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Full-Text Articles in OS and Networks

Taxaminer: Improving Taxonomy Label Quality Using Latent Semantic Indexing, Cartic Ramakrishnan, Christopher Thomas, Vipul Kashyap, Amit P. Sheth Jan 2006

Taxaminer: Improving Taxonomy Label Quality Using Latent Semantic Indexing, Cartic Ramakrishnan, Christopher Thomas, Vipul Kashyap, Amit P. Sheth

Kno.e.sis Publications

The development of taxonomies/ontologies is a human intensive process requiring prohibitively large resource commitments in terms of time and cost. In our previous work we have identified an experimentation framework for semi-automatic taxonomy/hierarchy generation from unstructured text. In the preliminary results presented, the taxonomy/hierarchy quality was lower than we had anticipated. In this paper, we present two variations of our experimentation framework, viz. Latent semantic Indexing (LSI) for document indexing and the use of term vectors to prune labels assigned to nodes in the final taxonomy/hierarchy. Using our previous results of taxonomy/hierarchy quality as the baseline we present results that …

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Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth Jan 2006

Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

This work presents an experimental system for data processing in space, time and semantics dimensions using current Semantic Web technologies. The paper describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics dimensions. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed in the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination …

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Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans Jan 2006

Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans

Kno.e.sis Publications

We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data. Our approach is based on extending the minimum entropy regularization framework to the structured prediction case, yielding a training objective that combines unlabeled conditional entropy with labeled conditional likelihood. Although the training objective is no longer concave, it can still be used to improve an initial model (e.g. obtained from supervised training) by iterative ascent. We apply our new training algorithm to the problem of identifying gene and protein …

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An Investigation Of Codon Usage Bias Including Visualization And Quantification In Organisms Exhibiting Multiple Biases, Douglas W. Raiford, Travis E. Doom, Dan E. Krane, Michael L. Raymer Jan 2006

An Investigation Of Codon Usage Bias Including Visualization And Quantification In Organisms Exhibiting Multiple Biases, Douglas W. Raiford, Travis E. Doom, Dan E. Krane, Michael L. Raymer

Kno.e.sis Publications

Prokaryotic genomic sequence data provides a rich resource for bioinformatic analytic algorithms. Information can be extracted in many ways from the sequence data. One often overlooked process involves investigating an organism’s codon usage. Degeneracy in the genetic code leads to multiple codons coding for the same amino acids. Organism’s often preferentially utilize specific codons when coding for an amino acid. This biased codon usage can be a useful trait when predicting a gene’s expressivity or whether the gene originated from horizontal transfer. There can be multiple biases at play in a genome causing errors in the predictive process. For this …

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A Semantic Future For Ai, Rudi Studer, Anupriya Ankolekar, Pascal Hitzler Jan 2006

A Semantic Future For Ai, Rudi Studer, Anupriya Ankolekar, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In our modern information society, people need to manage ever-increasing numbers of personal devices and conduct more of their work and activities online, often making use of heterogeneous services. The amount of information to be processed by each individual is constantly growing, making it increasingly difficult to control, channel, share and make constructive use of it. To mitigate this, computing needs to become much more human-centered, e.g. by presenting personalised information to users and by respecting personal preferences in controlling multiple devices or invoking various services. Appropriate representation of the semantics of the information and functionality of devices and services …

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Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth Jan 2006

Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth

Kno.e.sis Publications

This paper proposes a framework for automatic recognition of domain-specific entities from text, given limited background knowledge, e.g. in form of an ontology. The algorithm exploits several lightweight natural language processing techniques, such as tokenization and stemming, as well as statistical techniques, such as singular value decomposition (SVD) to suggest domain relatedness of unknown entities.

