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- Semantic Web (2)
- Adding Semantics to UDDI (1)
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- Cross-Organizational Business Process (1)
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- E-Workflows (1)
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- Logic Programming (1)
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- RDF (1)
- Responsibility Based Exception Handling (1)
- Scientific data clustering (1)
- Semantic Annotation of Web Service (1)
- Semantic Associations (1)
- Semantic Extensions to WSDL (1)
- Semantic Heterogeneity (1)
- Semantic Web Mining (1)
- Semantic Web Process (1)
- Semantic Web Querying (1)
Articles 1 - 27 of 27
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Semantic (Web) Technology In Action: Ontology Driven Information Systems For Search, Integration, And Analysis, Amit P. Sheth, Cartic Ramakrishnan
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 …
Semantic Web Processes: Semantics Enabled Annotation, Discovery, Composition, And Orchestration Of Web Scale Processes, Jorge Cardoso, Amit P. Sheth
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.
Validating And Refining Clusters Via Visual Rendering, Keke Chen, Ling Liu
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 …
Towards (Semi-) Automatic Generation Of Bio-Medical Ontologies, Vipul Kashyap, Cartic Ramakrishnan, Thomas Rindflesch
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 …
Semantic E-Workflow Composition, Jorge Cardoso, Amit P. Sheth
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 …
What Can Semantics Do For Bioinformatics?, Amit P. Sheth
Semantic Web In Action: Ontology-Driven Information Search, Integration And Analysis, Amit P. Sheth
Semantic Web In Action: Ontology-Driven Information Search, Integration And Analysis, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Christian Halaschek-Wiener, I. Budak Arpinar, Amit P. Sheth
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 …
Continuity Of Semantic Operators In Logic Programming And Their Approximation By Artificial Neural Networks, Pascal Hitzler, Anthony K. Seda
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.
Context-Aware Semantic Association Ranking, Boanerges Aleman-Meza, Chris Halaschek, I. Budak Arpinar, Amit P. Sheth
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 …
Learning Mixture Models With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao
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.
Boltzmann Machine Learning With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao
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.
A Visual Framework Invites Human Into The Clustering Process, Keke Chen, Ling Liu
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.
Toward A Comprehensive Supplement For Language Courses, Krishnaprasad Thirunarayan, Stephen P. Carl
Toward A Comprehensive Supplement For Language Courses, Krishnaprasad Thirunarayan, Stephen P. Carl
Kno.e.sis Publications
No abstract provided.
Adding Semantics To Web Services Standards, Kaarthik Sivashanmugam, Kunal Verma, Amit P. Sheth, John Miller
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 …
Semantic Web Process Lifecycle: Role Of Semantics In Annotation, Discovery, Composition And Orchestration, Amit P. Sheth
Semantic Web Process Lifecycle: Role Of Semantics In Annotation, Discovery, Composition And Orchestration, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Healthcare Enterprise Process Development And Integration, Kemafor Anyanwu, Amit P. Sheth, Jorge Cardoso, John A. Miller, Krzysztof J. Kochut
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 …
Exception Handling For Conflict Resolution In Cross-Organizational Workflows, Zongwei Luo, Amit P. Sheth, Krzysztof Kochut, I. Budak Arpinar
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, …
Ρ-Queries: Enabling Querying For Semantic Associations On The Semantic Web, Kemafor Anyanwu, Amit P. Sheth
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 …
Identifying Patterns In Dna Change, Jason R. Gilder, Dan E. Krane, Travis E. Doom, Michael L. Raymer
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 …
Ontology Driven Information Systems In Action (Capturing And Applying Existing Knowledge To Semantic Applications), Amit P. Sheth
Ontology Driven Information Systems In Action (Capturing And Applying Existing Knowledge To Semantic Applications), Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Generalized Metrics And Uniquely Determined Logic Programs, Pascal Hitzler, Anthony K. Seda
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, …
Formal Concept Analysis And Resolution On Algebraic Domains - Preliminary Report, Matthias Wendt, Pascal Hitzler
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.
Semantic Web Processes, Jorge Cardoso, Amit P. Sheth
Semantic Web Processes, Jorge Cardoso, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Learning Continuous Latent Variable Models With Bregman Divergences, Shaojun Wang, Dale Schuurmans
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.
Web Service: Been There, Done That?, Steffen Staab, Will Van Der Aalst, V. Richard Benjamins, Amit P. Sheth, John A. Miller, Chistoph Bussler, Alexander Maedche, Dieter Fensel, Dennis Gannon
Web Service: Been There, Done That?, Steffen Staab, Will Van Der Aalst, V. Richard Benjamins, Amit P. Sheth, John A. Miller, Chistoph Bussler, Alexander Maedche, Dieter Fensel, Dennis Gannon
Kno.e.sis Publications
Web services can be defined as loosely coupled, reusable software components that semantically encapsulate discrete functionality and are distributed and programmatically accessible over standard Internet protocols. Web services have received a lot of hype, the reasons for which are not easily determined. Some of their benefits might even seem to waste away, once we touch on the nitty-gritty details, because Web services per se do not offer a solution to underlying problems. The contributions included in this section delve into some of these issues, including: pitfalls of workflow issues; structuring procedural knowledge into problem-solving methods; discussing how a low initial …
Semantic N-Gram Language Modeling With The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao
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.