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- Semantic Web (42)
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Articles 361 - 390 of 540
Full-Text Articles in OS and Networks
Semantic Web Applications In Financial Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Semantic Web Applications In Financial Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Wsdl-S: Specification, Tools, Use Cases And Applications, Amit P. Sheth, Kunal Verma, Karthik Gomadam
Wsdl-S: Specification, Tools, Use Cases And Applications, Amit P. Sheth, Kunal Verma, Karthik Gomadam
Kno.e.sis Publications
No abstract provided.
Taxaminer: Improving Taxonomy Label Quality Using Latent Semantic Indexing, Cartic Ramakrishnan, Christopher Thomas, Vipul Kashyap, Amit P. Sheth
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 …
Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth
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 …
Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans
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 …
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
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 …
Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth
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.
Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang
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. …
Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong
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 …
An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli
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.
Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth
Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
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
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 …
Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York
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 …
Openws-Transaction: Enabling Reliable Web Service Transactions, Ivan Vasquez, John A. Miller, Kunal Verma, Amit P. Sheth
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 …
Demonstrating Dynamic Configuration And Execution Of Web Processes, Karthik Gomadam, Kunal Verma, Amit P. Sheth, John A. Miller
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.
Discovering Informative Connection Subgraphs In Multi-Relational Graphs, Cartic Ramakrishnan, William Milnor, Matthew Perry, Amit P. Sheth
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 …
Ontoqa: Metric-Based Ontology Quality Analysis, Samir Tartir, I. Budak Arpinar, Michael Moore, Amit P. Sheth, Boanerges Aleman-Meza
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 …
Semantics For Scientific Experiments And The Web: The Implicit, The Formal And The Powerful, Amit P. Sheth
Semantics For Scientific Experiments And The Web: The Implicit, The Formal And The Powerful, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Optimal Adaptation In Autonomic Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth
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.
Computing For Human Experience And Wellness, Amit P. Sheth
Computing For Human Experience And Wellness, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds
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 …
Ga-Facilitated Knn Classifier Optimization With Varying Similarity Measures, Michael R. Peterson, Travis E. Doom, Michael L. Raymer
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 …
Enterprise Applications Of Semantic Web: The Sweet Spot Of Risk And Compliance, Amit P. Sheth
Enterprise Applications Of Semantic Web: The Sweet Spot Of Risk And Compliance, Amit P. Sheth
Kno.e.sis Publications
Semantic Web is in the transition from vision and research to reality. In this early state, it is important to study the technical capabilities in the context of real-world applications, and how applications built using the Semantic Web technology meet the real market needs. Beyond push from research, it is the market pull and the ability of the technology to meet real business needs that is a key to ultimate success of any technology. In this paper, we discuss the market of Risk and Compliance which presents unique market opportunity combined with challenging technical requirements. We discuss how the Semantic …
Peer-To-Peer Discovery Of Semantic Associations, Matthew Perry, Maciej Janik, Cartic Ramakrishnan, Conrad Ibanez, I. Budak Arpinar, Amit P. Sheth
Peer-To-Peer Discovery Of Semantic Associations, Matthew Perry, Maciej Janik, Cartic Ramakrishnan, Conrad Ibanez, I. Budak Arpinar, Amit P. Sheth
Kno.e.sis Publications
The Semantic Web vision promises an extension of the current Web in which all data is annotated with machine understandable metadata. The relationship-centric nature of this data has led to the definition of Semantic Associations, which are complex relationships between resources. Semantic Associations attempt to answer queries of the form “how are resource A and resource B related?” Knowing how two entities are related is a crucial question in knowledge discovery applications. Much the same way humans collaborate and interact to form new knowledge, discovery of Semantic Associations across repositories on a peer-to-peer network can allow peers to share their …