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Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang Jan 2006

Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang

Kno.e.sis Publications

Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a novel "query specific" combination rule: After learning a set of simple belief network classifiers, we produce an answer to each query by combining their individual responses, using weights based inversely on their respective variances around their responses. These variances are based on the uncertainty of the network parameters, which in turn depend on the training datasample. In essence, this variance quantifies the base classifier's confidence of its response to this query. …

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Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong Jan 2006

Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong

Kno.e.sis Publications

The unsupervised nature of cluster analysis means that objects can be clustered in many ways, allowing different clustering algorithms to generate vastly different results. To address this, clustering comparison methods have traditionally been used to quantify the degree of similarity between alternative clusterings. However, existing techniques utilize only the point memberships to calculate the similarity, which can lead to unintuitive results. They also cannot be applied to analyze clusterings which only partially share points, which can be the case in stream clustering. In this paper we introduce a new measure named ADCO, which takes into account density profiles for each …

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An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli Jan 2006

An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli

Kno.e.sis Publications

We present a simple, principled approach to detecting foreground objects in video sequences in real-time. Our method is based on an on-line discriminative learning technique that is able to cope with illumination changes due to discontinuous switching, or illumination drifts caused by slower processes such as varying time of the day. Starting from a discriminative learning principle, we derive a training algorithm that, for each pixel, computes a weighted linear combination of selected past observations with time-decay. We present experimental results that show the proposed approach outperforms existing methods on both synthetic sequences and real video data.

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Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini Jan 2006

Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini

Computer Science Faculty Publications

We demonstrate the use of two user interfaces for interacting with web hierarchies. One uses the dependencies underlying a hierarchy to perform real-time query expansion and, in this way, acts as an in situ feedback mechanism. The other enables the user to cascade the output from one interaction to the input of another, and so on, and, in this way, supports procedural information-seeking tasks without disrupting the flow of interaction.

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Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth Jan 2006

Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Knowledge Modeling And Its Application In Life Sciences: A Tale Of Two Ontologies, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William S. York, Samir Tartir Jan 2006

Knowledge Modeling And Its Application In Life Sciences: A Tale Of Two Ontologies, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William S. York, Samir Tartir

Kno.e.sis Publications

High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics …

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Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York Jan 2006

Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York

Kno.e.sis Publications

Ontologies build the backbone for many life-sciences applications. These ontologies, however, are represented in XML based languages that are meant for machine-consumption and hence are difficult for humans to comprehend. For a meaningful visualization of these ontologies, it is important that the display of entities and relationships captures the cognitive representation of the domain as perceived by the domain experts. In this paper we present OntoVista, an ontology visualization tool that is adaptable to the needs of different domains, especially in the life sciences. While keeping the graph structures as the predominant model, we provide a semantically enhanced graph display …

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Openws-Transaction: Enabling Reliable Web Service Transactions, Ivan Vasquez, John A. Miller, Kunal Verma, Amit P. Sheth Dec 2005

Openws-Transaction: Enabling Reliable Web Service Transactions, Ivan Vasquez, John A. Miller, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

OpenWS-Transaction is an open source middleware that enables Web services to participate in a distributed transaction as prescribed by the WS-Coordination and WS-Transaction set of specifications. Central to the framework are the Coordinator and Participant entities, which can be integrated into existing services by introducing minimal changes to application code. OpenWS-Transaction allows transaction members to recover their original state in case of operational failure by leveraging techniques in logical logging and recovery at the application level. Depending on transaction style, system recovery may involve restoring key application variables and replaying uncommitted database activity. Transactions are assumed to be defined in …

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Demonstrating Dynamic Configuration And Execution Of Web Processes, Karthik Gomadam, Kunal Verma, Amit P. Sheth, John A. Miller Dec 2005

Demonstrating Dynamic Configuration And Execution Of Web Processes, Karthik Gomadam, Kunal Verma, Amit P. Sheth, John A. Miller

Kno.e.sis Publications

Web processes are next generation workflows on the web, created using Web services. In this paper we demonstrate the METEOR-S Configuration and Execution Environment (MCEE) system. It will illustrate the capabilities of the system to a) Discover partners b) Optimize partner selection using constraint analysis, c) Perform interaction protocol and data mediation. A graphical execution monitor to monitor the various phases of execution will be used to demonstrate various aspects of the system.

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Enterprise Systems Manager, Edward Aractingi Dec 2005

Enterprise Systems Manager, Edward Aractingi

IT Research

Presentation on the need of remote systems administration.

