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Full-Text Articles in Science and Technology Studies

Semantic Sensor Web, Amit P. Sheth, Cory Andrew Henson Feb 2008

Semantic Sensor Web, Amit P. Sheth, Cory Andrew Henson

Kno.e.sis Publications

No abstract provided.


Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick L. Tarleton, Mark Musen, Satya S. Sahoo, Prashant Doshi, Natasha Noy Jan 2008

Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick L. Tarleton, Mark Musen, Satya S. Sahoo, Prashant Doshi, Natasha Noy

Kno.e.sis Publications

No abstract provided.


Semantic Sensor Web, Cory Andrew Henson Jan 2008

Semantic Sensor Web, Cory Andrew Henson

Kno.e.sis Publications

No abstract provided.


Semantic Provenance For Escience: Managing The Deluge Of Scientific Data, Satya S. Sahoo, Amit P. Sheth, Cory Andrew Henson Jan 2008

Semantic Provenance For Escience: Managing The Deluge Of Scientific Data, Satya S. Sahoo, Amit P. Sheth, Cory Andrew Henson

Kno.e.sis Publications

Provenance information in eScience is metadata that's critical to effectively manage the exponentially increasing volumes of scientific data from industrial-scale experiment protocols. Semantic provenance, based on domain-specific provenance ontologies, lets software applications unambiguously interpret data in the correct context. The semantic provenance framework for eScience data comprises expressive provenance information and domain-specific provenance ontologies and applies this information to data management. The authors' "two degrees of separation" approach advocates the creation of high-quality provenance information using specialized services. In contrast to workflow engines generating provenance information as a core functionality, the specialized provenance services are integrated into a scientific workflow …


Hrests: An Html Microformat For Describing Restful Web Services, Jacek Kopecky, Karthik Gomadam, Tomas Vitvar Jan 2008

Hrests: An Html Microformat For Describing Restful Web Services, Jacek Kopecky, Karthik Gomadam, Tomas Vitvar

Kno.e.sis Publications

The Web 2.0 wave brings, among other aspects, the Programmable Web: increasing numbers of Web sites provide machine-oriented APIs and Web services. However, most APIs are only described with text in HTML documents. The lack of machine-readable API descriptions affects the feasibility of tool support for developers who use these services. We propose a microformat called hRESTS (HTML for RESTful Services) for machine-readable descriptions of Web APIs, backed by a simple service model. The hRESTS microformat describes main aspects of services, such as operations, inputs and outputs. We also present two extensions of hRESTS: SA-REST, which captures the facets of …


Mobile Semantic Computing, Karthik Gomadam, Anupam Joshi, Amit P. Sheth Jan 2008

Mobile Semantic Computing, Karthik Gomadam, Anupam Joshi, Amit P. Sheth

Kno.e.sis Publications

We propose to organize a special session on research in the intersection of mobile computing, the Semantic Web and Web services.

This session will examine how the research in these areas can serve as a foundation for new architectural and communication paradigms that can enhance service creation, distribution, discovery, integration and utilization in distributed and ubiquitous environments. Some of the initial areas that our early research have highlighted are :

  1. Semantic annotation of data in bandwidth constrained environments such as mobile networks to promote efficient bandwidth utilization
  2. Possibilities of using microformats such as RDFa and opportunities that can be explored …


Targeted Content Delivery For Social Media Content, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang Jan 2008

Targeted Content Delivery For Social Media Content, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang

Kno.e.sis Publications

Spotting contextually relevant keywords is fundamental to effective content suggestions on the Web. In this regard, misspellings, entity variations and off-topic discussions in content from Social Media pose unique challenges. Here, we present an algorithm that assists content delivery systems by identifying contextually relevant keywords and eliminating off-topic keywords. A preliminary user study over data from MySpace and Facebook clearly suggests the usefulness of our work in delivering more targeted content suggestions.


Semantic Sensor Web, Amit P. Sheth, Satya S. Sahoo Jan 2008

Semantic Sensor Web, Amit P. Sheth, Satya S. Sahoo

Kno.e.sis Publications

Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for …


Services Mashups: The New Generation Of Web Applications, Djamal Benslimane, Schahram Dustdar, Amit P. Sheth Jan 2008

Services Mashups: The New Generation Of Web Applications, Djamal Benslimane, Schahram Dustdar, Amit P. Sheth

Kno.e.sis Publications

Web services are becoming a major technology for deploying automated interactions between distributed and heterogeneous applications, and for connecting business processes. Service mashups indicate a way to create new Web applications by combining existing Web resources utilizing data and Web APIs. They facilitate the design and development of novel and modern Web applications based on easy-to-accomplish end-user service compositions.


