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2003

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Articles 1 - 30 of 33

Full-Text Articles in Bioinformatics

Semantic (Web) Technology In Action: Ontology Driven Information Systems For Search, Integration, And Analysis, Amit P. Sheth, Cartic Ramakrishnan Dec 2003

Semantic (Web) Technology In Action: Ontology Driven Information Systems For Search, Integration, And Analysis, Amit P. Sheth, Cartic Ramakrishnan

Kno.e.sis Publications

Semantics is seen as the key ingredient in the next phase of the Web infrastructure as well as the next generation of information systems applications. In this context, we review some of the reservations expressed about the viability of the Semantic Web. We respond to these by identifying a Semantic Technology that supports the key capabilities also needed to realize the Semantic Web vision, namely representing, acquiring and utilizing knowledge. Given that scalability is a key challenge, we briefly review our observations from developing three classes of real world applications and corresponding technology components: search/browsing, integration, and analytics. We distinguish …

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Semantic Web Processes: Semantics Enabled Annotation, Discovery, Composition, And Orchestration Of Web Scale Processes, Jorge Cardoso, Amit P. Sheth Dec 2003

Semantic Web Processes: Semantics Enabled Annotation, Discovery, Composition, And Orchestration Of Web Scale Processes, Jorge Cardoso, Amit P. Sheth

Kno.e.sis Publications

This tutorial deals with the evolution of inter- Enterprise and Web scale process to support e-commerce and e-services. It taps into the promises of two of the hottest R&D and technology areas: Web services and the Semantic Web. It presents how applying semantics to each of the steps in the Semantic Web Process lifecycle can help address critical issues in reuse, integration and scalability.

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Validating And Refining Clusters Via Visual Rendering, Keke Chen, Ling Liu Nov 2003

Validating And Refining Clusters Via Visual Rendering, Keke Chen, Ling Liu

Kno.e.sis Publications

The automatic clustering algorithms are known to work well in dealing with clusters of regular shapes, e.g. compact spherical/elongated shapes, but may incur higher error rates when dealing with arbitrarily shaped clusters. Although some efforts have been devoted to addressing the problem of skewed datasets, the problem of handling clusters with irregular shapes is still in its infancy, especially in terms of dimensionality of the datasets and the precision of the clustering results considered. Not surprisingly, the statistical indices works ineffective in validating clusters of irregular shapes, too. We address the problem of clustering and validating arbitrarily shaped clusters with …

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Towards (Semi-) Automatic Generation Of Bio-Medical Ontologies, Vipul Kashyap, Cartic Ramakrishnan, Thomas Rindflesch Nov 2003

Towards (Semi-) Automatic Generation Of Bio-Medical Ontologies, Vipul Kashyap, Cartic Ramakrishnan, Thomas Rindflesch

Kno.e.sis Publications

The design and construction of domain specific ontologies and taxonomies requires allocation of huge resources in terms of cost and time. These efforts are human intensive and we need to explore ways of minimizing human involvement and other resources. In the biomedical domain, we seek to leverage resources such as the UMLS1 Metathesaurus and NLP-based applications such as MetaMap2 in conjunction with statistical clustering techniques, to (partially) automate the process. This is expected to be useful to the team involved in developing MeSH and other biomedical taxonomies to identify gaps in the existing taxonomies, and to be able to quickly …

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Semantic E-Workflow Composition, Jorge Cardoso, Amit P. Sheth Nov 2003

Semantic E-Workflow Composition, Jorge Cardoso, Amit P. Sheth

Kno.e.sis Publications

Systems and infrastructures are currently being developed to support Web services. The main idea is to encapsulate an organization's functionality within an appropriate interface and advertise it as Web services. While in some cases Web services may be utilized in an isolated form, it is normal to expect Web services to be integrated as part of workflow processes. The composition of workflow processes that model e-service applications differs from the design of traditional workflows, in terms of the number of tasks (Web services) available to the composition process, in their heterogeneity, and in their autonomy. Therefore, two problems need to …

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What Can Semantics Do For Bioinformatics?, Amit P. Sheth Oct 2003

What Can Semantics Do For Bioinformatics?, Amit P. Sheth

Kno.e.sis Publications

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Semantic Web In Action: Ontology-Driven Information Search, Integration And Analysis, Amit P. Sheth Sep 2003

Semantic Web In Action: Ontology-Driven Information Search, Integration And Analysis, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Continuity Of Semantic Operators In Logic Programming And Their Approximation By Artificial Neural Networks, Pascal Hitzler, Anthony K. Seda Sep 2003

Continuity Of Semantic Operators In Logic Programming And Their Approximation By Artificial Neural Networks, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

One approach to integrating first-order logic programming and neural network systems employs the approximation of semantic operators by feedforward networks. For this purpose, it is necessary to view these semantic operators as continuous functions on the reals. This can be accomplished by endowing the space of all interpretations of a logic program with topologies obtained from suitable embeddings. We will present such topologies which arise naturally out of the theory of logic programming, discuss continuity issues of several well-known semantic operators, and derive some results concerning the approximation of these operators by feedforward neural networks.

