Databases and Information Systems | Open Access Articles

Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Review: Steve: The Art Museum Social Tagging Project., Mark Mcbride

Mark F McBride

The Steve Museum is a social tagging project created by volunteers from art museums and galleries. The main goal is to create user generated descriptions for works of art, because we all view, experience, and describe art differently.

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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 …

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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 …

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Combining Geospatial And Temporal Ontologies, Kripa Joshi

Electronic Theses and Dissertations

Publicly available ontologies are growing in number at present. These ontologies describe entities in a domain and the relations among these entities. This thesis describes a method to automatically combine a pair of orthogonal ontologies using cross products. A geospatial ontology and a temporal ontology are combined in this work. Computing the cross product of the geospatial and the temporal ontologies gives a complete set of pairwise combination of terms from the two ontologies. This method offers researchers the benefit of using ontologies that are already existing and available rather than building new ontologies for areas outside their scope of …

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Linking Moving Object Databases With Ontologies, Kraig King

Electronic Theses and Dissertations

This work investigates the supporting role of ontologies for supplementing the information contained in moving object databases. Details of the spatial representation as well as the sensed location of moving objects are frequently stored within a database schema. However, this knowledge lacks the semantic detail necessary for reasoning about characteristics that are specific to each object. Ontologies contribute semantic descriptions for moving objects and provide the foundation for discovering similarities between object types. These similarities can be drawn upon to extract additional details about the objects around us. The primary focus of the research is a framework for linking ontologies …

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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 …

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An Integrated Social Actor And Service Oriented Architecture (Soa) Approach For Improved Electronic Health Record (Ehr) Privacy And Confidentiality In The Us National Healthcare Information Network (Nhin), Gondy Leroy, Elliot Sloane, Steven Sheetz

CGU Faculty Publications and Research

The emerging US National Healthcare Information Network (NHIN) will improve healthcare’s efficacy, efficiency, and safety. The first-generation NHIN being developed has numerous advantages and limitations. One of the most difficult aspects of today’s NHIN is ensuring privacy and confidentiality for personal health data, because family and caregivers have multiple complex legal relationships to a patient. A Social Actor framework is suggested to organize and manage these legal roles, but the Social Actor framework would be very difficult to implement in today’s NHIN. Social Actor Security Management could, however, be effectively implemented using Service Oriented Architectures (SOAs), which are rapidly becoming …

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I’M A Virus Harming The Earth, M. Thulasidas

Research Collection School Of Computing and Information Systems

We humans plunder the raw material from our host planet with such an abandon that is only seen in viruses.

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Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …

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Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

This letter proposes to use multiorder neurons for clustering irregularly shaped data arrangements. Multiorder neurons are an evolutionary extension of the use of higher-order neurons in clustering. Higher-order neurons parametrically model complex neuron shapes by replacing the classic synaptic weight by higher-order tensors. The multiorder neuron goes one step further and eliminates two problems associated with higher-order neurons. First, it uses evolutionary algorithms to select the best neuron order for a given problem. Second, it obtains more information about the underlying data distribution by identifying the correct order for a given cluster of patterns. Empirically we observed that when the …

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Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user identities. Nevertheless, the query contents may disclose the physical location of the user. In this paper, we present a framework for preventing location-based identity inference of users who issue spatial queries to location-based services. We propose transformations based on the well-established K-anonymity concept to compute exact answers for range and nearest neighbor search, without …

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Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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The Librarian As Hacker, Getting More From Google, R Philip Reynolds

Librarian and Staff Publications

This paper will cover four areas. First it will discuss the research habits of search engine users and some of the problems with these habits. Then it will discuss librarians' use of search engines. Here we encounter the real question: Do we do much better? Can we use a search engines to their full potential? When needed, can we hack an engine to make it perform beyond its intended function? Can we use a clever workaround to solve a problem? Or are we on a level playing field with our patrons once we get outside traditional database searching? Google currently …

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Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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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 …

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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 …

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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.

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Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu

Research Collection School Of Computing and Information Systems

In this paper, we present our approaches and results of high-level feature extraction and automatic video search in TRECVID-2007.

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Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. In this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. The proposed solution first derives representative words from comments and then selects sentences containing representative words. The representativeness of words is measured using ReQuT (i.e., Reader, Quotation, and Topic). Evaluated on human labeled sentences, ReQuT together with summation-based sentence selection showed promising results.

