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Articles 331 - 360 of 540
Full-Text Articles in OS and Networks
Role Of Semantics In Autonomic & Adaptive Web Services And Processes, Amit P. Sheth
Role Of Semantics In Autonomic & Adaptive Web Services And Processes, Amit P. Sheth
Kno.e.sis Publications
The emergence of Service Oriented Architectures (SOA) has created a new paradigm of loosely coupled distributed systems. In the METEOR-S project, we have studied the comprehensive role of semantics in all stages of the life cycle of service and process-- including annotation, publication, discovery, interoperability/data mediation, and composition. In 2002-2003, we had offered a broad framework of semantics consisting of four types:1) Data semantics, 2) Functional semantics, 3) Non-Functional semantics and 4) Execution semantics. This talk describes the need for the four types of semantics, its standards-based support through WSDL-S/SAWSDL, and the need for such semantic representation to dynamic and …
Data Integration, Meenakshi Nagarajan
Glycoo Ontology, Christopher Thomas
Learning To Model Spatial Dependency: Semi-Supervised Discriminative Random Fields, Chi-Hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner
Learning To Model Spatial Dependency: Semi-Supervised Discriminative Random Fields, Chi-Hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner
Kno.e.sis Publications
We present a novel, semi-supervised approach to training discriminative random fields (DRFs) that efficiently exploits labeled and unlabeled training data to achieve improved accuracy in a variety of image processing tasks. We formulate DRF training as a form of MAP estimation that combines conditional loglikelihood on labeled data, given a data-dependent prior, with a conditional entropy regularizer defined on unlabeled data. Although the training objective is no longer concave, we develop an efficient local optimization procedure that produces classifiers that are more accurate than ones based on standard supervised DRF training. We then apply our semi-supervised approach to train DRFs …
Beyond Sawsdl - A Game Plan For Broader Adoption Of Semantic Web Services, Amit P. Sheth
Beyond Sawsdl - A Game Plan For Broader Adoption Of Semantic Web Services, Amit P. Sheth
Kno.e.sis Publications
After a flurry of research activities led by the OWL-S, WSMO, SWSF, and WSDL-S groups, we now have taken the first concrete steps toward building a Semantic Web Services (SWS) based solution, in the form of a W3C candidate recommendation SAWSDL [http://www.w3.org/2002/ws/sawsdl/], associated tools and use cases, and initial applications [1]. Where do we go from here? Researchers among us may be fully convinced of the importance and benefit of adding semantics to Web services and impatient to see their research translated into technologies and adapted for real use. However, I believe we may need to be patient and do …
A Unified Approach To Retrieving Web Documents And Semantic Web Data, Trivikram Immaneni, Krishnaprasad Thirunarayan
A Unified Approach To Retrieving Web Documents And Semantic Web Data, Trivikram Immaneni, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The Semantic Web seems to be evolving into a property-linked web of RDF data, conceptually divorced from (but physically housed in) the hyperlinked web of HTML documents. We discuss the Unified Web model that integrates the two webs and formalizes the structure and the semantics of interconnections between them. We also discuss the Hybrid Query Language which combines the Data and Information Retrieval techniques to provide a convenient and uniform way to retrieve data and documents from the Unified Web. We present the retrieval system SITAR and some preliminary results.
Schema-Driven Relationship Extraction From Unstructured Text, Cartic Ramakrishnan
Schema-Driven Relationship Extraction From Unstructured Text, Cartic Ramakrishnan
Kno.e.sis Publications
No abstract provided.
Sensor Networks Survey, Cory Andrew Henson, Satya S. Sahoo
Sensor Networks Survey, Cory Andrew Henson, Satya S. Sahoo
Kno.e.sis Publications
No abstract provided.
Glycomics Project Overview, Satya S. Sahoo
Glycomics Project Overview, Satya S. Sahoo
Kno.e.sis Publications
No abstract provided.
