, and time-consuming. A conceptual design for a tool that provides computer-assistance in the interpretation of specification requirements has been created and a strategy for semantic-markup, which is the overlaying of abstract syntax (“the essence”) on the text, has been developed. The solution is based on the techniques for Information Extraction and the XML technology, and it captures the specification content within a semantic ontology. The working prototype of the tool being built will serve as …

Towards Peer-To-Peer Semantic Web: A Distributed Environment For Sharing Semantic Knowledge On The Web, Madhan Arumugam, Amit P. Sheth, I. Budak Arpinar

Kno.e.sis Publications

The real value of Semantic Web vision can be demonstrated if people and applications can create and discover new and interesting knowledge and share this knowledge in a transparent manner similar to the way data is exchanged today. Therefore, we believe that Semantic Web will consist of a distributed environment of shared and interoperable ontologies, which have emerged as common formalisms for knowledge representation. The users will need to discover new ontologies, which are not known to them before and use them to either annotate the content or to formulate their information requests. This requires an environment that supports creating, …

Modeling Quality Of Service For Workflows And Web Service Processes, Jorge Cardoso, John A. Miller, Amit P. Sheth, Jonathan Arnold

Kno.e.sis Publications

Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In workflows for e-commerce and Web-services applications, suppliers and customers define a binding agreement or contract between the two parties, specifying Quality of Service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. Therefore, when services or products are created or managed using workflows, the underlying workflow system must accept the specifications and be able to estimate, …

Process Composition: Quality Of Service Specification, Semantics And Adaptation, Jorge Cardoso, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Characterizing Logic Programming Semantics With Level Mappings, Pascal Hitzler, Matthias Wendt

Computer Science and Engineering Faculty Publications

Declarative semantics in logic programming and nonmonotonic reasoning are often defined via fixed points of semantic operators. While many relationships between different semantics known from the literature have been studied, a uniform treatment is still missing. In this paper, we provide uniform operator-free characterizations for some of the most important semantics, more precisely, for the stable, the well-founded, and the Fitting semantics, for the weakly-perfect model semantics, and for the least model semantics for negation-free programs.

The Fixed-Point Theorems Of Priess-Crampe And Ribenboim In Logic Programming, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

Sibylla Priess-Crampe and Paulo Ribenboim recently established a general fixed-point theorem for multivalued mappings defined on generalized ultrametric spaces, and introduced it to the area of logic programming semantics. We discuss, in this context, the applications which have been made so far of this theorem and of its corollaries. In particular, we will relate these results to Scott-Ershov domains, familiar in programming language semantics, and to the generalized metrics of Khamsi, Kreinovich, and Misane which have been applied, by these latter authors, to logic programming. Amongst other things, we will also show that a unified treatment of the fixed-point theory …

Managing Semantic Content For The Web, Amit P. Sheth, Clemens Bertram, David Avant, Brian Hammond, Krzysztof Kochut, Yashodhan Warke

Kno.e.sis Publications

By associating meaning with content, the Semantic Web will facilitate search, interoperability, and the composition of complex applications. A recent Scientific American article described the Semantic Web as 'an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.' Not long ago, researchers at a Stanford University symposium predicted that this second phase of the Web would be as revolutionary as the Web itself.

Predicting Oral Reading Miscues, Jack Mostow, Joseph Beck, S. Vanessa Winter, Shaojun Wang

Kno.e.sis Publications

This paper explores the problem of predicting specific reading mistakes, called miscues, on a given word. Characterizing likely miscues tells an automated reading tutor what to anticipate, detect, and remediate. As training and test data, we use a database of over 100,000 miscues transcribed by University of Colorado researchers. We explore approaches that exploit different sources of predictive power: the uneven distribution of words in text, and the fact that most miscues are real words. We compare the approaches’ ability to predict miscues of other readers on other text. A simple rote method does best on the most frequent 100 …

Workflow Quality Of Service, Jorge Cardoso, Amit P. Sheth, John A. Miller

Kno.e.sis Publications

Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In ecommerce processes, suppliers and customers define a binding agreement or contract between the two parties, specifying quality of service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of service. Management of such QoS directly impacts success of organizations participating in e-commerce. Organizations operating in modern markets require an excellent degree of quality of service management. Products and services must be available to customers with well-defined specifications. A good management of quality …

Ilp Operators For Propositional Connectionist Networks, Miguel Angel Gutierrez-Naranjo, Pascal Hitzler

Computer Science and Engineering Faculty Publications

No abstract provided.

Towards Nonmonotonic Reasoning On Hierarchical Knowledge, Pascal Hitzler

Computer Science and Engineering Faculty Publications

W.C. Rounds and G.Q. Zhang have recently proposed to study a form of disjunctive logic programming generalized to algebraic domains [RZ01]. This system allows reasoning with information which is hierarchically structured and forms a (suitable) domain. We extend this framework to include reasoning with negative information, i.e. the implicit or explicit absence of bits of information. These investigations will naturally lead to a form of default reasoning which is strongly related to programming with answer sets to stable models, which has recently created much interest amongst artificial intelligence researchers concerned with knowledge representation and reasoning.

