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Articles 271 - 300 of 691
Full-Text Articles in Databases and Information Systems
Computing For The Human Experience: Semantics-Empowered Sensors, Services, And Social Computing On The Ubiquitous Web, Amit P. Sheth
Computing For The Human Experience: Semantics-Empowered Sensors, Services, And Social Computing On The Ubiquitous Web, Amit P. Sheth
Kno.e.sis Publications
People are on the verge of an era in which the human experience can be enriched in ways they couldn't have imagined two decades ago. Rather than depending on a single technology, people progressed with several whose semantics-empowered convergence and integration will enable us to capture, understand, and reapply human knowledge and intellect. Such capabilities will consequently elevate our technological ability to deal with the abstractions, concepts, and actions that characterize human experiences. This will herald computing for human experience (CHE). The CHE vision is built on a suite of technologies that serves, assists, and cooperates with humans to nondestructively …
Provenance Context Entity (Pace): Scalable Provenance Tracking For Scientific Rdf Data, Satya S. Sahoo, Olivier Bodenreider, Pascal Hitzler, Amit P. Sheth, Krishnaprasad Thirunarayan
Provenance Context Entity (Pace): Scalable Provenance Tracking For Scientific Rdf Data, Satya S. Sahoo, Olivier Bodenreider, Pascal Hitzler, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The Resource Description Framework (RDF) format is being used by a large number of scientific applications to store and disseminate their datasets. The provenance information, describing the source or lineage of the datasets, is playing an increasingly significant role in ensuring data quality, computing trust value of the datasets, and ranking query results. Current provenance tracking approaches using the RDF reification vocabulary suffer from a number of known issues, including lack of formal semantics, use of blank nodes, and application-dependent interpretation of reified RDF triples. In this paper, we introduce a new approach called Provenance Context Entity (PaCE) that uses …
A Study In Hadoop Streaming With Matlab For Nmr Data Processing, Kalpa Gunaratna, Paul E. Anderson, Ajith Harshana Ranabahu, Amit P. Sheth
A Study In Hadoop Streaming With Matlab For Nmr Data Processing, Kalpa Gunaratna, Paul E. Anderson, Ajith Harshana Ranabahu, Amit P. Sheth
Kno.e.sis Publications
Applying Cloud computing techniques for analyzing large data sets has shown promise in many data-driven scientific applications. Our approach presented here is to use Cloud computing for Nuclear Magnetic Resonance (NMR)data analysis which normally consists of large amounts of data. Biologists often use third party or commercial software for ease of use. Enabling the capability to use this kind of software in a Cloud will be highly advantageous in many ways. Scripting languages especially designed for clouds may not have the flexibility biologists need for their purposes. Although this is true, they are familiar with special software packages that allow …
Twitris 2.0 : Semantically Empowered System For Understanding Perceptions From Social Data, Ashutosh Sopan Jadhav, Hemant Purohit, Pavan Kapanipathi, Pramod Anantharam, Ajith H. Ranabahu, Vinh Nguyen, Pablo N. Mendes, Alan Gary Smith, Michael Cooney, Amit P. Sheth
Twitris 2.0 : Semantically Empowered System For Understanding Perceptions From Social Data, Ashutosh Sopan Jadhav, Hemant Purohit, Pavan Kapanipathi, Pramod Anantharam, Ajith H. Ranabahu, Vinh Nguyen, Pablo N. Mendes, Alan Gary Smith, Michael Cooney, Amit P. Sheth
Kno.e.sis Publications
We present Twitris 2.0, a Semantic Web application that facilitates understanding of social perceptions by Semantics-based processing of massive amounts of event-centric data. Twitris 2.0 addresses challenges in large scale processing of social data, preserving spatio-temporal-thematic properties. Twitris 2.0 also covers context based semantic integration of multiple Web resources and expose semantically enriched social data to the public domain. Semantic Web technologies enable the systematic integration and analysis abilities.
