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 …

Predictive Self-Organizing Networks For Text Categorization, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper introduces a class of predictive self-organizing neural networks known as Adaptive Resonance Associative Map (ARAM) for classification of free-text documents. Whereas most sta- tistical approaches to text categorization derive classification knowledge based on training examples alone, ARAM performs supervised learn- ing and integrates user-defined classification knowledge in the form of IF-THEN rules. Through our experiments on the Reuters-21578 news database, we showed that ARAM performed reasonably well in mining categorization knowledge from sparse and high dimensional document feature space. In addition, ARAM predictive accuracy and learning efficiency can be improved by incorporating a set of rules derived from …

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.

The Partial Evaluation Approach To Information Personalization, Naren Ramakrishnan, Saverio Perugini

Computer Science Faculty Publications

Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology— PIPE (‘Personalization is Partial Evaluation’) — for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a …

Aplikasi Wayarles Menggunakan Telefon Bimbit Dengan-Wap, Wan Osman Wan Maria

Student Works (2000-2009)

“Wireless Site Solution using WAP-enabled Mobile Phone” is an application developed based on WAP technology. It makes use of the N-tier Client/Server Architecture to provide users especially those who are still new in this technology. With wireless access to manage their daily task and get latest information as well. The main purpose of this project is to provide an alternative for users in managing their daily tasks in some simple clicks and also to allow users to access information in a very interesting way. There are two major modules in this application which are the user module and administrator module. …

Digital Library Of Thesis, Fong Fong Chong

Student Works (2000-2009)

Digital library of thesis is a web-based library system for submitting, storing and disseminating or theses electronically. This system is proposed to overcome the short comings of the traditional methods of storing and disseminating or printed thesis. Users can use this system to upload their theses in the electronic form to the server and the theses can be retrieved using the efficient search capabilities provided. Source codes can be stored in this system too. This system provides an efficient way or handling source codes by storing the source codes in the reusable components or object form. This is to promote …

Classes Of Logic Programs Which Possess Unique Supported Models, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Logic programming is concerned with the use of logic as a programming language. The main manifestation of this computing paradigm is in the various versions of Prolog which are now available, in which computation is viewed as deduction from sets of Horn clauses, although there is also growing interest in the related form known as answer set programming, see [10]. The reference [1] contains a good survey of the growth of logic programming over the last twenty-five years both as a stand-alone programming language and as a software component of large information systems. One advantage a logic program P has …

Semantic Web And Information Brokering: Opportunities, Commercialization, And Challenges, Amit P. Sheth

Kno.e.sis Publications

From the chairs' report published in SIGMOD record: The keynote address entitled 'Semantic Web and Information Brokering: Opportunities, Early Commercializations, and Challenges' was delivered by Amit Sheth (University of Georgia and Taalee Corp). Sheth characterized semantics as the next step in the evolution of the WWW and stressed the importance of semantically organized information for supporting ubiquitous, powerful, accurate and efficient access to this information. Sheth also reviewed proposals for semantic interoperability frameworks such as the DAML(DARPA Agent Mark-Up Language), the Oingo family of tools for defining concepts and extracting knowledge from large databases, as well as several scenarios on …

Exception Handling In Workflow Systems, Zongwei Luo, Amit P. Sheth, Krzysztof J. Kochut, John A. Miller

Kno.e.sis Publications

In this paper, defeasible workflow is proposed as a framework to support exception handling for workflow management. By using the “justified” ECA rules to capture more contexts in workflow modeling, defeasible workflow uses context dependent reasoning to enhance the exception handling capability of workflow management systems. In particular, this limits possible alternative exception handler candidates in dealing with exceptional situations. Furthermore, a case-based reasoning (CBR) mechanism with integrated human involvement is used to improve the exception handling capabilities. This involves collecting cases to capture experiences in handling exceptions, retrieving similar prior exception handling cases, and reusing the exception handling experiences …

Dimensionality Reduction Using Genetic Algorithms, Michael L. Raymer, William F. Punch, Erik D. Goodman, Leslie A. Kuhn, Anil K. Jain

Kno.e.sis Publications

Pattern recognition generally requires that objects be described in terms of a set of measurable features. The selection and quality of the features representing each pattern affect the success of subsequent classification. Feature extraction is the process of deriving new features from original features to reduce the cost of feature measurement, increase classifier efficiency, and allow higher accuracy. Many feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and classification efficiency, it does not necessarily reduce the number of features to be measured since each …