Sa-Rest: Semantically Interoperable And Easier-To-Use Services And Mashups, Amit P. Sheth, Karthik Gomadam, Jonathan Lathem
Sa-Rest: Semantically Interoperable And Easier-To-Use Services And Mashups, Amit P. Sheth, Karthik Gomadam, Jonathan Lathem
Kno.e.sis Publications
Services based on the representational state transfer (REST) paradigm, a lightweight implementation of a service-oriented architecture, have found even greater success than their heavyweight siblings, which are based on the Web Services Description Language (WSDL.) and SOAP. By using XML-based messaging, RESTful services can bring together discrete data from different services to create meaningful data sets; mashups such as these are extremely popular today.
From “Glycosyltransferase” To “Congenital Muscular Dystrophy”: Integrating Knowledge From Ncbi Entrez Gene And The Gene Ontology, Satya S. Sahoo, Kelly Zeng, Olivier Bodenreider, Amit P. Sheth
From “Glycosyltransferase” To “Congenital Muscular Dystrophy”: Integrating Knowledge From Ncbi Entrez Gene And The Gene Ontology, Satya S. Sahoo, Kelly Zeng, Olivier Bodenreider, Amit P. Sheth
Kno.e.sis Publications
Entrez Gene (EG), Online Mendelian Inheritance in Man (OMIM) and the Gene Ontology (GO) are three complementary knowledge resources that can be used to correlate genomic data with disease information. However, bridging between genotype and phenotype through these resources currently requires manual effort or the development of customized software. In this paper, we argue that integrating EG and GO provides a robust and flexible solution to this problem. We demonstrate how the Resource Description Framework (RDF) developed for the Semantic Web can be used to represent and integrate these resources and enable seamless access to them as a unified resource. …
What, Where And When: Supporting Semantic, Spatial And Temporal Queries In A Dbms, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
What, Where And When: Supporting Semantic, Spatial And Temporal Queries In A Dbms, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
Kno.e.sis Publications
Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. The outcome of the analytical process in these applications often hinges on uncovering and analyzing complex relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful in these applications. However, these analysis mechanisms are primarily intended for thematic relationships. We describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between …
Collecting Expertise Of Researchers For Finding Relevant Experts In A Peer-Review Setting, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar
Collecting Expertise Of Researchers For Finding Relevant Experts In A Peer-Review Setting, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar
Kno.e.sis Publications
We present ideas for determining the expertise of researchers across various areas of computer science and for finding relevant experts/reviewers in a peer review setting. We explain how Semantic Web techniques for data collection and data representation using ontologies can be used in addressing this specific 'ExpertFinder' problem.
Brief Announcement: Space Adaptation: Privacy-Preserving Multiparty Collaborative Mining With Geometric Perturbation, Keke Chen, Ling Liu
Brief Announcement: Space Adaptation: Privacy-Preserving Multiparty Collaborative Mining With Geometric Perturbation, Keke Chen, Ling Liu
Kno.e.sis Publications
No abstract provided.
Evolution And Maintenance Of Frequent Pattern Space When Transactions Are Removed, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong
Evolution And Maintenance Of Frequent Pattern Space When Transactions Are Removed, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong
Kno.e.sis Publications
This paper addresses the maintenance of discovered frequent patterns when a batch of transactions are removed from the original dataset. We conduct an in-depth investigation on how the frequent pattern space evolves under transaction removal updates using the concept of equivalence classes. Inspired by the evolution analysis, an effective and exact algorithm TRUM is proposed to maintain frequent patterns. Experimental results demonstrate that our algorithm outperforms representative state-of-the-art algorithms.
Regression Cubes With Lossless Compression And Aggregation, Yixin Chen, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, Jianyong Wang
Regression Cubes With Lossless Compression And Aggregation, Yixin Chen, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, Jianyong Wang
Kno.e.sis Publications
As OLAP engines are widely used to support multidimensional data analysis, it is desirable to support in data cubes advanced statistical measures, such as regression and filtering, in addition to the traditional simple measures such as count and average. Such new measures will allow users to model, smooth, and predict the trends and patterns of data. Existing algorithms for simple distributive and algebraic measures are inadequate for efficient computation of statistical measures in a multidimensional space. In this paper, we propose a fundamentally new class of measures, compressible measures, in order to support efficient computation of the statistical models. For …
Implicit Online Learning With Kernels, Li Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli
Implicit Online Learning With Kernels, Li Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli
Kno.e.sis Publications
We present two new algorithms for online learning in reproducing kernel Hilbert spaces. Our first algorithm, ILK (implicit online learning with kernels), employs a new, implicit update technique that can be applied to a wide variety of convex loss functions. We then introduce a bounded memory version, SILK (sparse ILK), that maintains a compact representation of the predictor without compromising solution quality, even in non-stationary environments. We prove loss bounds and analyze the convergence rate of both. Experimental evidence shows that our proposed algorithms outperform current methods on synthetic and real data.
