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Spatial Semantics For Better Interoperability And Analysis: Challenges And Experiences In Building Semantically Rich Applications In Web 3.0, Amit P. Sheth Dec 2010

Spatial Semantics For Better Interoperability And Analysis: Challenges And Experiences In Building Semantically Rich Applications In Web 3.0, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Flexible Bootstrapping-Based Ontology Alignment, Prateek Jain, Pascal Hitzler, Amit P. Sheth Nov 2010

Flexible Bootstrapping-Based Ontology Alignment, Prateek Jain, Pascal Hitzler, Amit P. Sheth

Kno.e.sis Publications

BLOOMS (Jain et al, ISWC2010) is an ontology alignment system which, in its core, utilizes the Wikipedia category hierarchy for establishing alignments. In this paper, we present a Plug-and-Play extension to BLOOMS, which allows to flexibly replace or complement the use of Wikipedia by other online or offline resources, including domain-specific ontologies or taxonomies. By making use of automated translation services and of Wikipedia in languages other than English, it makes it possible to apply BLOOMS to alignment tasks where the input ontologies are written in different languages.


Ontology Alignment For Linked Open Data, Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh Nov 2010

Ontology Alignment For Linked Open Data, Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, Peter Z. Yeh

Kno.e.sis Publications

The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the ...


Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth Sep 2010

Ranking Documents Semantically Using Ontological Relationships, Boanerges Aleman-Meza, I. Budak Arpinar, Mustafa V. Nural, Amit P. Sheth

Kno.e.sis Publications

Although arguable success of today’s keyword based search engines in certain information retrieval tasks, ranking search results in a meaningful way remains an open problem. In this work, the goal is to use of semantic relationships for ranking documents without relying on the existence of any specific structure in a document or links between documents. Instead, real-world entities are identified and the relevance of documents is determined using relationships that are known to exist between the entities in a populated ontology. We introduce a measure of relevance that is based on traversal and the semantics of relationships that link ...


A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth Sep 2010

A Taxonomy-Based Model For Expertise Extrapolation, Delroy H. Cameron, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Sheron L. Decker, Amit P. Sheth

Kno.e.sis Publications

While many ExpertFinder applications succeed in finding experts, their techniques are not always designed to capture the various levels at which expertise can be expressed. Indeed, expertise can be inferred from relationships between topics and subtopics in a taxonomy. The conventional wisdom is that expertise in subtopics is also indicative of expertise in higher level topics as well. The enrichment of Expertise Profiles for finding experts can therefore be facilitated by taking domain hierarchies into account. We present a novel semantics-based model for finding experts, expertise levels and collaboration levels in a peer review context, such as composing a Program ...


Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen Aug 2010

Cross-Market Model Adaptation With Pairwise Preference Data For Web Search Ranking, Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen

Kno.e.sis Publications

Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibility required of a commercial web search. However, manually labeled training data (with multiple absolute grades) has become the bottleneck for training a quality ranking function, particularly for a new domain. In this paper, we explore the adaptation of machine-learned ranking models across a set of geographically diverse markets with the market-specific pairwise preference data, which can be easily obtained from clickthrough logs. We propose a novel adaptation algorithm, Pairwise-Trada, which is able to adapt ranking models that are trained ...


Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong Aug 2010

Pattern Space Maintenance For Data Updates And Interactive Mining, Mengling Feng, Guozhu Dong, Jinyan Li, Yap-Peng Tan, Limsoon Wong

Kno.e.sis Publications

This article addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer− (PSM−), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art methods by an order of ...


Sit-To-Stand Detection Using Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic, Carmen Abbott Jul 2010

Sit-To-Stand Detection Using Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic, Carmen Abbott

Kno.e.sis Publications

The ability to rise from a chair is an important parameter to assess the balance deficits of a person. In particular, this can be an indication of risk for falling in elderly persons. Our goal is automated assessment of fall risk using video data. Towards this goal, we present a simple yet effective method of detecting transition, i.e. sit-to-stand and stand-to-sit, from image frames using fuzzy clustering methods on image moments. The technique described in this paper is shown to be robust even in the presence of noise and has been tested on several data sequences using different subjects ...


Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth Jul 2010

Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Trust is an amorphous concept that is becoming Increasingly important in many domains, such as P2P networks, E-commerce, social networks, and sensor networks. While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a ...


Cloud Based Scientific Workflow For Nmr Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith Harshana Ranabahu, Michael L. Raymer, Amit P. Sheth Jul 2010

Cloud Based Scientific Workflow For Nmr Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith Harshana Ranabahu, Michael L. Raymer, Amit P. Sheth

Kno.e.sis Publications

This work presents a service oriented scientific workflow approach to NMR-based metabolomics data analysis. We demonstrate the effectiveness of this approach by implementing several common spectral processing techniques in the cloud using a parallel map-reduce framework, Hadoop.


Biomedical Ontologies For Parasite Research, Vinh Nguyen, Satya S. Sahoo, Priti Parikh, Todd Minning, Brent Weatherly, Flora Logan, Amit P. Sheth, Rick Tarleton Jul 2010

Biomedical Ontologies For Parasite Research, Vinh Nguyen, Satya S. Sahoo, Priti Parikh, Todd Minning, Brent Weatherly, Flora Logan, Amit P. Sheth, Rick Tarleton

Kno.e.sis Publications

Trypanosoma cruzi is a protozoan parasite that causes Chagas disease or American trypanosomiasis, which is the leading cause of death in Latin America. The primary objective of this study is to create an ontology-driven information infrastructure to support parasite researchers in identifying gene knockout, vaccination, or drug targets for T. cruzi. This involves querying across multiple datasets from diverse sources, such as proteome, pathway, internal lab data, etc. that are often represented in heterogeneous formats. To address this, a multi-ontology parasite knowledge repository (PKR) is being created with an intuitive graphical query interface called Cuebee. The PKR is underpinned by ...


How To Make Linked Data More Than Data, Prateek Jain, Amit P. Sheth, Kunal Verma, Pascal Hitzler, Peter Z. Yeh Jun 2010

How To Make Linked Data More Than Data, Prateek Jain, Amit P. Sheth, Kunal Verma, Pascal Hitzler, Peter Z. Yeh

Kno.e.sis Publications

The LOD cloud has a potential for applicability in many AI-related tasks, such as open domain question answering, knowledge discovery, and the Semantic Web. An important prerequisite before the LOD cloud can enable these goals is allowing its users (and applications) to effectively pose queries to and retrieve answers from it. However, this prerequisite is still an open problem for the LOD cloud and has restricted it to 'merely more data.' To transform the LOD cloud from 'merely more data' to 'semantically linked data' there are plenty of open issues which should be addressed. We believe this transformation of the ...


Semantically Annotated Restful Services For Large-Scale Metabolomics Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith H. Ranabahu, Michael L. Raymer, Amit P. Sheth Jun 2010

Semantically Annotated Restful Services For Large-Scale Metabolomics Data Analysis, Ashwin Manjunatha, Paul E. Anderson, Satya S. Sahoo, Ajith H. Ranabahu, Michael L. Raymer, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Janus: From Workflows To Semantic Provenance And Linked Open Data, Paolo Missier, Satya S. Sahoo, Jun Zhao, Carole Goble, Amit P. Sheth Jun 2010

Janus: From Workflows To Semantic Provenance And Linked Open Data, Paolo Missier, Satya S. Sahoo, Jun Zhao, Carole Goble, Amit P. Sheth

Kno.e.sis Publications

Data provenance graphs are form of metadata that can be used to establish a variety of properties of data products that undergo sequences of transformations, typically specified as workflows. Their usefulness for answering user provenance queries is limited, however, unless the graphs are enhanced with domain-specific annotations. In this paper we propose a model and architecture for semantic, domain-aware provenance, and demonstrate its usefulness in answering typical user queries. Furthermore, we discuss the additional benefits and the technical implications of publishing provenance graphs as a form of Linked Data. A prototype implementation of the model is available for data produced ...