A Modular Approach To Document Indexing And Semantic Search, Dhanya Ravishankar, Krishnaprasad Thirunarayan, Trivikram Immaneni
A Modular Approach To Document Indexing And Semantic Search, Dhanya Ravishankar, Krishnaprasad Thirunarayan, Trivikram Immaneni
Kno.e.sis Publications
This paper develops a modular approach to improving effectiveness of searching documents for information by reusing and integrating mature software components such as Lucene APIs, WORDNET, LSA techniques, and domain-specific controlled vocabulary. To evaluate the practical benefits, the prototype was used to query MEDLINE database, and to locate domain-specific controlled vocabulary terms in Materials and Process Specifications. Its extensibility has been demonstrated by incorporating a spell-checker for the input query, and by structuring the retrieved output into hierarchical collections for quicker assimilation. It is also being used to experimentally explore the relationship between LSA and document clustering using 20-mini-newsgroups and …
On Embedding Machine-Processable Semantics Into Documents, Krishnaprasad Thirunarayan
On Embedding Machine-Processable Semantics Into Documents, Krishnaprasad Thirunarayan
Kno.e.sis Publications
Most Web and legacy paper-based documents are available in human comprehensible text form, not readily accessible to or understood by computer programs. Here, we investigate an approach to amalgamate XML technology with programming languages for representational purposes that can enhance traceability, thereby facilitating semiautomatic extraction and update. Specifically, we propose a modular technique to embed machine-processable semantics into a text document with tabular data via annotations, resulting sometimes in ill-formed XML fragments, and evaluate this technique vis a vis document querying, manipulation, and integration. The ultimate aim is to be able to author and extract human-readable and machine-comprehensible parts of …
A Semantic Template Based Designer For Semantic Web Processes, Ranjit Mulye, John A. Miller, Kunal Verma, Karthik Gomadam, Amit P. Sheth
A Semantic Template Based Designer For Semantic Web Processes, Ranjit Mulye, John A. Miller, Kunal Verma, Karthik Gomadam, Amit P. Sheth
Kno.e.sis Publications
The growing popularity of service oriented computing based on Web services standards is creating a need for paradigms to represent and design business processes. Significant work has been done in the representation aspects with regards to WSBPEL. However, design and modeling of business processes is still an open issue. In this paper, we present a novel designer for business processes, which allows for intuitive modeling of Web processes, as well as using a template based approach for semi-automatically integrating partners either at design time or at deployment time. This work has been done as part of the METEOR-S project, which …
Lifecycle Of Semantic Web Processes, Jorge Cardoso, Chistoph Bussler, Amit P. Sheth
Lifecycle Of Semantic Web Processes, Jorge Cardoso, Chistoph Bussler, Amit P. Sheth
Kno.e.sis Publications
This tutorial presents what can be achieved by symbiotic synthesis of two of the most important research and technology application areas: Web Services and the Semantic Web. It presents the more recent evolution of the Web Service platform towards rich Web Service and process model annotation, and explores some of the promises and challenges in applying semantics to each of the steps in the Semantic Web Process lifecycle.
Web Service Semantics - Wsdl-S, Rama Akkiraju, Joel Farrell, John A. Miller, Meenakshi Nagarajan, Amit P. Sheth, Kunal Verma
Web Service Semantics - Wsdl-S, Rama Akkiraju, Joel Farrell, John A. Miller, Meenakshi Nagarajan, Amit P. Sheth, Kunal Verma
Kno.e.sis Publications
Web services have primarily been designed for providing inter-operability between business applications. Current technologies assume a large amount of human interaction, for integrating two applications. This is primarily due to the fact that business process integration requires understanding of data and functions of the involved entities. Semantic Web technologies, powered by description logic based languages like OWL[1], aim to add greater meaning to Web content, by annotating the data with ontologies. Ontologies provide a mechanism of providing shared conceptualizations of domains. This allows agents to get an understanding of users’ Web content and greatly reduces human interaction for meaningful Web …
Ga-Facilitated Classifier Optimization With Varying Similarity Measures, Michael R. Peterson, Travis E. Doom, Michael L. Raymer
Ga-Facilitated 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 classification. Traditional knn classifiers employ Euclidian distance to assess neighbor similarity, though other measures may also be used. GAs can search for optimal linear weights of features to improve knn performance using both Euclidian distance and cosine similarity. GAs also optimize additive feature offsets in search of an optimal point of reference for assessing angular similarity using the cosine measure. This poster explores weight and offset optimization for knn with varying similarity measures, including Euclidian distance (weights only), cosine similarity, and Pearson correlation. The use of offset optimization …