{Ontology: Resource} X {Matching : Mapping} X {Schema : Instance} :: Components Of The Same Challenge, Amit P. Sheth
{Ontology: Resource} X {Matching : Mapping} X {Schema : Instance} :: Components Of The Same Challenge, Amit P. Sheth
Kno.e.sis Publications
Ontologies enable us to elevate syntactic and structural processing in an information system/Web to an information system/Web powered with semantic processing. Experience has shown that monolithic and tightly coupled approaches seldom succeed, and majority of information systems and applications will need to deal with plurality of ontologies in a loosely coupled environment (i.e., independently evolving ontologies and inter-ontology relationships, existence of different contexts for different users/applications etc.) Development of such loosely-coupled multi-ontology environments entails development of techniques for ontology mapping/alignment, multi-ontology query processing, and much more.
Active Semantic Electronic Medical Record, Amit P. Sheth, Sangeeta Agrawal, Jonathan Lathem, Nicole Oldham, H. Wingate, K. Gallagher
Active Semantic Electronic Medical Record, Amit P. Sheth, Sangeeta Agrawal, Jonathan Lathem, Nicole Oldham, H. Wingate, K. Gallagher
Kno.e.sis Publications
The healthcare industry is rapidly advancing towards the widespread use of electronic medical records systems to manage the increasingly large amount of patient data and reduce medical errors. In addition to patient data there is a large amount of data describing procedures, treatments, diagnoses, drugs, insurance plans, coverage, formularies and the relationships between these data sets. While practices have benefited from the use of EMRs, infusing these essential programs with rich domain knowledge and rules can greatly enhance their performance and ability to support clinical decisions. Active Semantic Electronic Medical Record (ASEMR) application discussed here uses Semantic Web technologies to …
A Framework For Schema-Driven Relationship Discovery From Unstructured Text, Cartic Ramakrishnan, Krzysztof Kochut, Amit P. Sheth
A Framework For Schema-Driven Relationship Discovery From Unstructured Text, Cartic Ramakrishnan, Krzysztof Kochut, Amit P. Sheth
Kno.e.sis Publications
We address the issue of extracting implicit and explicit relationships between entities in biomedical text. We argue that entities seldom occur in text in their simple form and that relationships in text relate the modified, complex forms of entities with each other. We present a rule-based method for (1) extraction of such complex entities and (2) relationships between them and (3) the conversion of such relationships into RDF. Furthermore, we present results that clearly demonstrate the utility of the generated RDF in discovering knowledge from text corpora by means of locating paths composed of the extracted relationships.
Semantic Interoperability Of Web Services - Challenges And Experiences, Meenakshi Nagarajan, Kunal Verma, Amit P. Sheth, John A. Miller, Jonathan Lathem
Semantic Interoperability Of Web Services - Challenges And Experiences, Meenakshi Nagarajan, Kunal Verma, Amit P. Sheth, John A. Miller, Jonathan Lathem
Kno.e.sis Publications
With the rising popularity of Web services, both academia and industry have invested considerably in Web service description standards, discovery, and composition techniques. The standards based approach utilized by Web services has supported interoperability at the syntax level. However, issues of structural and semantic heterogeneity between messages exchanged by Web services are far more complex and crucial to interoperability. It is for these reasons that we recognize the value that schema/data mappings bring to Web service descriptions. In this paper, we examine challenges to interoperability; classify the types of heterogeneities that can occur between interacting services and present a possible …
Optimal Adaptation In Web Processes With Coordination Constraints, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth
Optimal Adaptation In Web Processes With Coordination Constraints, 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 constraints that necessitate coordination. For example, in a supply chain process, orders placed by a 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. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to change the suppliers. We focus on formulating the decision making models of the managers, who must adapt to external events while satisfying …
Flexible Querying Of Xml Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni
Flexible Querying Of Xml Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni
Kno.e.sis Publications
Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. We also present a simple yet robust relevance ranking for heterogeneous document-centric XML.