Provenance Management In Parasite Research, Vinh Nguyen, Priti Parikh, Satya S. Sahoo, Amit P. Sheth Jun 2010

Provenance Management In Parasite Research, Vinh Nguyen, Priti Parikh, Satya S. Sahoo, Amit P. Sheth

Kno.e.sis Publications

The objective of this research is to create a semantic problem solving environment (PSE) for human parasite Trypanosoma cruzi. As a part of the PSE, we are trying to manage provenance of the experiment data as it is generated. It requires to capture the provenance which is often collected through web forms used by biologists to input the information about experiments they conduct. We have created Parasite Experiment Ontology (PEO) that represents provenance information used in the project. We have modified the back end which processes the data gathered from biologists, generates RDF triples and serializes them into the triple ...


Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth May 2010

Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

A number of government, corporate, and academic organizations are collecting enormous amounts of data provided by environmental sensors. However, this data is too often locked within organizations and underutilized by the greater community. In this paper, we present a framework to make this sensor data openly accessible by publishing it on the Linked Open Data (LOD) Cloud. This is accomplished by converting raw sensor observations to RDF and linking with other datasets on LOD. With such a framework, organizations can make large amounts of sensor data openly accessible, thus allowing greater opportunity for utilization and analysis.


Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth May 2010

Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust and reputation are becoming increasingly important in diverse areas such as search, e-commerce, social media, semantic sensor networks, etc. We review past work and explore future research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and ...


Trust In Social And Sensor Networks, Pramod Anantharam, Krishnaprasad Thirunarayan, Cory Andrew Henson, Amit P. Sheth Apr 2010

Trust In Social And Sensor Networks, Pramod Anantharam, Krishnaprasad Thirunarayan, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust can be defined as the perception of the trustor about the degree to which the trustee would satisfy an expectation about a transaction constituting risk. Trust plays a pivotal role when the risk in believing incorrect information is high. With Web 2.0 where user generated content and real time interactions dominate, the openness of data contribution may hinder the quality of information we can get.


Semantics-Empowered Text Exploration For Knowledge Discovery, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth, Victor Chan Apr 2010

Semantics-Empowered Text Exploration For Knowledge Discovery, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth, Victor Chan

Kno.e.sis Publications

The interaction paradigm offered by most contemporary Web Information Systems is a search-and-sift paradigm in which users manually seek information using hyperlinked documents. This paradigm is derived from a document-centric model that gives users minimal support for scanning through high volumes of text. We present a novel information exploration paradigm based on a data-centric view of corpora, along with a prototype implementation that demonstrates the value in content-driven navigation. We leverage semantic metadata to link data in documents by exploiting named relationships between entities. We also present utilities for gathering user generated navigation trails, critical for knowledge discovery. We discuss ...


What Goes Around Comes Around - Improving Linked Open Data Through On-Demand Model Creation, Christopher Thomas, Wenbo Wang, Pankaj Mehra, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth Apr 2010

What Goes Around Comes Around - Improving Linked Open Data Through On-Demand Model Creation, Christopher Thomas, Wenbo Wang, Pankaj Mehra, Delroy H. Cameron, Pablo N. Mendes, Amit P. Sheth

Kno.e.sis Publications

Web 2.0 has changed the way we share and keep up with information. We communicate through social media platforms and make the information we exchange to a large extent publicly available. Linked Open Data (LOD) follows the same paradigm of sharing information but also makes it machine accessible. LOD provides an abundance of structured information albeit in a less formally rigorous form than would be desirable for Semantic Web applications. Nevertheless, most of the LOD assertions are community reviewed and we can rely on their accuracy to a large extent. In this work we want to follow the Web ...


Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth Apr 2010

Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth

Kno.e.sis Publications

We provide a definition of context based on theme, time and location, and propose a mixed retrieval/extraction model for the dynamic suggestion of trending relationships to LOD resources.