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Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Amit P. Sheth Sep 2003

Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Amit P. Sheth

Kno.e.sis Publications

Discovering complex and meaningful relationships, which we call Semantic Associations, is an important challenge. Just as ranking of documents is a critical component of today's search engines, ranking of relationships will be essential in tomorrow's semantic search engines that would support discovery and mining of the Semantic Web. Building upon our recent work on specifying types of Semantic Associations in RDF graphs, which are possible to create through semantic metadata extraction and annotation, we discuss a framework where ranking techniques can be used to identify more interesting and more relevant Semantic Associations. Our techniques utilize alternative ways of specifying the …

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Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Chris Halaschek, I. Budak Arpinar, Amit P. Sheth Aug 2003

Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Chris Halaschek, I. Budak Arpinar, Amit P. Sheth

Kno.e.sis Publications

Discovering complex and meaningful relationships, which we call Semantic Associations, is an important challenge. Just as ranking of documents is a critical component of today's search engines, ranking of relationships will be essential in tomorrow's semantic search engines that would support discovery and mining of the Semantic Web. Building upon our recent work on specifying types of Semantic Associations in RDF graphs, which are possible to create through semantic metadata extraction and annotation, we discuss a framework where ranking techniques can be used to identify more interesting and more relevant Semantic Associations. Our techniques utilize alternative ways of specifying the …

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Learning Mixture Models With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao Aug 2003

Learning Mixture Models With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Kno.e.sis Publications

We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from Jaynes’ maximum entropy principle and from standard maximum likelihood estimation. We demonstrate the LME principle by deriving new algorithms for mixture model estimation, and show how robust new variants of the EM algorithm can be developed. Our experiments show that estimation based on LME generally yields better results than maximum likelihood estimation, particularly when inferring latent variable models from small amounts of data.

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Boltzmann Machine Learning With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao Aug 2003

Boltzmann Machine Learning With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Kno.e.sis Publications

We present a new statistical learning paradigm for Boltzmann machines based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from Jaynes maximum entropy principle and from standard maximum likelihood estimation. We demonstrate the LME principle BY deriving new algorithms for Boltzmann machine parameter estimation, and show how robust and fast new variant of the EM algorithm can be developed. Our experiments show that estimation based on LME generally yields better results than maximum likelihood estimation, particularly when inferring hidden units from small amounts of data.

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A Visual Framework Invites Human Into The Clustering Process, Keke Chen, Ling Liu Jul 2003

A Visual Framework Invites Human Into The Clustering Process, Keke Chen, Ling Liu

Kno.e.sis Publications

Clustering is a technique commonly used in scientific research. The task of clustering inevitably involves human participation - the clustering is not finished when the computer/algorithm finishes but the user has evaluated, understood and accepted the patterns. This defines a human involved "clustering-analysis/evaluation" iteration. Instead of neglecting this human involvement, we provide a visual framework (VISTA) with all power of algorithmic approaches (since their result can be visualized), and in addition we allow the user to steer/monitor/refine the clustering process with domain knowledge. The visual-rendering result also provides a precise pattern for fast post-processing.

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Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg Jul 2003

Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper considers several variations of an optimization problem with potential applications in such areas as biomolecular sequence analysis and image processing. Given a sequence of items, each with a weight and a length, the goal is to find a subsequence of consecutive items of optimal value, where value is either total weight or total weight divided by total length. There may also be a specified lower and/or upper bound on the acceptable length of subsequences. This paper shows that all the variations of the problem are solvable in linear time and space even with non-uniform item lengths and divisible …

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Toward A Comprehensive Supplement For Language Courses, Krishnaprasad Thirunarayan, Stephen P. Carl Jul 2003

Toward A Comprehensive Supplement For Language Courses, Krishnaprasad Thirunarayan, Stephen P. Carl

Kno.e.sis Publications

No abstract provided.