Optimal Adaptation Of Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth
Optimal Adaptation Of 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. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to change the suppliers. We present our methods within the framework of autonomic Web processes. This framework seeks to add properties of self-configuration, adaptation, and self-optimization …
Geospatial Ontology Development And Semantic Analytics, I. Budak Arpinar, Cartic Ramakrishnan, Molly Azami, Amit P. Sheth, E. Lynn Usery, Mei-Po Kwan
Geospatial Ontology Development And Semantic Analytics, I. Budak Arpinar, Cartic Ramakrishnan, Molly Azami, Amit P. Sheth, E. Lynn Usery, Mei-Po Kwan
Kno.e.sis Publications
Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we …
Masquerader Detection Using Oclep: One-Class Classification Using Length Statistics Of Emerging Patterns, Lijun Chen, Guozhu Dong
Masquerader Detection Using Oclep: One-Class Classification Using Length Statistics Of Emerging Patterns, Lijun Chen, Guozhu Dong
Kno.e.sis Publications
We introduce a new method for masquerader detection that only uses a user’s own data for training, called Oneclass Classification using Length statistics of Emerging Patterns (OCLEP). Emerging patterns (EPs) are patterns whose support increases from one dataset/class to another with a big ratio, and have been very useful in earlier studies. OCLEP classifies a case T as self or masquerader by using the average length of EPs obtained by contrasting T against sets of samples of a user’s normal data. It is based on the observation that one needs long EPs to differentiate instances from a common class, but …
Semantic Empowerment Of Health Care And Life Science Applications, Amit P. Sheth
Semantic Empowerment Of Health Care And Life Science Applications, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Semantic Analytics Visualization, Leonidas Deligiannidis, Amit P. Sheth, Boanerges Aleman-Meza
Semantic Analytics Visualization, Leonidas Deligiannidis, Amit P. Sheth, Boanerges Aleman-Meza
Kno.e.sis Publications
In this paper we present a new tool for semantic analytics through 3D visualization called “Semantic Analytics Visualization” (SAV). It has the capability for visualizing ontologies and meta-data including annotated web-documents, images, and digital media such as audio and video clips in a synthetic three-dimensional semi-immersive environment. More importantly, SAV supports visual semantic analytics, whereby an analyst can interactively investigate complex relationships between heterogeneous information. The tool is built using Virtual Reality technology which makes SAV a highly interactive system. The backend of SAV consists of a Semantic Analytics system that supports query processing and semantic association discovery. Using a …
Ivibrate: Interactive Visualization Based Framework For Clustering Large Datasets, Keke Chen, Ling Liu
Ivibrate: Interactive Visualization Based Framework For Clustering Large Datasets, Keke Chen, Ling Liu
Kno.e.sis Publications
With continued advances in communication network technology and sensing technology, there is astounding growth in the amount of data produced and made available through cyberspace. Efficient and high-quality clustering of large datasets continues to be one of the most important problems in large-scale data analysis. A commonly used methodology for cluster analysis on large datasets is the three-phase framework of sampling/summarization, iterative cluster analysis, and disk-labeling. There are three known problems with this framework which demand effective solutions. The first problem is how to effectively define and validate irregularly shaped clusters, especially in large datasets. Automated algorithms and statistical methods …
Detecting The Change Of Clustering Structure In Categorical Data Streams, Keke Chen, Ling Liu
Detecting The Change Of Clustering Structure In Categorical Data Streams, Keke Chen, Ling Liu
Kno.e.sis Publications
Analyzing clustering structures in data streams can provide critical information for making decision in real time. In this paper, we present a framework for detecting the change of critical clustering structure in categorical data streams. The framework consists of the Hierarchical Entropy Tree structure (HE-Tree) and the extended ACE clustering algorithm. HE-Tree can efficiently capture the entropy property of the categorical data streams and allow us to draw precise clustering information from the data stream for high-quality BkPLots with the extended ACE algorithm.