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Discovering Informative Connection Subgraphs In Multi-Relational Graphs, Cartic Ramakrishnan, William Milnor, Matthew Perry, Amit P. Sheth Dec 2005

Discovering Informative Connection Subgraphs In Multi-Relational Graphs, Cartic Ramakrishnan, William Milnor, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

Discovering patterns in graphs has long been an area of interest. In most approaches to such pattern discovery either quantitative anomalies, frequency of substructure or maximum flow is used to measure the interestingness of a pattern. In this paper we introduce heuristics that guide a subgraph discovery algorithm away from banal paths towards more "informative" ones. Given an RDF graph a user might pose a question of the form: "What are the most relevant ways in which entity X is related to entity Y?" the response to which is a subgraph connecting X to Y. We use our heuristics to …

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Ontoqa: Metric-Based Ontology Quality Analysis, Samir Tartir, I. Budak Arpinar, Michael Moore, Amit P. Sheth, Boanerges Aleman-Meza Nov 2005

Ontoqa: Metric-Based Ontology Quality Analysis, Samir Tartir, I. Budak Arpinar, Michael Moore, Amit P. Sheth, Boanerges Aleman-Meza

Kno.e.sis Publications

As the Semantic Web gains importance for sharing knowledge on the Internet this has lead to the development and publishing of many ontologies in different domains. When trying to reuse existing ontologies into their applications, users are faced with the problem of determining if an ontology is suitable for their needs. In this paper, we introduce OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics. These metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed …

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Semantics For Scientific Experiments And The Web: The Implicit, The Formal And The Powerful, Amit P. Sheth Nov 2005

Semantics For Scientific Experiments And The Web: The Implicit, The Formal And The Powerful, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Optimal Adaptation In Autonomic Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth Nov 2005

Optimal Adaptation In Autonomic Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth

Kno.e.sis Publications

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service dependencies. For example, in a supply chain process, orders placed by the manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the supplier.

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Dlp Isn't So Bad After All, Peter Haase, Markus Krotzsch, York Sure, Rudi Studer, Pascal Hitzler Nov 2005

Dlp Isn't So Bad After All, Peter Haase, Markus Krotzsch, York Sure, Rudi Studer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We discuss some of the recent controversies concerning the DLP fragment of OWL. We argue that it is a meaningful fragment and can serve as a basic interoperability layer between OWL and logic programming-based ontology languages.

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On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov Nov 2005

On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Computer Science Faculty Publications

In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1-o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and therefore partitions, …

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Modeling Fuzzy Rules With Description Logics, Sudhir Agarwal, Pascal Hitzler Nov 2005

Modeling Fuzzy Rules With Description Logics, Sudhir Agarwal, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In real application scenarios, input data and knowledge is often vague. Likewise, it is often the case that exact reasoning over data is impossible due to complex dependencies between input data and target outputs. For practical applications, however, good approximations often suffice, and efficient calculation of an approximate answer is often preferable over complex processing which may take a long time to come up with an exact answer. Fuzzy logic supports both features by providing fuzzy membership functions and fuzzy IF-THEN rule bases. In this paper, we show how fuzzy membership functions and fuzzy rules can be modeled by means …

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Computing For Human Experience And Wellness, Amit P. Sheth Oct 2005

Computing For Human Experience And Wellness, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds Oct 2005

Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds

Kno.e.sis Publications

This paper summarizes progress to date on the WSU model for engineering mathematics education, an NSF funded curriculum reform initiative at Wright State University. The WSU model seeks to increase student retention, motivation and success in engineering through application-driven, just-in-time engineering math instruction. The WSU approach involves the development of a novel freshman-level engineering mathematics course EGR 101, as well as a large-scale restructuring of the engineering curriculum. By removing traditional math prerequisites and moving core engineering courses earlier in the program, the WSU model shifts the traditional emphasis on math prerequisite requirements to an emphasis on engineering motivation for …

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Ga-Facilitated Knn Classifier Optimization With Varying Similarity Measures, Michael R. Peterson, Travis E. Doom, Michael L. Raymer Sep 2005