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Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh Jun 2003

Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from these procedures. While much work has been done on assessing the global question of number of clusters in a dataset, relatively little research exists on assessing stability of individual clusters. A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will …

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Adding Semantics To Web Services Standards, Kaarthik Sivashanmugam, Kunal Verma, Amit P. Sheth, John Miller Jun 2003

Adding Semantics To Web Services Standards, Kaarthik Sivashanmugam, Kunal Verma, Amit P. Sheth, John Miller

Kno.e.sis Publications

With the increasing growth in popularity of Web services, discovery of relevant Web services becomes a significant challenge. One approach is to develop semantic Web services where by the Web services are annotated based on shared ontologies, and use these annotations for semantics-based discovery of relevant Web services. We discuss one such approach that involves adding semantics to WSDL using DAML+OIL ontologies. Our approach also uses UDDI to store these semantic annotations and search for Web services based on them. We compare our approach with another initiative to add semantics to support Web service discovery, and show how our approach …

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Semantic Web Process Lifecycle: Role Of Semantics In Annotation, Discovery, Composition And Orchestration, Amit P. Sheth May 2003

Semantic Web Process Lifecycle: Role Of Semantics In Annotation, Discovery, Composition And Orchestration, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Healthcare Enterprise Process Development And Integration, Kemafor Anyanwu, Amit P. Sheth, Jorge Cardoso, John A. Miller, Krzysztof J. Kochut May 2003

Healthcare Enterprise Process Development And Integration, Kemafor Anyanwu, Amit P. Sheth, Jorge Cardoso, John A. Miller, Krzysztof J. Kochut

Kno.e.sis Publications

Healthcare enterprises involve complex processes that span diverse groups and organisations. These processes involve clinical and administrative tasks, large volumes of data, and large numbers of patients and personnel. The tasks can be performed either by humans or by automated systems. In the latter case, the tasks are supported by a variety of software applications and information systems which are very often heterogeneous, autonomous, and distributed. The development of systems to manage and automate these processes has increasingly played an important role in improving the efficiency of healthcare enterprises. In this paper we look at four healthcare and medical applications …

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Exception Handling For Conflict Resolution In Cross-Organizational Workflows, Zongwei Luo, Amit P. Sheth, Krzysztof Kochut, I. Budak Arpinar May 2003

Exception Handling For Conflict Resolution In Cross-Organizational Workflows, Zongwei Luo, Amit P. Sheth, Krzysztof Kochut, I. Budak Arpinar

Kno.e.sis Publications

Workflow management systems (WfMSs) are being increasingly deployed to deliver e-business transactions across organizational boundaries. To ensure a high service quality in such transactions, exception-handling schemes for conflict resolution are needed. The conflicts primarily arise due to failure of a task in workflow execution because of underlying application, or controlling WfMS component failures or insufficient user input. So far, little progress has been reported in addressing conflict resolution in cross-organizational business processes, though its importance has been recognized. In this paper, we identify the exception handling techniques that support conflict resolution in cross-organizational settings. In particular, we propose a novel, …

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Ρ-Queries: Enabling Querying For Semantic Associations On The Semantic Web, Kemafor Anyanwu, Amit P. Sheth May 2003

Ρ-Queries: Enabling Querying For Semantic Associations On The Semantic Web, Kemafor Anyanwu, Amit P. Sheth

Kno.e.sis Publications

This paper presents the notion of Semantic Associations as complex relationships between resource entities. These relationships capture both a connectivity of entities as well as similarity of entities based on a specific notion of similarity called ρ-isomorphism. It formalizes these notions for the RDF data model, by introducing a notion of a Property Sequence as a type. In the context of a graph model such as that for RDF, Semantic Associations amount to specific certain graph signatures. Specifically, they refer to sequences (i.e. directed paths) here called Property Sequences, between entities, networks of Property Sequences (i.e. undirected paths), or subgraphs …

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Identifying Patterns In Dna Change, Jason R. Gilder, Dan E. Krane, Travis E. Doom, Michael L. Raymer Apr 2003

Identifying Patterns In Dna Change, Jason R. Gilder, Dan E. Krane, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Now that a draft sequence of the human genome is nearly complete, questions regarding both the information contained within our genetic blueprints as well as the manner in which that information content changes over time can be addressed in ways that had not previously been possible. By their very nature, some of the nucleotide sequences present within our genome allow detailed examination of the mode and pattern of evolution that has shaped our genetic instructions over time spans of tens of millions of years. Alu repeats are one example. Using these relatively short, ubiquitous DNA sequences we explore the problem …

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Ontology Driven Information Systems In Action (Capturing And Applying Existing Knowledge To Semantic Applications), Amit P. Sheth Mar 2003