A Proposed Undergraduate Bioinformatics Curriculum For Computer Scientists, Travis E. Doom, Michael L. Raymer, Dan E. Krane, Oscar Garcia

Kno.e.sis Publications

Bioinformatics is a new and rapidly evolving discipline that has emerged from the fields of experimental molecular biology and biochemistry, and from the the artificial intelligence, database, and algorithms disciplines of computer science. Largely because of the inherently interdisciplinary nature of bioinformatics research, academia has been slow to respond to strong industry and government demands for trained scientists to develop and apply novel bioinformatics techniques to the rapidly-growing, freely-available repositories of genetic and proteomic data. While some institutions are responding to this demand by establishing graduate programs in bioinformatics, the entrance barriers for these programs are high, largely due to …

Multi-Dimensional Regression Analysis Of Time-Series Data Streams, Yixin Chen, Guozhu Dong, Jiawei Han, Benjamin W. Wah, Jianyong Wang

Kno.e.sis Publications

Real-time production systems and other dynamic environments often generate tremendous (potentially infinite) amount of stream data; the volume of data is too huge to be stored on disks or scanned multiple times. Can we perform on-line, multi-dimensional analysis and data mining of such data to alert people about dramatic changes of situations and to initiate timely, high-quality responses? This is a challenging task.

In this paper, we investigate methods for online, multi-dimensional regression analysis of time-series stream data, with the following contributions: (1) our analysis shows that only a small number of compressed regression measures instead of the complete stream …

Xml-Based Modeling And Simulation: Web Service Technologies And Their Synergy With Simulation, Senthilanand Chandrasekaran, Gregory S. Silver, John A. Miller, Jorge Cardoso, Amit P. Sheth

Kno.e.sis Publications

The World Wide Web has had an huge influence on the computing field in general as well as simulation in particular (e.g., Web-based simulation). A new wave of development based upon XML has started. Two of the most interesting aspects of this development are the Semantic Web and Web services. This paper examines the synergy between Web service technology and simulation. In one direction, Web service processes can be simulated for the purpose of correcting/improving the design. In the other direction, simulation models/components can be built out of Web services. Work on seamlessly using simulation as a part of Web …

Authorization And Access Control Of Application Data In Workflow Systems, Shengli Wu, Amit P. Sheth, John A. Miller, Zongwei Luo

Kno.e.sis Publications

Workflow Management Systems (WfMSs) are used to support the modeling and coordinated execution of business processes within an organization or across organizational boundaries. Although some research efforts have addressed requirements for authorization and access control for workflow systems, little attention has been paid to the requirements as they apply to application data accessed or managed by WfMSs. In this paper, we discuss key access control requirements for application data in workflow applications using examples from the healthcare domain, introduce a classification of application data used in workflow systems by analyzing their sources, and then propose a comprehensive data authorization and …

The Latent Maximum Entropy Principle, Shaojun Wang, Ronald Rosenfeld, Yunxin Zhao, Dale Schuurmans

Kno.e.sis Publications

We present an extension of Jaynes' maximum entropy principle to handle latent variables. We use an EM algorithm that incorporates nested iterative scaling to approximately calculate maximum entropy solutions for this principle, and give a proof of its convergence.

Knowledge Discovery In Biological Datasets Using A Hybrid Bayes Classifier/Evolutionary Algorithm, Michael L. Raymer, Leslie A. Kuhn, William F. Punch

Kno.e.sis Publications

A key element of bioinformatics research is the extraction of meaningful information from large experimental data sets. Various approaches, including statistical and graph theoretical methods, data mining, and computational pattern recognition, have been applied to this task with varying degrees of success. We have previously shown that a genetic algorithm coupled with a k-nearest-neighbors classifier performs well in extracting information about protein-water binding from X-ray crystallographic protein structure data. Using a novel classifier based on the Bayes discriminant function, we present a hybrid algorithm that employs feature selection and extraction to isolate salient features from large biological data sets. The …

Profile Combinatorics For Fragment Selection In Comparative Protein Structure Modeling, Deacon Sweeney, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Sequencing of the human genome was a great stride towards modeling cellular complexes, massive systems whose key players are proteins and DNA. A major bottleneck limiting the modeling process is structure and function annotation for the new genes. Contemporary protein structure prediction algorithms represent the sequence of every protein of known structure with a profile to which the profile of a protein sequence of unknown structure is compared for recognition. We propose a novel approach to increase the scope and resolution of protein structure profiles. Our technique locates equivalent regions among the members of a structurally similar fold family, and …

Online Bayesian Tree-Structured Transformation Of Hmms With Optimal Model Selection For Speaker Adaptation, Shaojun Wang, Yunxin Zhao