A New Fixed-Point Theorem For Logic Programming Semantics, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a new fixed-point theorem akin to the Banach contraction mapping theorem, but in the context of a novel notion of generalized metric space, and show how it can be applied to analyse the denotational semantics of certain logic programs. The theorem is obtained by generalizing a theorem of Priess-Crampe and Ribenboim, which grew out of applications within valuation theory, but is also inspired by a theorem of S.G. Matthews which grew out of applications to conventional programming language semantics. The class of programs to which we apply our theorem was defined previously by us in terms of operators …

On-Line Bayesian Speaker Adaptation By Using Tree-Structured Transformation And Robust Priors, Shaojun Wang, Yunxin Zhao

Kno.e.sis Publications

This paper presents new results by using our previously proposed on-line Bayesian learning approach for affine transformation parameter estimation in speaker adaptation. The on-line Bayesian learning technique allows updating parameter estimates after each utterance and it can accommodate flexible forms of transformation functions as well as prior probability density functions. We show through experimental results the robustness of heavy tailed priors to mismatch in prior density estimation. We also show that by properly choosing the transformation matrices and depths of hierarchical trees, recognition performance improved significantly.

Local Properties Of Query Languages, Guozhu Dong, Leonid Libkin, Limsoon Wong

Kno.e.sis Publications

In this paper we study the expressiveness of local queries. By locality we mean — informally — that in order to check if a tuple belongs to the result of a query, one only has to look at a certain predetermined portion of the input. Examples include all relational calculus queries. We start by proving a general result describing outputs of local queries. This result leads to many easy inexpressibility proofs for local queries. We then consider a closely related property, namely, the bounded degree property. It describes the outputs of local queries on structures that locally look “simple.” Every …

The Space Of Jumping Emerging Patterns And Its Incremental Maintenance, Jinyan Li, Kotagiri Ramamohanarao, Guozhu Dong

Kno.e.sis Publications

The concept of jumping emerging patterns (JEPs) has been proposed to describe those discriminating features which only occur in the positive training instances but do not occur in the negative class at all; JEPs have been used to construct classifiers which generally provide better accuracy than the state-of-the-art classifiers such as C4.5. The algorithms for maintaining the space of jumping emerging patterns (JEP space) are presented in this paper. We prove that JEP spaces satisfy the property of convexity. Therefore JEP spaces can be concisely represented by two bounds: consisting respectively of the most general elements and the most specific …

Separating Auxiliary Arity Hierarchy Of First-Order Incremental Evaluation Using (3+1)-Ary Input Relations, Guozhu Dong, Louxin Zhang

Kno.e.sis Publications

Presents a first-order incremental evaluation system that uses first-order queries to maintain a database view defined by a non-first-order query. Reduction of the arity of queries to understand the power of foies; Use of a key lemma for proving a query which encodes the multiple parity problem.

Systems Integration: A Tool For Project Monitoring In The Public Sector, Baharum Noriati

Student Works (2000-2009)

Many computerized systems today operate within organizational boundaries. In the Malaysian public sector, early systems were developed to solve organizational business functions. In the course of developing application systems to resolve specific needs, these organizations hardly look beyond the boundaries of their business domain. This phenomenon led to the existence of islands of information systems within the government sector. In this study, the researcher proposed to look into the issues of systems integration (SI) within the public sector, in general and subsequently proceed to an area where SI is deemed to be appropriate. Project monitoring for the government in Malaysia …

Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan

Computer Science Faculty Publications

The NIST Guide to Available Mathematical Software (GAMS) system at http://gams.nist .gov serves as the gateway to thousands of scientific codes and modules for numerical computation. We describe the PIPE personalization facility for GAMS, whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance. The key idea is to (i) mine structure, and (ii) exploit it in a programmatic manner to generate personalized web pages. Our approach supports both content-based and collaborative personalization and enables information integration from multiple (and complementary) web resources. We present case studies for the domain of linear, …

Imprecise Answers In Distributed Environments: Estimation Of Information Loss For Multi-Ontology Based Query Processing, Eduardo Mena, Vipul Kashyap, Arantza Illarramendi, Amit P. Sheth

Kno.e.sis Publications

The World Wide Web is fast becoming a ubiquitous computing environment. Prevalent keyword-based search techniques are scalable, but are incapable of accessing information based on concepts. We investigate the use of concepts from multiple, real-world pre-existing, domain ontologies to describe the underlying data content and support information access at a higher level of abstraction. It is not practical to have a single domain ontology to describe the vast amounts of data on the Web. In fact, we expect multiple ontologies to be used as different world views and present an approach to "browse" ontologies as a paradigm for information access. …