Semantic Sensor Web, Amit P. Sheth Jan 2008

Semantic Sensor Web, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Unsupervised Discovery Of Compound Entities For Relationship Extraction, Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang, Amit P. Sheth Jan 2008

Unsupervised Discovery Of Compound Entities For Relationship Extraction, Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang, Amit P. Sheth

Kno.e.sis Publications

In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple entities. We therefore focus on identifying compound entities rather than mentions of simple entities. We present a method based on rules over grammatical dependency structures for unsupervised segmentation of sentences into compound entities and relationships. We complement the rule-based approach with a statistical component that prunes structures with low information content, thereby reducing false positives in the prediction of compound entities, their constituents and relationships. The extraction is manually evaluated with respect to the UMLS Semantic Network …


Ontology Driven Semantic Provenance For Heterogeneous Bionomics Experimental Data, Satya S. Sahoo, Michael L. Raymer, Cory Andrew Henson, Amit P. Sheth, William S. York Jan 2008

Ontology Driven Semantic Provenance For Heterogeneous Bionomics Experimental Data, Satya S. Sahoo, Michael L. Raymer, Cory Andrew Henson, Amit P. Sheth, William S. York

Kno.e.sis Publications

Scientific experimental data generated by all the bionomic technologies is characterized by heterogeneity in its representation formats, constituents, and generation processes and, therefore, also in its usage. Using the proteomics domain we demonstrate the important role of provenance information o manage, interpret and analyze experimental data. We present a novel approach that employs an ontology as a knowledge model to automatically create semantic provenance information for high-throughput mass spectrometry (MS) data in the glycoproteomics domain. The Semantic Provenance Annotation of Data in protEomics (SPADE) implementation is based on the ProPreO ontology, a large-process ontology ( ~500 classes, 40 named relationships …


Strategic Importance Of Higher Education And Research In Positioning Gujarat For Global Competitiveness, Amit P. Sheth Jan 2008

Strategic Importance Of Higher Education And Research In Positioning Gujarat For Global Competitiveness, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.


Traveling The Semantic Web Through Space, Theme And Time, Amit P. Sheth, Matthew Perry Jan 2008

Traveling The Semantic Web Through Space, Theme And Time, Amit P. Sheth, Matthew Perry

Kno.e.sis Publications

In this installment of Semantics and Services, we further develop the idea of spatial, temporal, and thematic (STT) processing of semantic Web data and describe the Web infrastructure needed to support it. Starting from Ramesh Jain's vision of the EventWeb as a view of what's possible with a Web that better accommodates all three dimensions of event-related information (thematic, spatial, and temporal), we outline the architecture needed to support it and current research that aims to realize it.


Collaborative Ro1 With Ncbo Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick Tarleton, Prashant Doshi, Mark Musen, Natasha Noy, Satya S. Sahoo, Daniel B. Weatherly Jan 2008

Collaborative Ro1 With Ncbo Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick Tarleton, Prashant Doshi, Mark Musen, Natasha Noy, Satya S. Sahoo, Daniel B. Weatherly

Kno.e.sis Publications

No abstract provided.


Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang Jan 2008

Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang

Kno.e.sis Publications

In this work, we investigate techniques to monitize user activity on public forums, marketplaces and groups on social network sites. Our approach involves (a) identifying the monetization potential of user posts and (b) eliminating o- topic content in monetizable posts to use the most relevant keywords for advertising. Our first user study involving 30 users and data from MySpace and Facebook, shows that 52% of ad impressions shown after using our system were more targeted compared to the 30% relevant impressions generated without using our system. A second smaller study suggests that profile ads that are based on user activity …


Joint Extraction Of Compound Entities And Relationships From Biomedical Literature, Cartic Ramakrishnan, Pablo N. Mendes, Rodrigo A.T.S. De Gama, Guilherme C.N. Ferreira, Amit P. Sheth Jan 2008

Joint Extraction Of Compound Entities And Relationships From Biomedical Literature, Cartic Ramakrishnan, Pablo N. Mendes, Rodrigo A.T.S. De Gama, Guilherme C.N. Ferreira, Amit P. Sheth

Kno.e.sis Publications

In this paper we identify some limitations of contemporary information extraction mechanisms in the context of biomedical literature. We present an extraction mechanism that generates structured representations of textual content. Our extraction mechanism achieves this by extracting compound entities, and relationships between them, occuring in text. A detailed evaluation of the relationship and compound entities extracted is presented. Our results show over 62% average precision across 8 relationship types tested with over 82% average precision for compound entity identification1.