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On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Wikipedia is presently the largest free-and-open online encyclopedia collaboratively edited and maintained by volunteers. While Wikipedia offers full-text search to its users, the accuracy of its relevance-based search can be compromised by poor quality articles edited by non-experts and inexperienced contributors. In this paper, we propose a framework that re-ranks Wikipedia search results considering article quality. We develop two quality measurement models, namely Basic and PeerReview, to derive article quality based on co-authoring data gathered from articles' edit history. Compared with Wikipedia's full-text search engine, Google and Wikiseek, our experimental results showed that (i) quality-only ranking produced by PeerReview gives …

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Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Wikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. Despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of Wikipedia articles edited by non-experts and inexperienced contributors. In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. Our Basic model is designed based …

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Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

Searching answers to complex questions is a challenging IR task. In this paper, we examine the use of query templates with semantic slots to formulate slot-based queries. These queries have query terms assigned to entity and relationship slots. We develop several query expansion methods for slot-based queries so as to improve their retrieval effectiveness on a document collection. Each method consists of a combination of term scoring scheme, term scoring formula, and term assignment scheme. Our preliminary experiments evaluate these different slot-based query expansion methods on a collection of news documents,and conclude that:(1) slot-based queries yield better retrieval accuracy compared …

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Reduce Response Time: Get "Hooked" On A Wiki, Rebecca Klein, Matthew Smith, David Sierkowski

Information Technology Faculty and Staff Publications

Managing the flow of information both within the IT department and to our customers is one of our greatest challenges in the Office of Technology Information at Valparaiso University. To be successful, IT staff first need to acquire the right information from colleagues to provide excellent service. Then, the staff must determine the most effective way to communicate that information to internal and external customers to encourage the flow of information. To advance the IT department’s goals, how best can we utilize “information” and “communication” vehicles to exchange information, improve workflow, and ultimately communicate essential information to our internal and …

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Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs

MIS/OM/DS Faculty Publications

The difficulty for organizations arises because neither complexity nor its impacts on performance are well understood (Fisher & Ittner, 1999b). The mechanisms through which it affects cost, quality, delivery, and flexibility need to be explained (Ramdas, 2003). However, this cannot happen until complexity can be explained theoretically. But, to build theory there must first be a common understanding about the construct of interest (Wacker, 2004). Only then can researchers operationalize it and search for meaningful relationships. In light of this, I develop a definition of complexity below. A sampling of the operations management literature is then presented within the context …

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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 …

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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.

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Does Mutual Knowledge Affect Virtual Team Performance? Theoretical Analysis And Anecdotal Evidence, Alanah Davis, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

This paper describes the concept of mutual knowledge and its potential impact on virtual team performance. Based on an analysis of extant literature, we argue that there is a gap in our understanding of what is known about mutual knowledge as it impacts team dynamics and virtual team performance. Supporting literature, anecdotes, and case studies are used to discuss the importance of mutual knowledge for virtual team performance and the research issues that need to be addressed in the future.

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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.

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Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han

Research Collection School Of Computing and Information Systems

Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, demanding powerful data mining methods. Due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. In this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gApprox. gApprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on …

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Full-Text Articles in Databases and Information Systems

Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth

Kno.e.sis Publications

Review: Steve: The Art Museum Social Tagging Project., Mark Mcbride

Mark F McBride

Towards Tractable Local Closed World Reasoning For The Semantic Web, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Video On The Semantic Sensor Web, Cory Andrew Henson, Amit P. Sheth, Prateek Jain, Josh Pschorr, Terry Rapoch

Kno.e.sis Publications

Combining Geospatial And Temporal Ontologies, Kripa Joshi

Electronic Theses and Dissertations

Linking Moving Object Databases With Ontologies, Kraig King

Electronic Theses and Dissertations

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

An Integrated Social Actor And Service Oriented Architecture (Soa) Approach For Improved Electronic Health Record (Ehr) Privacy And Confidentiality In The Us National Healthcare Information Network (Nhin), Gondy Leroy, Elliot Sloane, Steven Sheetz

CGU Faculty Publications and Research

I’M A Virus Harming The Earth, M. Thulasidas

Research Collection School Of Computing and Information Systems

Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth

Kno.e.sis Publications

The Librarian As Hacker, Getting More From Google, R Philip Reynolds

Librarian and Staff Publications

Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth

Kno.e.sis Publications

Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth

Kno.e.sis Publications

Supporting Complex Thematic, Spatial And Temporal Queries Over Semantic Web Data, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain

Kno.e.sis Publications

Conjunctive Queries For A Tractable Fragment Of Owl 1.1, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu

Research Collection School Of Computing and Information Systems

Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong

Research Collection School Of Computing and Information Systems

Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

Reduce Response Time: Get "Hooked" On A Wiki, Rebecca Klein, Matthew Smith, David Sierkowski

Information Technology Faculty and Staff Publications

Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs

MIS/OM/DS Faculty Publications

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

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

Does Mutual Knowledge Affect Virtual Team Performance? Theoretical Analysis And Anecdotal Evidence, Alanah Davis, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

Swashup: Situational Web Applications Mashups, E. Michael Maximilien, Ajith Harshana Ranabahu, Stefan Tai

Kno.e.sis Publications

Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han

Research Collection School Of Computing and Information Systems