Ontology Driven Information Systems In Action (Capturing And Applying Existing Knowledge To Semantic Applications), Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li Mar 2003

Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li

UW Biostatistics Working Paper Series

Theoretically, many modern statistical procedures are trivial to parallelize. However, practical deployment of a parallelized implementation which is robust and reliably runs on different computational cluster configurations and environments is far from trivial. We present a framework for the R statistical computing language that provides a simple yet powerful programming interface to a computational cluster. This interface allows the development of R functions that distribute independent computations across the nodes of the computational cluster. The resulting framework allows statisticians to obtain significant speed-ups for some computations at little additional development cost. The particular implementation can be deployed in heterogeneous computing …

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Literate Statistical Practice, Anthony Rossini, Friedrich Leisch Mar 2003

Literate Statistical Practice, Anthony Rossini, Friedrich Leisch

UW Biostatistics Working Paper Series

Literate Statistical Practice (LSP, Rossini, 2001) describes an approach for creating self-documenting statistical results. It applies literate programming (Knuth, 1992) and related techniques in a natural fashion to the practice of statistics. In particular, documentation, specification, and descriptions of results are written concurrently with writing and evaluation of statistical programs. We discuss how and where LSP can be integrated into practice and illustrate this with an example derived from an actual statistical consulting project. The approach is simplified through the use of a comprehensive, open source toolset incorporating Noweb, Emacs Speaks Statistics (ESS), Sweave (Ramsey, 1994; Rossini, et al, 2002; …

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Generalized Metrics And Uniquely Determined Logic Programs, Pascal Hitzler, Anthony K. Seda Jan 2003

Generalized Metrics And Uniquely Determined Logic Programs, Pascal Hitzler, Anthony K. Seda

Computer Science and Engineering Faculty Publications

The introduction of negation into logic programming brings the benefit of enhanced syntax and expressibility, but creates some semantical problems. Specifically, certain operators which are monotonic in the absence of negation become non-monotonic when it is introduced, with the result that standard approaches to denotational semantics then become inapplicable. In this paper, we show how generalized metric spaces can be used to obtain fixed-point semantics for several classes of programs relative to the supported model semantics, and investigate relationships between the underlying spaces we employ. Our methods allow the analysis of classes of programs which include the acyclic, locally hierarchical, …

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Formal Concept Analysis And Resolution On Algebraic Domains - Preliminary Report, Matthias Wendt, Pascal Hitzler Jan 2003

Formal Concept Analysis And Resolution On Algebraic Domains - Preliminary Report, Matthias Wendt, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We relate two formerly independent areas: Formal concept analysis and logic of domains. We will establish a correspondence between contextual attribute logic on formal contexts resp. concept lattices and a clausal logic on coherent algebraic cpos. We show how to identify the notion of formal concept in the domain theoretic setting. In particular, we show that a special instance of the resolution rule from the domain logic coincides with the concept closure operator from formal concept analysis. The results shed light on the use of contexts and domains for knowledge representation and reasoning purposes.

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Semantic N-Gram Language Modeling With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao Jan 2003

Semantic N-Gram Language Modeling With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Kno.e.sis Publications

We describe a unified probabilistic framework for statistical language modeling-the latent maximum entropy principle-which can effectively incorporate various aspects of natural language, such as local word interaction, syntactic structure and semantic document information. Unlike previous work on maximum entropy methods for language modeling, which only allow explicit features to be modeled, our framework also allows relationships over hidden features to be captured, resulting in a more expressive language model. We describe efficient algorithms for marginalization, inference and normalization in our extended models. We then present experimental results for our approach on the Wall Street Journal corpus.

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Semantic Web Processes, Jorge Cardoso, Amit P. Sheth Jan 2003

Semantic Web Processes, Jorge Cardoso, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Learning Continuous Latent Variable Models With Bregman Divergences, Shaojun Wang, Dale Schuurmans Jan 2003

Learning Continuous Latent Variable Models With Bregman Divergences, Shaojun Wang, Dale Schuurmans

Kno.e.sis Publications

We present a class of unsupervised statistical learning algorithms that are formulated in terms of minimizing Bregman divergences— a family of generalized entropy measures defined by convex functions. We obtain novel training algorithms that extract hidden latent structure by minimizing a Bregman divergence on training data, subject to a set of non-linear constraints which consider hidden variables. An alternating minimization procedure with nested iterative scaling is proposed to find feasible solutions for the resulting constrained optimization problem. The convergence of this algorithm along with its information geometric properties are characterized.

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