Kno.e.sis Publications

This paper presents a new recursive Bayesian learning approach for transformation parameter estimation in speaker adaptation. Our goal is to incrementally transform or adapt a set of hidden Markov model (HMM) parameters for a new speaker and gain large performance improvement from a small amount of adaptation data. By constructing a clustering tree of HMM Gaussian mixture components, the linear regression (LR) or affine transformation parameters for HMM Gaussian mixture components are dynamically searched. An online Bayesian learning technique is proposed for recursive maximum a posteriori (MAP) estimation of LR and affine transformation parameters. This technique has the advantages of …

Semantic Operators And Fixed-Point Theory In Logic Programming, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We consider rather general operators mapping valuations to (sets of) valuations in the context of the semantics of logic programming languages. This notion generalizes several of the standard operators encountered in this subject and is inspired by earlier work of M.C. Fitting. The fixed points of such operators play a fundamental role in logic programming semantics by providing standard models of logic programs and also in determining the computability properties of these standard models. We discuss some of our recent work employing topological ideas, in conjunction with order theory, to establish methods by which one can find the fixed points …

Summarizing Data Sets For Classification, Christopher W. Kinzig, Krishnaprasad Thirunarayan, Gary B. Lamont, Robert E. Marmelstein

Kno.e.sis Publications

This paper describes our approach and experiences with implementing a data mining system using genetic algorithms in C++. In contrast with earlier classification algorithms that tended to “tile” the data sets using some pre-specified “shapes”, the proposed system is based on Marmelstein’s work on determining natural boundaries for class homogeneous regions. These boundaries are further refined to construct a compact set of simple data mining rules for classification.

Query Processing With An Fpga Coprocessor Board, Jack S. Jean, Guozhu Dong, Hwa Zhang, Xinzhong Guo, Baifeng Zhang

Kno.e.sis Publications

In this paper, a commercial FPGA coprocessor board is used to accelerate the processing of queries on a relational database that contains texts and images. FPGA designs for text searching and image matching are described and their performances summarized. A potential design for a database JOIN operator is then studied. A query optimization preprocessor is then proposed.

Making Use Of The Most Expressive Jumping Emerging Patterns For Classification, Jinyan Li, Guozhu Dong, Kotagiri Ramamohanarao

Kno.e.sis Publications

Classification aims to discover a model from training data that can be used to predict the class of test instances. In this paper, we propose the use of jumping emerging patterns (JEPs) as the basis for a new classifier called the JEP-Classifier. Each JEP can capture some crucial difference between a pair of datasets. Then, aggregating all JEPs of large supports can produce a more potent classification power. Procedurally, the JEP-Classifier learns the pair-wise features (sets of JEPs) contained in the training data, and uses the collective impacts contributed by the most expressive pair-wise features to determine the class labels …

Survivability Architecture For Workflow Management Systems, Jorge Cardoso, Zongwei Luo, John A. Miller, Amit P. Sheth, Krzysztof J. Kochut

Kno.e.sis Publications

The survivability of critical infrastructure systems has been gaining increasing concern from the industry. The survivability research area addresses the issue of infrastructure systems that continues to provide pre-established service levels to users in the face of disorders and react to changes in the surrounding environment. Workflow management systems need to be survivable since they are used to support critical and sensitive business processes. They require a high level of dependability and should not allow process instances to be interrupted or aborted due to failures. Moreover, due to their sensitivity, business process should reflect any change in the environment. In …

A "Converse" Of The Banach Contraction Mapping Theorem, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

We prove a type of converse of the Banach contraction mapping theorem for metric spaces: if X is a T₁ topological space and f: X -> X is a function with the unique fixed point a such that fⁿ(x) converges to a for each x is a member of X, then there exists a distance function d on X such that f is a contraction on the complete ultrametric space (X,d) with contractivity factor 1/2. We explore properties of the resulting space (X,d).

Unique Supported-Model Classes Of Logic Programs, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

We study classes of programs, herein called unique supported-model classes, with the property that each program in the class has a unique supported model. Elsewhere, the authors examined these classes from the point of view of operators defined relative to certain three-valued logics. In this paper, we complement our earlier results by considering how unique supported-model classes fit into the framework given by various classes of programs in several well-known approaches to semantics.

Kontraktionssatze Auf Verallgemeinerten Metrischen Raumen, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Latent Maximum Entropy Principle For Statistical Language Modeling, Shaojun Wang, Ronald Rosenfeld, Yunxin Zhao

Kno.e.sis Publications

We describe a unified probabilistic framework for statistical language modeling, the latent maximum entropy principle. The salient feature of this approach is that the hidden causal hierarchical dependency structure can be encoded into the statistical model in a principled way by mixtures of exponential families with a rich expressive power. We first show the problem formulation, solution, and certain convergence properties. We then describe how to use this machine learning technique to model various aspects of natural language, such as syntactic structure of sentences, semantic information in a document. Finally, we draw a conclusion and point out future research directions.