Power Of Clouds In Your Pocket: An Efficient Approach For Cloud Mobile Hybrid Application Development, Ashwin Manjunatha, Ajith Harshana Ranabahu, Amit P. Sheth, Krishnaprasad Thirunarayan
Power Of Clouds In Your Pocket: An Efficient Approach For Cloud Mobile Hybrid Application Development, Ashwin Manjunatha, Ajith Harshana Ranabahu, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The advancements in computing have resulted in a boom of cheap, ubiquitous, connected mobile devices as well as seemingly unlimited, utility style, pay as you go computing resources, commonly referred to as Cloud computing. However, taking full advantage of this mobile and cloud computing landscape, especially for the data intensive domains has been hampered by the many heterogeneities that exist in the mobile space as well as the Cloud space. Our research focuses on exploiting the capabilities of the mobile and cloud landscape by defining a new class of applications called cloud mobile hybrid (CMH) applications and a Domain Specific …
Semantic Web – Interoperability, Usability, Applicability, Pascal Hitzler, Krzysztof Janowicz
Semantic Web – Interoperability, Usability, Applicability, Pascal Hitzler, Krzysztof Janowicz
Computer Science and Engineering Faculty Publications
No abstract provided.
Approximate Instance Retrieval On Ontologies, Tuvshintur Tserendorj, Stephan Grimm, Pascal Hitzler
Approximate Instance Retrieval On Ontologies, Tuvshintur Tserendorj, Stephan Grimm, Pascal Hitzler
Computer Science and Engineering Faculty Publications
With the development of more expressive description logics (DLs) for the Web Ontology Language OWL the question arises how we can properly deal with the high computational complexity for efficient reasoning. In application cases that require scalable reasoning with expressive ontologies, non-standard reasoning solutions such as approximate reasoning are necessary to tackle the intractability of reasoning in expressive DLs. In this paper, we are concerned with the approximation of the reasoning task of instance retrieval on DL knowledge bases, trading correctness of retrieval results for gain of speed. We introduce our notion of an approximate concept extension and we provide …
Semantics Centric Solutions For Application And Data Portability In Cloud Computing, Ajith Harshana Ranabahu, Amit P. Sheth
Semantics Centric Solutions For Application And Data Portability In Cloud Computing, Ajith Harshana Ranabahu, Amit P. Sheth
Kno.e.sis Publications
Cloud computing has become one of the key considerations both in academia and industry. Cheap, seemingly unlimited computing resources that can be allocated almost instantaneously and pay-as-you-go pricing schemes are some of the reasons for the success of Cloud computing. The Cloud computing landscape, however, is plagued by many issues hindering adoption. One such issue is vendor lock-in, forcing the Cloud users to adhere to one service provider in terms of data and application logic. Semantic Web has been an important research area that has seen significant attention from both academic and industrial researchers. One key property of Semantic Web …
Save Gas Using Your Office Computer From Home, Steve Duckworth, Damon Armour, Jeff Heck
Save Gas Using Your Office Computer From Home, Steve Duckworth, Damon Armour, Jeff Heck
Georgia Library Quarterly
The article discusses the protocols used to establish remote computer connections from home. The Remote Desktop Protocol (RDP) used in Windows 7 connecting to a Windows 2008 server reportedly allows the playing of high-definition video using Media Player. It is stated that commercial product connections which may bypass security infrastructure are risky because of the home computer's possible insecurity and that home devices used for business purposes may be legally searched by the state.
