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Articles 511 - 540 of 855
Full-Text Articles in Science and Technology Studies
Unsupervised Discovery Of Compound Entities For Relationship Extraction, Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang, Amit P. Sheth
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 …
Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang
Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang
Kno.e.sis Publications
No abstract provided.
Reasoning In Circumscriptive Alco, Stephan Grimm, Pascal Hitzler
Reasoning In Circumscriptive Alco, Stephan Grimm, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Non-monotonic 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 locally 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 sound and complete decision …
Expressive Tractable Description Logics Based On Sroiq Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Expressive Tractable Description Logics Based On Sroiq Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Computer Science and Engineering Faculty Publications
We introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ - the basis for the ongoing standardisation of OWL 2 - can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ …
Strategic Importance Of Higher Education And Research In Positioning Gujarat For Global Competitiveness, Amit P. Sheth
Strategic Importance Of Higher Education And Research In Positioning Gujarat For Global Competitiveness, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
A Coherent Well-Founded Model For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
A Coherent Well-Founded Model For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
Computer Science and Engineering Faculty Publications
With the advent of the Semantic Web, the question becomes important how to best combine open-world based ontology languages, like OWL, with closed-world rules paradigms. One of the most mature proposals for this combination is known as Hybrid MKNF knowledge bases [11], which is based on an adaptation of the stable model semantics to knowledge bases consisting of ontology axioms and rules. In this paper, we propose a well-founded semantics for such knowledge bases which promises to provide better efficiency of reasoning, which is compatible both with the OWL-based semantics and the traditional well-founded semantics for logic programs, and which …
Approximate Owl-Reasoning With Screech, Tuvshintur Tserendorj, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler
Approximate Owl-Reasoning With Screech, Tuvshintur Tserendorj, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Applications of expressive ontology reasoning for the Semantic Web require scalable algorithms for deducing implicit knowledge from explicitly given knowledge bases. Besides the development of more effi- cient such algorithms, awareness is rising that approximate reasoning solutions will be helpful and needed for certain application domains. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on …
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
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.
Semantic Sensor Web, Amit P. Sheth, Satya S. Sahoo
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 …
Semantic Provenance For Escience: Managing The Deluge Of Scientific Data, Satya S. Sahoo, Amit P. Sheth, Cory Andrew Henson
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 …
Learning Expressive Ontologies, Johanna Volker, Peter Haase, Pascal Hitzler
Learning Expressive Ontologies, Johanna Volker, Peter Haase, Pascal Hitzler
Computer Science and Engineering Faculty Publications
No abstract provided.
Hrests: An Html Microformat For Describing Restful Web Services, Jacek Kopecky, Karthik Gomadam, Tomas Vitvar
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 …
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
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.
Targeted Content Delivery For Social Media Content, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang
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.
Traveling The Semantic Web Through Space, Theme And Time, Amit P. Sheth, Matthew Perry
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.
A General Boosting Method And Its Application To Learning Ranking Functions For Web Search, Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun
A General Boosting Method And Its Application To Learning Ranking Functions For Web Search, Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun
Kno.e.sis Publications
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach is based on optimization of quadratic upper bounds of the loss functions which allows us to present a rigorous convergence analysis of the algorithm. More importantly, this general framework enables us to use a standard regression base learner such as decision trees for fitting any loss function. We illustrate an application of the proposed method in learning ranking functions for Web search by combining both preference data and labeled data for training. We present experimental …
Video On The Semantic Sensor Web, Cory Andrew Henson, Amit P. Sheth, Prateek Jain, Josh Pschorr, Terry Rapoch
Video On The Semantic Sensor Web, Cory Andrew Henson, Amit P. Sheth, Prateek Jain, Josh Pschorr, Terry Rapoch
Kno.e.sis Publications
Millions of sensors around the globe currently collect avalanches of data about our world. The rapid development and deployment of sensor technology is intensifying the existing problem of too much data and not enough knowledge. With a view to alleviating this glut, we propose that sensor data, especially video sensor data, can be annotated with semantic metadata to provide contextual information about videos on the Web. In particular, we present an approach to annotating video sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the W3C and Open Geospatial Consortium (OGC) and …
Towards Tractable Local Closed World Reasoning For The Semantic Web, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
Towards Tractable Local Closed World Reasoning For The Semantic Web, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Recently, the logics of minimal knowledge and negation as failure MKNF [12] was used to introduce hybrid MKNF knowledge bases [14], a powerful formalism for combining open and closed world reasoning for the Semantic Web. We present an extension based on a new three-valued framework including an alternating fixpoint, the well-founded MKNF model. This approach, the well-founded MKNF semantics, derives its name from the very close relation to the corresponding semantics known from logic programming. We show that the well-founded MKNF model is the least model among all (three-valued) MKNF models, thus soundly approximating also the two-valued MKNF models from …
Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth
Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth
Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Conjunctive Queries For A Tractable Fragment Of Owl 1.1, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Conjunctive Queries For A Tractable Fragment Of Owl 1.1, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Despite the success of the Web Ontology Language OWL, the development of expressive means for querying OWL knowledge bases is still an open issue. In this paper, we investigate how a very natural and desirable form of queries-namely conjunctive ones-can be used in conjunction with OWL such that one of the major design criteria of the latter-namely decidability-can be retained. More precisely, we show that querying the tractable fragment EL++ of OWL 1.1 is decidable. We also provide a complexity analysis and show that querying unrestricted EL++ is undecidable.
Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth
Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Kno.e.sis Publications
Social networking, distributed problem solving and human computation have gained high visibility. Wikipedia is a well established service that incorporates aspects of these three fields of research. For this reason it is a good object of study for determining quality of solutions in a social setting that is open, completely distributed, bottom up and not peer reviewed by certified experts. In particular, this paper aims at identifying semantic convergence of Wikipedia articles; the notion that the content of an article stays stable regardless of continuing edits. This could lead to an automatic recommendation of good article tags but also add …
Supporting Complex Thematic, Spatial And Temporal Queries Over Semantic Web Data, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
Supporting Complex Thematic, Spatial And Temporal Queries Over Semantic Web Data, 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. Often, the analytical process requires uncovering and analyzing complex thematic 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 for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities. We …
The Economic Contribution Of Marine Science And Education Institutions In The Monterey Bay Crescent, Judith T. Kildow Dr, Nathaniel Miller
The Economic Contribution Of Marine Science And Education Institutions In The Monterey Bay Crescent, Judith T. Kildow Dr, Nathaniel Miller
Publications
Ocean and coastal areas of the United States contribute significantly to our nation’s overall economy. The extent to which our economy benefits from the wide range of marine and coastal activities is not completely understood. The National Ocean Economics Program (NOEP) has attempted to track and value the ocean and coastal- related economic activities in the United States. To date six sectors are included in its information system (www.oceaneconomics.org). The economic contribution of marine research and education institutions is a sector of activity that lies outside of the normal federal government datasets, but one which seemed to have growing importance …
A Multi-Objective Genetic Algorithm That Employs A Hybrid Approach For Isolating Codon Usage Bias Indicative Of Translational Efficiency, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
A Multi-Objective Genetic Algorithm That Employs A Hybrid Approach For Isolating Codon Usage Bias Indicative Of Translational Efficiency, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
Kno.e.sis Publications
Isolation of translational efficiency bias can have important applications in gene expression prediction and heterologous protein production. In some genomes the presence of a high GC(AT)-content bias can confound the isolation of translational efficiency bias. In other organisms translational efficiency bias is weak making it difficult to isolate. Described here is a multi-objective genetic algorithm that improves the isolation of translational efficiency bias in Streptomyces coelicolor A3(2) and Pseudomonas aeruginosa PAO1, two organisms shown to have high GC-content and weak translational efficiency bias.
Swashup: Situational Web Applications Mashups, E. Michael Maximilien, Ajith Harshana Ranabahu, Stefan Tai
Swashup: Situational Web Applications Mashups, E. Michael Maximilien, Ajith Harshana Ranabahu, Stefan Tai
Kno.e.sis Publications
Distributed programming has shifted from private networks to the Internet using heterogeneous Web APIs. This enables the creation of situational applications of composed services exposing user interfaces, i.e., mashups. However, this programmable Web lacks unified models that can facilitate mashup creation, reuse, and deployments. This poster demonstrates a platform to facilitate Web 2.0 mashups.
A Proposed Statistical Protocol For The Analysis Of Metabolic Toxicological Data Derived From Nmr Spectroscopy, Benjamin J. Kelly, Paul E. Anderson, Nicholas V. Reo, Nicholas J. Delraso, Travis E. Doom, Michael L. Raymer
A Proposed Statistical Protocol For The Analysis Of Metabolic Toxicological Data Derived From Nmr Spectroscopy, Benjamin J. Kelly, Paul E. Anderson, Nicholas V. Reo, Nicholas J. Delraso, Travis E. Doom, Michael L. Raymer
Kno.e.sis Publications
Nuclear magnetic resonance (NMR) spectroscopy is a non-invasive method of acquiring a metabolic profile from biofluids. This metabolic information may provide keys to the early detection of exposure to a toxin. A typical NMR toxicology data set has low sample size and high dimensionality. Thus, traditional pattern recognition techniques are not always feasible. In this paper, we evaluate several common alternatives for isolating these biomarkers. The fold test, unpaired t-test, and paired t-test were performed on an NMR-derived toxicological data set and results were compared. The paired t-test method was preferred, due to its ability to attribute statistical significance, to …
Realizing The Relationship Web: Morphing Information Access On The Web From Today's Document- And Entity-Centric Paradigm To A Relationship-Centric Paradigm, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Description Logic Programs: Normal Forms, Pascal Hitzler, Andreas Eberhart
Description Logic Programs: Normal Forms, Pascal Hitzler, Andreas Eberhart
Computer Science and Engineering Faculty Publications
The relationship and possible interplay between different knowledge representation and reasoning paradigms is a fundamental topic in artificial intelligence. For expressive knowledge representation for the Semantic Web, two different paradigms - namely Description Logics (DLs) and Logic Programming - are the two most successful approaches. A study of their exact relationships is thus paramount. An intersection of OWL with (function-free non-disjunctive) Datalog, called DLP (for Description Logic Programs), has been described in [1,2]. We provide normal forms for DLP in Description Logic syntax and in Datalog syntax, thus providing a bridge for the researcher and user who is familiar with …