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.

Webtv, Soon Hing Leong

Student Works (2000-2009)

This graduation project report was a partial requirement of the Bachelor Degree of Information Technology. This project focused on the testing and implementation of streaming multimedia files using multicast and unicast technology through Local Area Network with conserving network resources. It is also an effort being carried out to provide a multimedia and interactive base entertainment system for Faculty of Computer Science and Information Technology. Multimedia has become a popular catchword during the last few years. The idea behind a multimedia network is a single network combining an improving all current technologies that realizes fast and convenient access for the …

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.

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. …

Optimization Techniques For Data Intensive Decision Flows, Richard Hull, Francois Llirbat, Bharat Kumar, Gang Zhou, Guozhu Dong, Jianwen Su

Kno.e.sis Publications

For an enterprise to take advantage of the opportunities afforded by electronic commerce it must be able to make decisions about business transactions in near-real-time. In the coming era of segment-of-one marketing, these decisions will be quite intricate, so that customer treatments can be highly personalized, reflecting customer preferences, the customer's history with the enterprise, and targeted business objectives. This paper describes a paradigm called “decision flows” for specifying a form of incremental decision-making that can combine diverse business factors in near-real-time.

This paper introduces and empirically analyzes a variety of optimization strategies for decision flows that are “data-intensive”, i.e. …

Characterizations Of Classes Of Programs By Three-Valued Operators, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Several important classes of normal logic programs, including the classes of acyclic, acceptable, and locally hierarchical programs, have the property that every program in the class has a unique two-valued supported model. In this paper, we call such classes unique supported model classes. We analyse and characterize these classes by means of operators on three-valued logics. Our studies will motivate the definition of a larger unique supported model class which we call the class of Phi-accessible programs. Finally, we show that the class of Phi -accessible programs is computationally adequate in that every partial recursive function can be implemented by …

On-Line Bayesian Tree-Structured Transformation Of Hidden Markov Models 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) the entire set of HMM parameters for a new speaker or new acoustic enviroment from a small amount of adaptation data. By establishing a clustering tree of HMM Gaussian mixture components, the finest affine transformation parameters for individual HMM Gaussian mixture components can be dynamically searched. The on-line Bayesian learning technique proposed in our recent work is used for recursive maximum a posteriori estimation of affine transformation parameters. Speaker adaptation experiments using a 26-letter English alphabet …

Critical It Role In Healthcare: National Agenda, Applications, And Technologies, Jack Corley, Warren Karp, Amit P. Sheth

Kno.e.sis Publications

We share a widely-held vision that tomorrow's health care will be delivered by a distributed team using a knowledge based process that is focused on prevention and wellness. Caregivers will be able to treat and monitor patients where and when needed, capturing data as a natural byproduct of care delivery. Clinical teams with a wide range of skills and expertise will deliver consistent, quality care based on timely, situation-specific knowledge and guidance derived from outcomes evidence. That same knowledge will support advances in healthcare research and education. Home care and remote medicine will increase, reducing the need for high-cost hospitalization. …

Efficient Support For Decision Flows In E-Commerce Applications, Richard Hull, Francois Llirbat, Jianwen Su, Guozhu Dong, Bharat Kumar, Gang Zhou

Kno.e.sis Publications

In the coming era of segment-of-one marketing, decisions about business transactions will be quite intricate, so that customer treatments can be highly individualized, reflecting customer preferences, targeted business objectives, etc. This paper describes a paradigm called “decision flows” for specifying a form of incremental decision-making that can combine a myriad of diverse business factors and be executed in near-realtime. Starting with initial input, a decision flow will iteratively gather and derive additional information until a conclusion is reached. Decision flows can be specified in a rules-based manner that generalizes so-called “business rules” but provides more structure than traditional expert systems. …

A Multilevel Secure Workflow Management System, Myong H. Kang, Judith N. Froscher, Amit P. Sheth, Krzysztof J. Kochut, John A. Miller

Kno.e.sis Publications

The Department of Defense (DoD) needs multilevel secure (MLS) workflow management systems to enable globally distributed users and applications to cooperate across classification levels to achieve mission critical goals. An MLS workflow management system that allows a user to program multilevel mission logic, to securely coordinate widely distributed tasks, and to monitor the progress of the workflow across classification levels is required. In this paper, we present a roadmap for implementing MLS workflows and focus on a workflow builder that is a graphical design tool for specifying such workflows.

How Proteins Fold, Flex, And Bind Other Molecules, Leslie A. Kuhn, Volker Schnecke, Michael L. Raymer, Paul C. Sanschagrin

Kno.e.sis Publications

No abstract provided.

Data Integration By Describing Sources With Constraint Databases, Xun Cheng, Guozhu Dong, Tzekwan Lau, Jianwen Su

Kno.e.sis Publications

We develop a data integration approach for the efficient evaluation of queries over autonomous source databases. The approach is based on some novel applications and extensions of constraint database techniques. We assume the existence of a global database schema. The contents of each data source are described using a set of constraint tuples over the global schema; each such tuple indicates possible contributions from the source. The “source description catalog” (SDC) of a global relation consists of its associated constraint tuples. Such a method of description is advantageous since it is flexible to add new sources and to modify existing …

Efficient Mining Of Partial Periodic Patterns In Time Series Database, Jiawei Han, Guozhu Dong, Yiwen Yin

Kno.e.sis Publications

Partial periodicity search, i.e., search for partial periodic patterns in time-series databases, is an interesting data mining problem. Previous studies on periodicity search mainly consider finding full periodic patterns, where every point in time contributes (precisely or approximately) to the periodicity. However, partial periodicity is very common in practice since it is more likely that only some of the time episodes may exhibit periodic patterns.

We present several algorithms for efficient mining of partial periodic patterns, by exploring some interesting properties related to partial periodicity, such as the Apriori property and the max-subpattern hit set property, and by shared mining …

Multivalued Mappings, Fixed-Point Theorems And Disjunctive Databases, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

In this paper, we discuss the semantics of disjunctive programs and databases and show how multivalued mappings and their fixed points arise naturally within this context. A number of fixed-point theorems for multivalued mappings are considered, some of which are already known and some of which are new. The notion of a normal derivative of a disjunctive program is introduced. Normal derivatives are normal logic programs which are determined by the disjunctive program. Thus, the well-known single-step operator associated with a normal derivative is single-valued, and its fixed points can be found by well-established means. It is shown how fixed …

Maintaining Transitive Closure Of Graphs In Sql, Guozhu Dong, Leonid Libkin, Jianwen Su, Limsoon Wong

Kno.e.sis Publications

It is common knowledge that relational calculus and even SQL are not expressive enough to express recursive queries such as the transitive closure. In a real database system, one can overcome this problem by storing a graph together with its transitive closure and maintaining the latter whenever updates to the former occur. This leads to the concept of an incremental evaluation system, or IES.

Much is already known about the theory of IES but very little has been translated into practice. The purpose of this paper is to fill in this gap by providing a gentle introduction to and …