A Reasonable Semantic Web, Pascal Hitzler, Frank Van Harmelen
A Reasonable Semantic Web, Pascal Hitzler, Frank Van Harmelen
Computer Science and Engineering Faculty Publications
The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which forces us to question established lines of research and to rethink the underlying approaches. We argue that reasoning for the Semantic Web should be understood as "shared inference," which is not necessarily based on deductive methods. Model-theoretic semantics (and sound and complete reasoning based on it) functions as a gold standard, but applications dealing with large-scale and noisy data usually cannot afford the required runtimes. Approximate methods, including deductive ones, but also approaches based on …
Automated Isolation Of Translational Efficiency Bias That Resists The Confounding Effect Of Gc(At)-Content, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
Automated Isolation Of Translational Efficiency Bias That Resists The Confounding Effect Of Gc(At)-Content, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
Kno.e.sis Publications
Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Detection of this bias is an important tool …
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Kno.e.sis Publications
In this paper we discuss the collection, semantic annotation and analysis of real-time social signals from micro-blogging data. We focus on users interested in analyzing social signals collectively for sensemaking. Our proposal enables flexibility in selecting subsets for analysis, alleviating information overload. We define an architecture that is based on state-of-the-art Semantic Web technologies and a distributed publish subscribe protocol for real time communication. In addition, we discuss our method and application in a scenario related to the health care reform in the United States.
Continuous Semantics To Analyze Real-Time Data, Amit P. Sheth, Christopher Thomas, Pankaj Mehra
Continuous Semantics To Analyze Real-Time Data, Amit P. Sheth, Christopher Thomas, Pankaj Mehra
Kno.e.sis Publications
Increasingly we are presented with dynamic domains involved in social, mobile, and sensor webs. Such domains are spontaneous (arising suddenly), follow a period of rapid evolution, involving real-time or near real-time data, involve many distributed participants and diverse viewpoints involving topical or contentious subjects, and involve feature context colored by local knowledge and sociocultural backgrounds. This article present continuous semantics can help us model such dynamic domains and analyze the related real-time data. Capabilities include crating dynamic domain model by mining social data, and using dynamic models for semantic analysis of real-time data.
Research In Semantic Web And Information Retrieval: Trust, Sensors, And Search, Krishnaprasad Thirunarayan
Research In Semantic Web And Information Retrieval: Trust, Sensors, And Search, Krishnaprasad Thirunarayan
Kno.e.sis Publications
No abstract provided.
Sparql Query Re-Writing For Spatial Datasets Using Partonomy Based Transformation Rules, Prateek Jain, Cory Andrew Henson, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Sparql Query Re-Writing For Spatial Datasets Using Partonomy Based Transformation Rules, Prateek Jain, Cory Andrew Henson, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Kno.e.sis Publications
Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology’s containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query …
A Local Qualitative Approach To Referral And Functional Trust, Krishnaprasad Thirunarayan, Dharan Althuru, Cory Andrew Henson, Amit P. Sheth
A Local Qualitative Approach To Referral And Functional Trust, Krishnaprasad Thirunarayan, Dharan Althuru, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Trust and confidence are becoming key issues in diverse applications such as ecommerce, social networks, semantic sensor web, semantic web information retrieval systems, etc. Both humans and machines use some form of trust to make informed and reliable decisions before acting. In this work, we briefly review existing work on trust networks, pointing out some of its drawbacks. We then propose a local framework to explore two different kinds of trust among agents called referral trust and functional trust, that are modelled using local partial orders, to enable qualitative trust personalization. The proposed approach formalizes reasoning with trust, distinguishing between …
Towards Reasoning Pragmatics, Pascal Hitzler
Towards Reasoning Pragmatics, Pascal Hitzler
Computer Science and Engineering Faculty Publications
The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which force us to question established lines of research and to rethink the underlying approaches.