Ga-Facilitated Knn Classifier Optimization With Varying Similarity Measures, Michael R. Peterson, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Genetic algorithms are powerful tools for k-nearest neighbors classifier optimization. While traditional knn classification techniques typically employ Euclidian distance to assess pattern similarity, other measures may also be utilized. Previous research demonstrates that GAs can improve predictive accuracy by searching for optimal feature weights and offsets for a cosine similarity-based knn classifier. GA-selected weights determine the classification relevance of each feature, while offsets provide alternative points of reference when assessing angular similarity. Such optimized classifiers perform competitively with other contemporary classification techniques. This paper explores the effectiveness of GA weight and offset optimization for knowledge discovery using knn classifiers with …

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A Comparative Study And Analysis Of Pvm And Mpi For Parallel And Distributed Systems, Dr. Syed Jamal Hussain, Ghufran Ahmed Aug 2005

A Comparative Study And Analysis Of Pvm And Mpi For Parallel And Distributed Systems, Dr. Syed Jamal Hussain, Ghufran Ahmed

International Conference on Information and Communication Technologies

Networks of Workstations (NOWs) based on various operating systems are globally accepted as the standard for computing environments in the IT industry. To harness the tremendous potential for computing capability represented by these NOWs, various new tools are being developed. Parallel Virtual Machine (PVM) and Message Passing Interface (MPI) have existed on UNIX workstations for some time, and are maturing in their capability for handling Distributed Parallel Processing (DPP). This research is aimed to explore each of these two vehicles for DPP, considering capability, ease of use, and availability, and compares their distinguishing features; and also explores programmer interface and …

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Poster Session A: Analyzing & Enhancing Energy Efficient Communication Protocol For Wireless Micro-Sensor Networks, Irfan Majeed Butt, Shoab Ahmed Khan Aug 2005

Poster Session A: Analyzing & Enhancing Energy Efficient Communication Protocol For Wireless Micro-Sensor Networks, Irfan Majeed Butt, Shoab Ahmed Khan

International Conference on Information and Communication Technologies

The paper presents an analysis of energy efficient routing protocols with direct communication protocol. A comparison of these protocols is made analyzing energy consumption at each node and explaining system lifetime after certain rounds. The paper also proposes a novel energy conscious cluster head selection algorithm for making system more reliable and efficient. Simulation shows that our proposed algorithm enhances the system reliability and accuracy.

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Poster Session A: A Multi-Priority Application Framework For Mobile Ad Hoc Networks, M. Ibrahim Channa, Ahsan Chaudhry, Kashif Sharif, Irum Memon Aug 2005

Poster Session A: A Multi-Priority Application Framework For Mobile Ad Hoc Networks, M. Ibrahim Channa, Ahsan Chaudhry, Kashif Sharif, Irum Memon

International Conference on Information and Communication Technologies

The fast spread of small wireless computers has enabled the design and deployment of wireless Ad Hoc networks. Typical applications proposed for such networks include both Real Time and Non-Real Time applications. We propose an architecture that provides a complete framework for Real Time applications and Best Effort traffic. The proposed architecture comprises of an Ad Hoc Routing Protocol for route setup and route repair, a Bandwidth Allocation and Reservation Scheme for Real Time traffic, and a MAC layer protocol that provides traffic differentiation. The Admission Control module is used to admit or reject a new Real Time flow request …

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Keynote: Emerging Era Of Cooperative Empowerment: Grid, Peer-To-Peer, And Community Computing, Dr. Javed I. Khan Aug 2005

Keynote: Emerging Era Of Cooperative Empowerment: Grid, Peer-To-Peer, And Community Computing, Dr. Javed I. Khan

International Conference on Information and Communication Technologies

In this paper we discuss an emerging trend in high performance computing-the social or community computing. The emergence of screensaver computing, grid computing, peer-to-peer systems, and their demonstrated ability to garner computing power as potent as the supercomputers seems to be auspicious. In this paper we discuss the new phenomenon of community computing-including their potential applications in solving a new set of grand challenge problems. We also discuss the previously uncharted technological challenges architects of these new paradigms are addressing.

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