Computer Sciences Commons^™

Cs 1000-01: Technology And Society, Meg Wiltshire

Computer Science & Engineering Syllabi

What impact does technology have on society? As technology plays a greater role in our everyday lives, this becomes and increasingly important issue. The past 30 years have seen unprecedented technological advances, but the benefits obtained are often offset by unforeseen consequences and repercussions, such as privacy concerns, identity theft, and safety. This course will evaluate the consequences of technology on individuals, organizations, and society, identifying the potential benefits and limitations. We will discuss how social, ethical, legal, and philosophical issues have impacted, and will continue to impact, society.

Predicting Parkinson's Disease Progression With Smartphone Data, Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit P. Sheth

Kno.e.sis Publications

Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group.

Research Challenges And Opportunities In Knowledge Representation, Natasha Noy, Deborah Mcguinness, Eyal Amir, Chitta Baral, Michael Beetz, Sean Bechhofer, Craig Boutilier, Anthony Cohn, Johan De Kleer, Michel Dumontier, Tim Finin, Kenneth Forbus, Lise Getoor, Yolanda Gil, Jeff Heflin, Pascal Hitzler, Craig Knoblock, Henry Kautz, Yuliya Lierler, Vladimir Lifschitz, Peter F. Patel-Schneider, Christine Piatko, Doug Riecken, Mark Schildhauer

Computer Science and Engineering Faculty Publications

Modern intelligent systems in every area of science rely critically on knowledge representation and reasoning (KR). The techniques and methods developed by the researchers in knowledge representation and reasoning are key drivers of innovation in computer science; they have led to significant advances in practical applications in a wide range of areas from natural-­‐language processing to robotics to software engineering. Emerging fields such as the semantic web, computational biology, social computing, and many others rely on and contribute to advances in knowledge representation. As the era of “Big Data” evolves, scientists in a broad range of disciplines are increasingly relying …

Knowledge Representation In The Big Data Age, Pascal Hitzler

Computer Science and Engineering Faculty Publications

No abstract provided.

What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt

Kno.e.sis Publications

The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators associated with conversation analysis in social science, we model the presence of conversation in the communication landscape of Twitter in a large corpus of 1.5M tweets for various disaster and non-disaster events spanning different periods, lengths of time and varied social significance. Within Replies, Retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic …

A Resolution Procedure For Description Logics With Nominal Schemas, Cong Wang, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a polynomial resolution-based decision procedure for the recently introduced description logic ELHOV_n(⊓), which features nominal schemas as new language construct. Our algorithm is based on ordered resolution and positive superposition, together with a lifting lemma. In contrast to previous work on resolution for description logics, we have to overcome the fact that ELHOV_n(⊓) does not allow for a normalization resulting in clauses of globally limited size.

A Hybrid Approach To Finding Relevant Social Media Content For Complex Domain Specific Information Needs, Delroy H. Cameron, Amit P. Sheth, Nishita Jaykumar, Gaurish Anand, Krishnaprasad Thirunarayan, Gary Alan Smith

Kno.e.sis Publications

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex, domain specific information needs. Some complex search situations require knowledge of both ontological concepts as well as 'intelligible constructs' not typically modeled in ontologies. Intelligible constructs convey essential information, which may be important to the holistic information needs of information seekers. Such constructs may include notions of intensity, frequency, interval, dosage, emotion, sentiment, equivalence, synonymy, negation, parts-of-speech, etc. However, few search systems utilize both structured background knowledge (ontologies) and the aforementioned knowledge for query interpretation in domain specific searches. Instead, there is …

Traffic Analytics Using Probabilistic Graphical Models Enhanced With Knowledge Bases, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Graphical models have been successfully used to deal with uncertainty, incompleteness, and dynamism within many domains. These models built from data often ignore preexisting declarative knowledge about the domain in the form of ontologies and Linked Open Data (LOD) that is increasingly available on the web. In this paper, we present an approach to leverage such 'top-down' domain knowledge to enhance 'bottom-up' building of graphical models. Specifically, we propose three operations on the graphical model structure to enrich it with nodes, edges, and edge directions. We illustrate the enrichment process using traffic data from 511.org and declarative knowledge from ConceptNet. …

Advancing Data Reuse In Phyloinformatics Using An Ontology-Driven Semantic Web Approach, Maryam Panahiazar, Amit P. Sheth, Ajith Harshana Ranabahu, Rutger Vos, Jim Leebens-Mack

Kno.e.sis Publications

Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web …

Twitris: Socially Influenced Browsing, Ashutosh Sopan Jadhav, Wenbo Wang, Raghava Mutharaju, Pramod Anantharam, Vinh Nguyen, Amit P. Sheth, Karthik Gomadam, Meenakshi Nagarajan, Ajith Harshana Ranabahu

Kno.e.sis Publications

In this paper, we present Twitris, a semantic Web application that facilitates browsing for news and information, using social perceptions as the fulcrum. In doing so we address challenges in large scale crawling, processing of real time information, and preserving spatio-temporal-thematic properties central to observations pertaining to real time events. We extract metadata about events from Twitter and bring related news and Wikipedia articles to the user. In developing Twitris, we have used the DBPedia ontology.