A Contrast Pattern Based Clustering Quality Index For Categorical Data, Qingbao Liu, Guozhu Dong
A Contrast Pattern Based Clustering Quality Index For Categorical Data, Qingbao Liu, Guozhu Dong
Kno.e.sis Publications
Since clustering is unsupervised and highly explorative, clustering validation (i.e. assessing the quality of clustering solutions) has been an important and long standing research problem. Existing validity measures have significant shortcomings. This paper proposes a novel contrast pattern based clustering quality index (CPCQ) for categorical data, by utilizing the quality and diversity of the contrast patterns (CPs) which contrast the clusters in clusterings. High quality CPs can characterize clusters and discriminate them against each other. Experiments show that the CPCQ index (1) can recognize that expert-determined classes are the best clusters for many datasets from the UCI repository; (2) does …
Ontology-Driven Provenance Management In Escience: An Application In Parasite Research, Satya S. Sahoo, D. Brent Weatherly, Raghava Mutharaju, Pramod Anantharam, Amit P. Sheth, Rick L. Tarleton
Ontology-Driven Provenance Management In Escience: An Application In Parasite Research, Satya S. Sahoo, D. Brent Weatherly, Raghava Mutharaju, Pramod Anantharam, Amit P. Sheth, Rick L. Tarleton
Kno.e.sis Publications
Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be underpinned by formal semantics to enable analysis of large scale provenance information by software applications. Further, effective analysis of provenance information requires well-defined query mechanisms to support complex queries over large datasets. This paper introduces an ontology-driven provenance management infrastructure for biology experiment data, as part …
An Anytime Algorithm For Computing Inconsistency Measurement, Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin
An Anytime Algorithm For Computing Inconsistency Measurement, Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin
Computer Science and Engineering Faculty Publications
Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first analyze its computational complexity. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximation of the inconsistency degree from above and below. We show that …
A Survey Of The Semantic Specification Of Sensors, Michael Compton, Cory Andrew Henson, Laurent Lefort, Holger Neuhaus, Amit P. Sheth
A Survey Of The Semantic Specification Of Sensors, Michael Compton, Cory Andrew Henson, Laurent Lefort, Holger Neuhaus, Amit P. Sheth
Kno.e.sis Publications
Semantic sensor networks use declarative descriptions of sensors promote reuse and integration, and to help solve the difficulties of installing, querying and maintaining complex, heterogeneous sensor networks. This paper reviews the state of the art for the semantic specification of sensors, one of the fundamental technologies in the semantic sensor network vision. Twelve sensor ontologies are reviewed and analysed for the range and expressive power of their concepts. The reasoning and search technology developed in conjunction with these ontologies is also reviewed, as is technology for annotating OGC standards with links to ontologies. Sensor concepts that cannot be expressed accurately …
Provenir Ontology: Towards A Framework For Escience Provenance Management, Satya S. Sahoo, Amit P. Sheth
Provenir Ontology: Towards A Framework For Escience Provenance Management, Satya S. Sahoo, Amit P. Sheth
Kno.e.sis Publications
Provenance metadata describes the 'lineage' or history of an entity and necessary information to verify the quality of data, validate experiment protocols, and associate trust value with scientific results. eScience projects generate data and the associated provenance metadata in a distributed environment (such as myGrid) and on a very large scale that often precludes manual analysis. Given this scenario, provenance information should be, (a) interoperable across projects, research groups, and application domains, and (b) support analysis over large datasets using reasoning to discover implicit information. In this paper, we introduce an ontology-driven framework for eScience provenance management underpinned by an …
Suggestions For Owl 3, Pascal Hitzler
Suggestions For Owl 3, Pascal Hitzler
Computer Science and Engineering Faculty Publications
With OWL 2 about to be completed, it is the right time to start discussions on possible future modifications of OWL. We present here a number of suggestions in order to discuss them with the OWL user community. They encompass expressive extensions on polynomial OWL 2 profiles, a suggestion for an OWL Rules language, and expressive extensions for OWL DL.