Scale: A Scalable Framework For Efficiently Clustering Transactional Data, Hua Yan, Keke Chen, Ling Liu, Zhang Yi Jan 2010

Scale: A Scalable Framework For Efficiently Clustering Transactional Data, Hua Yan, Keke Chen, Ling Liu, Zhang Yi

Kno.e.sis Publications

This paper presents SCALE, a fully automated transactional clustering framework. The SCALE design highlights three unique features. First, we introduce the concept of Weighted Coverage Density as a categorical similarity measure for efficient clustering of transactional datasets. The concept of weighted coverage density is intuitive and it allows the weight of each item in a cluster to be changed dynamically according to the occurrences of items. Second, we develop the weighted coverage density measure based clustering algorithm, a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Third, we introduce two clustering validation metrics and show that these domain ...


Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth Jan 2010

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.


Semantics Centric Solutions For Application And Data Portability In Cloud Computing, Ajith Harshana Ranabahu, Amit P. Sheth Jan 2010

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 ...


Mobicloud - Making Clouds Reachable: A Toolkit For Easy And Efficient Development Of Customized Cloud Mobile Hybrid Applications, Ashwin Manjunatha, Ajith Harshana Ranabahu, Amit P. Sheth, Krishnaprasad Thirunarayan Jan 2010

Mobicloud - Making Clouds Reachable: A Toolkit For Easy And Efficient Development Of Customized Cloud Mobile Hybrid Applications, 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 attempts to exploit the capabilities of the mobile and cloud landscape by introducing MobiCloud, an online toolkit to efficiently develop Cloud-mobile hybrid (CMH) applications. We define a CMH ...


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 Jan 2010

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 ...


From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton Jan 2010

From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton

Kno.e.sis Publications

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and intuitive form-based interfaces to facilitate easy querying of the data. These interfaces could be seen as implementing a set of 'pre-canned' queries commonly used by the life science researchers that we study. The second approach is based on semantic Web technologies and is knowledge (model) driven. It utilizes a large OWL ontology and same datasets as before but associated as RDF instances of the ontology concepts. An intuitive interface is provided that allows the ...


A Study In Hadoop Streaming With Matlab For Nmr Data Processing, Kalpa Gunaratna, Paul E. Anderson, Ajith Harshana Ranabahu, Amit P. Sheth Jan 2010

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 ...


Sensor Data And Perception: Can Sensors Play 20 Questions, Cory Andrew Henson Jan 2010

Sensor Data And Perception: Can Sensors Play 20 Questions, Cory Andrew Henson

Kno.e.sis Publications

Currently, there are many sensors collecting information about our environment, leading to an overwhelming number of observations that must be analyzed and explained in order to achieve situation awareness. As perceptual beings, we are also constantly inundated with sensory data, yet we are able to make sense of our environment with relative ease. Why is the task of perception so easy for us, and so hard for machines; and could this have anything to do with how we play the game 20 Questions?


Getting Code Near The Data: A Study Of Generating Customized Data Intensive Scientific Workflows With Domain Specific Language, Ashwin Manjunatha, Ajith Harshana Ranabahu, Paul E. Anderson, Amit P. Sheth Jan 2010

Getting Code Near The Data: A Study Of Generating Customized Data Intensive Scientific Workflows With Domain Specific Language, Ashwin Manjunatha, Ajith Harshana Ranabahu, Paul E. Anderson, Amit P. Sheth

Kno.e.sis Publications

The amount of data produced in modern biological experiments such as Nuclear Magnetic Resonance (NMR) analysis far exceeds the processing capability of a single machine. The present state-of-the-art is taking the ”data to code”, the philosophy followed by many of the current service oriented workflow systems. However this is not feasible in some cases such as NMR data analysis, primarily due to the large scale of data.

The objective of this research is to bring ”code to data”, preferred in the cases when the data is extremely large. We present a DSL based approach to develop customized data intensive scientific ...