Adaptive Semantic Annotation Of Entity And Concept Mentions In Text, Pablo N. Mendes

Kno.e.sis Publications

The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.
These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a …

Consequence Based Procedure For Description Logics With Self Restriction, Cong Wang, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a consequence based classification procedure for the description logics with self restriction constructor. Due to the difficulty of constructing a concept inclusion model for self restriction, we use a different proof by showing that all the completion rules can simulate all the corresponding ordered resolution inferences.

Logical Linked Data Compression, Amit Krishna Joshi, Pascal Hitzler, Guozhu Dong

Computer Science and Engineering Faculty Publications

Linked data has experienced accelerated growth in recent years. With the continuing proliferation of structured data, demand for RDF compression is becoming increasingly important. In this study, we introduce a novel lossless compression technique for RDF datasets, called Rule Based Compression (RB Compression) that compresses datasets by generating a set of new logical rules from the dataset and removing triples that can be inferred from these rules. Unlike other compression techniques, our approach not only takes advantage of syntactic verbosity and data redundancy but also utilizes semantic associations present in the RDF graph. Depending on the nature of the dataset, …

Group Developed Weighing Matrices, K. T. Arasu, Jeffrey R. Hollon

Mathematics and Statistics Faculty Publications

A weighing matrix is a square matrix whose entries are 1, 0 or −1, such that the matrix times its transpose is some integer multiple of the identity matrix. We examine the case where these matrices are said to be devel- oped by an abelian group. Through a combination of extending previous results and by giving explicit constructions we will answer the question of existence for 318 such matrices of order and weight both below 100. At the end, we are left with 98 open cases out of a possible 1,022. Further, some of the new results provide insight into …

A Latent Dirichlet Allocation/N-Gram Composite Language Model, Raymond Daniel Kulhanek

Browse all Theses and Dissertations

I present a composite language model in which an n-gram language model is integrated with the Latent Dirichlet Allocation topic clustering model. I also describe a parallel architecture that allows this model to be trained over large corpora and present experimental results that show how the composite model compares to a standard n-gram model over corpora of varying size.

A Large Scale Distributed Syntactic, Semantic And Lexical Language Model For Machine Translation, Ming Tan

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The n-gram model is the most widely used language model (LM) in statistical machine translation system, due to its simplicity and scalability. However, it only encodes the local lexical relation between adjacent words and clearly ignores the rich syntactic and semantic structures of the natural languages. Attempting to increase the order of an n-gram to describe longer range dependencies in natural language immediately runs into the curse of dimensionality. Although previous researches tried to increase the order of n-gram on a large corpus, they did not see obvious improvement beyond 6-gram. Meanwhile, other LMs, such as syntactic language models and …

A Semantics-Based Approach To Machine Perception, Cory Andrew Henson

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Machine perception can be formalized using semantic web technologies in order to derive abstractions from sensor data using background knowledge on the Web, and efficiently executed on resource-constrained devices. Advances in sensing technology hold the promise to revolutionize our ability to observe and understand the world around us. Yet the gap between observation and understanding is vast. As sensors are becoming more advanced and cost-effective, the result is an avalanche of data of high volume, velocity, and of varied type, leading to the problem of too much data and not enough knowledge (i.e., insights leading to actions). Current estimates predict …

A Methodology For Extracting Human Bodies From Still Images, Athanasios Tsitsoulis

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Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that …

Anomalies In Sensor Network Deployments: Analysis, Modeling, And Detection, Giovani Rimon Abuaitah

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A sensor network serves as a vital source for collecting raw sensory data. Sensor data are later processed, analyzed, visualized, and reasoned over with the help of several decision making tools. A decision making process can be disastrously misled by a small portion of anomalous sensor readings. Therefore, there has been a vast demand for mechanisms that identify and then eliminate such anomalies in order to ensure the quality, integrity, and/or trustworthiness of the raw sensory data before they can even be interpreted.

Prior to identifying anomalies, it is essential to understand the various anomalous behaviors prevalent in a sensor …

Cooperative Interactive Distributed Guidance On Mobile Devices, Gregory Burnett

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Mobiles device are quickly becoming an indispensable part of our society. Equipped with numerous communication capabilities, they are increasingly being examined as potential tools for civilian and military usage to aide in distributed remote collaboration for dynamic decision making and physical task completion. With an ever growing mobile workforce, the need for remote assistance in aiding field workers who are confronted with situations outside their expertise certainly increases. Enhanced capabilities in using mobile devices could significantly improve numerous components of a task's completion (i.e. accuracy, timing, etc.). This dissertation considers the design of mobile implementation of technology and communication capabilities …

Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills

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The purpose of this research is to design and implement a new methodology that captures the natural language understanding of events from English natural language text and model it using Stochastic Petri Nets. To establish a baseline of recent natural language processing (NLP) and understanding (NLU) research, two surveys are presented. One is a general survey in NLP and NLU methodologies for processing multi-documents. It summarizes and presents methodologies in terms of their features, capabilities, and maturity. The second survey focuses on graph-based methods for NL text processing and understanding and analyzes them in terms of their functional descriptions, capabilities …

Semsos : An Architecture For Query, Insertion, And Discovery For Semantic Sensor Networks, Joshua Kenneth Pschorr

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With sensors, storage, and bandwidth becoming ever cheaper, there has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web and then interpreting their observations is a non-trivial challenge. The Open Geospatial Consortium (OGC) defines a web service specification known as the Sensor Observation Service (SOS) that is designed to standardize the way sensors and sensor data are discovered and accessed on the Web. Though this standard goes a long way in providing interoperability between sensor data producers and …

Two Fundamental Building Blocks To Provide Quick Reaction Capabilities For The Department Of Defense, Daniel Alan Uppenkamp

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The Department of Defense (DoD) has a need for long-term development efforts in conjunction with short-term development efforts. Ideally, Quick Reaction Capabilities (QRC) would be able to make use of the same processes that are used for Acquisition Programs (AP) with a few modifications to accommodate the accelerated schedule. Unfortunately, APs have a more fundamental problem with both the development process and the development framework. In August of 2007, the agile development process and modular, open source framework discussed in this thesis were two key factors that enabled the Air Force Research Laboratory (AFRL) to successfully deploy AngelFire in support …

Adaptive Semantic Annotation Of Entity And Concept Mentions In Text, Pablo N. Mendes

Browse all Theses and Dissertations

The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.

These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a …

Mining Diversified Decision Trees Across Multiple Datasets To Capture Similarities And Alignable Differences, Qian Han

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This dissertation studies the problem of mining shared and alignable difference knowledge structures across multiple datasets/applications. Shared and alignable difference knowledge structures are important for identifying analogies between application domains and for forming new hypothesis in challenging research applications, and for assessing the degree and types of knowledge-level similarities and differences between application domains for use in learning transfer. Generally speaking, shared knowledge structures characterize underlying datasets and highlight conceptual-level structural similarities among the datasets. This dissertation studies the mining of shared decision trees, which are a special type of shared knowledge structures. We first consider building one shared decision …

Multivariate Data Analysis, Diana Copeland, Michael Raymer

Explorations – The Journal of Undergraduate Research, Scholarship and Creativity at Wright State

The study of biology, computer science, and information technology all combine to form the science of bioinformatics [1]. This field was created to make discoveries on new biological insights [1]. Bioinformatics has several important task one of them being able to analyze and interpret different types of data and this includes multivariate data analysis. Multivariate data analysis can use linear projection methods such as linear discriminant analysis (LDA), principal component analysis (PCA), and projection to latent structures (PLS). I have created a Java program that can manipulate multivariate data by manual rotation and will be comparing my results to the …

User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas

Kno.e.sis Publications

Web applications are increasingly showing recommended users from social media along with some descriptions, an attempt to show relevancy - why they are being shown. For example, Twitter search for a topical keyword shows expert twitterers on the side for 'whom to follow'. Google+ and Facebook also recommend users to follow or add to friend circle. Popular Internet newspaper- The Huffington Post shows Twitter influencers/ experts on the side of an article for authoritative relevant tweets. The state of the art shows user profile bios as summary for Twitter experts, but it has issues with length constraint imposed by user …

Are Twitter Users Equal In Predicting Elections? A Study Of User Groups In Predicting 2012 U.S. Republican Primaries, Lu Chen, Wenbo Wang, Amit P. Sheth

Kno.e.sis Publications

Existing studies on predicting election results are under the assumption that all the users should be treated equally. However, recent work [14] shows that social media users from different groups (e.g., “silent majority” vs. “vocal minority”) have significant differences in the generated content and tweeting behavior. The effect of these differences on predicting election results has not been exploited yet. In this paper, we study the spectrum of Twitter users who participate in the on-line discussion of 2012 U.S. Republican Presidential Primaries, and examine the predictive power of different user groups (e.g., highly engaged users vs. lowly engaged users, right-leaning …

The Ssn Ontology Of The W3c Semantic Sensor Network Incubator Group, Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Andrew Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit P. Sheth, Kerry Taylor

Kno.e.sis Publications

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

Demonstration: Dynamic Sensor Registration And Semantic Processing For Ad-Hoc Mobile Environments (Semmob), Pramod Anantharam, Gary Alan Smith, Josh Pschorr, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

SemMOB enables dynamic registration of sensors via mobile devices, search, and near real-time inference over sensor observations in ad-hoc mobile environments (e.g., fire fighting). We demonstrate SemMOB in the context of an emergency response use case that requires automatic and dynamic registrations of sensor devices and annotation of sensor observations, decoding of latitude-longitude information in terms of human sensible names, fusion and abstraction of sensor values using background knowledge, and their visualization using mash-up.