Ibm Altocumulus: A Cross-Cloud Middleware And Platform, E. Michael Maximilien, Ajith Harshana Ranabahu, Roy Engehausen, Laura Anderson
Ibm Altocumulus: A Cross-Cloud Middleware And Platform, E. Michael Maximilien, Ajith Harshana Ranabahu, Roy Engehausen, Laura Anderson
Kno.e.sis Publications
Cloud computing has become the new face of computing and promises to offer virtually unlimited, cheap, readily available, "utility type" computing resources. Many vendors have entered this market with different offerings ranging from infrastructure-as-a-service such as Amazon, to fully functional platform services such as Google App Engine. However, as a result of this heterogeneity, deploying applications to a cloud and managing them needs to be done using vendor specific methods. This "lock in" is seen as a major hurdle in adopting cloud technologies to the enterprise. IBM Altocumulus, the cloud middleware platform from IBM Almaden Services Research, aims to solve …
Paraconsistent Reasoning For Owl 2, Yue Ma, Pascal Hitzler
Paraconsistent Reasoning For Owl 2, Yue Ma, Pascal Hitzler
Computer Science and Engineering Faculty Publications
A four-valued description logic has been proposed to reason with description logic based inconsistent knowledge bases. This approach has a distinct advantage that it can be implemented by invoking classical reasoners to keep the same complexity as under the classical semantics. However, this approach has so far only been studied for the basid description logic ALC. In this paper, we further study how to extend the four-valued semantics to the more expressive description logic SROIQ which underlies the forthcoming revision of the Web Ontology Language, OWL 2, and also investigate how it fares when adapated to tractable description logics including …
A Preferential Tableaux Calculus For Circumscriptive Alco, Stephan Grimm, Pascal Hitzler
A Preferential Tableaux Calculus For Circumscriptive Alco, Stephan Grimm, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Nonmonotonic extensions of description logics (DLs) allow for default and local closed-world reasoning and are an acknowledged desired feature for applications, e.g. in the Semantic Web. A recent approach to such an extension is based on McCarthy's circumscription, which rests on the principle of minimising the extension of selected predicates to close off dedicated parts of a domain model. While decidability and complexity results have been established in the literature, no practical algorithmisation for circumscriptive DLs has been proposed so far. In this paper, we present a tableaux calculus that can be used as a decision procedure for concept satisfiability …
A Best Practice Model For Cloud Middleware Systems, Ajith Harshana Ranabahu, E. Michael Maximilien
A Best Practice Model For Cloud Middleware Systems, Ajith Harshana Ranabahu, E. Michael Maximilien
Kno.e.sis Publications
Cloud computing is the latest trend in computing where the intention is to facilitate cheap, utility type computing resources in a service-oriented manner. However, the cloud landscape is still maturing and there are heterogeneities between the clouds, ranging from the application development paradigms to their service interfaces,and scaling approaches. These differences hinder the adoption of cloud by major enterprises. We believe that a cloud middleware can solve most of these issues to allow cross-cloud inter-operation. Our proposed system is Altocumulus, a cloud middleware that homogenizes the clouds. In order to provide the best use of the cloud resources and make …
Context And Domain Knowledge Enhanced Entity Spotting In Informal Text, Daniel Gruhl, Meena Nagarajan, Jan Pieper, Christine Robson, Amit P. Sheth
Context And Domain Knowledge Enhanced Entity Spotting In Informal Text, Daniel Gruhl, Meena Nagarajan, Jan Pieper, Christine Robson, Amit P. Sheth
Kno.e.sis Publications
This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album “Music” or Lilly Allen’s pop hit “Smile”.
We evaluate improvements in annotation accuracy that can be obtained by restricting the set of possible entities using real-world constraints. We find that constrained domain entity extraction raises the annotation accuracy significantly, making an …
Context Is Highly Contextual!, Amit P. Sheth
Context Is Highly Contextual!, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
“Best K”: Critical Clustering Structures In Categorical Datasets, Keke Chen, Ling Liu
“Best K”: Critical Clustering Structures In Categorical Datasets, Keke Chen, Ling Liu
Kno.e.sis Publications
The demand on cluster analysis for categorical data continues to grow over the last decade. A well-known problem in categorical clustering is to determine the best K number of clusters. Although several categorical clustering algorithms have been developed, surprisingly, none has satisfactorily addressed the problem of best K for categorical clustering. Since categorical data does not have an inherent distance function as the similarity measure, traditional cluster validation techniques based on geometric shapes and density distributions are not appropriate for categorical data. In this paper, we study the entropy property between the clustering results of categorical data with different K …