Databases and Information Systems Commons^™

Using Attribute Behavior Diversity To Build Accurate Decision Tree Committees For Microarray Data, Qian Han, Guozhu Dong

Kno.e.sis Publications

DNA microarrays (gene chips), frequently used in biological and medical studies, measure the expressions of thousands of genes per sample. Using microarray data to build accurate classifiers for diseases is an important task. This paper introduces an algorithm, called Committee of Decision Trees by Attribute Behavior Diversity (CABD), to build highly accurate ensembles of decision trees for such data. Since a committee's accuracy is greatly influenced by the diversity among its member classifiers, CABD uses two new ideas to "optimize" that diversity, namely (1) the concept of attribute behavior–based similarity between attributes, and (2) …

Common Criteria Meets Realpolitik Trust, Alliances, And Potential Betrayal, Jan Kallberg

Jan Kallberg

Common Criteria for Information Technology Security Evaluation has the ambition to be a global standard for IT-security certification. The issued certifications are mutually recognized between the signatories of the Common Criteria Recognition Arrangement. The key element in any form of mutual relationships is trust. A question raised in this paper is how far trust can be maintained in Common Criteria when additional signatories enter with conflicting geopolitical interests to earlier signatories. Other issues raised are control over production, the lack of permanent organization in the Common Criteria, which leads to concerns of being able to oversee the actual compliance. As …

Twitris+: Social Media Analytics Platform For Effective Coordination, Gary Alan Smith, Amit P. Sheth, Ashutosh Sopan Jadhav, Hemant Purohit, Lu Chen, Michael Cooney, Pavan Kapanipathi, Pramod Anantharam, Pramod Koneru, Wenbo Wang

Kno.e.sis Publications

Twitris+ is a Semantic Social Media analytics platform to provide technologies for analyzing large-scale social media streams across Spatio-Temporal-Thematic (STT) and People-Content-Network (PCN) dimensions. It provides holistic situational awareness from one interface and enables organizational actors to engage in well-coordinated ways for desired tasks during emergency response.

Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …

The Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Yunxin Zhao

Kno.e.sis Publications

We present an extension to Jaynes’ maximum entropy principle that incorporates latent variables. The principle of latent maximum entropy we propose is different from both Jaynes’ maximum entropy principle and maximum likelihood estimation, but can yield better estimates in the presence of hidden variables and limited training data. We first show that solving for a latent maximum entropy model poses a hard nonlinear constrained optimization problem in general. However, we then show that feasible solutions to this problem can be obtained efficiently for the special case of log-linear models---which forms the basis for an efficient approximation to the latent maximum …

Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk

Kno.e.sis Publications

We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested [student within school] fixed effects multinomial logistic regression models were specified from these using Akaike’s Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions …

What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach

Kno.e.sis Publications

The present research aims to detect coordinated citizen response within social media traffic to assist emergency response. We use domain-independent linguistic properties as the first step in narrowing the candidate set of messages for domain-dependent and computationally intensive analysis.

Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.

Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Twitter has enjoyed tremendous popularity in the recent years. To help categorizing and search tweets, Twitter users assign hashtags to their tweets. Given that hashtag assignment is the primary way to semantically categorizing and search tweets, it is highly susceptible to abuse by spammers and other anomalous users [1]. Popular hashtags such as #Obama and #ladygaga could be hijacked by having them added to unrelated tweets with the intent of misleading many other users or promoting specific agenda to the users. The users performing this act are known as the hashtag hijackers. As the hijackers usually abuse common sets of …

Iexplore: A Provenance-Based Application For Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Thomas Rindflesch, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

W3c Semantic Sensor Networks: Ontologies, Applications, And Future Directions, Cory Andrew Henson

Kno.e.sis Publications

Plenary Talk discussing the W3C Semantic Sensor Network, including the ontology, applications, and future directions.

Towards Cyber Operations The New Role Of Academic Cyber Security Research And Education, Jan Kallberg, Bhavani Thuraisingham

Jan Kallberg

Abstract – The shift towards cyber operations represents a shift not only for the defense establishments worldwide but also cyber security research and education. Traditionally cyber security research and education has been founded on information assurance, expressed in underlying subfields such as forensics, network security, and penetration testing. Cyber security research and education is connected to the homeland security agencies and defense through funding, mutual interest in the outcome of the research, and the potential job market for graduates. The future of cyber security is both defensive information assurance measures and active defense driven information operations that jointly and coordinately …

Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth

Kno.e.sis Publications

We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …

A Web-Based Study Of Self-Treatment Of Opioid Withdrawal Symptoms With Loperamide, Raminta Daniulaityte, Robert G. Carlson, Russel S. Falck, Delroy H. Cameron, Sujan Udayanaga, Lu Chen, Amit P. Sheth

Kno.e.sis Publications

Aims: Many websites provide a medium for individuals to freely share their experiences and knowledge about different drugs. Such user-generated content can be used as a rich data source to study emerging drug use practices and trends. The study aims to examine web-based reports of loperamide use practices among non-medical opioid users. Loperamide, a piperidine derivative, is an opioid agonist approved for the control of diarrhea symptoms. Because of its general inability to cross the blood-brain barrier, it is considered to have no abuse potential and is available without a prescription. Methods: A website that allows free discussion of illicit …

Topical Anomaly Detection From Twitter Streams, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong

Research Collection School Of Computing and Information Systems

Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According …

Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria

Research Collection School Of Computing and Information Systems

Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive balanced news information is important. We propose a model that maps the news media sources along a dimensional dichotomous political spectrum using the co-subscriptions relationships inferred by Twitter links. By analyzing 7 million follow links, we show that the political dichotomy naturally arises on Twitter when we only consider direct media subscription. Furthermore, we demonstrate a real-time Twitter-based application …

Integrating Owl And Rules: A Syntax Proposal For Nominal Schemas, David Carral Martinez, Adila Krisnadhi, Pascal Hitzler

Computer Science and Engineering Faculty Publications

This paper proposes an addition to OWL 2 syntax to incorporate nominal schemas, which is a new description-logic style extension of OWL 2 which was recently proposed, and which makes is possible to express "variable nominal classes" within axioms in an OWL 2 ontology. Nominal schemas make it possible to express DL-safe rules of arbitrary arity within the extended OWL paradigm, hence covering the well-known DL-safe SWRL language. To express this feature, we extend OWL 2 syntax to include necessary and minimal modifications to both Functional and Manchester syntax grammars and mappings from these two syntaxes to Turtle/RDF. We also …

Semantic Aspects Of Earthcube, Pascal Hitzler, Krzysztof Janowicz, Gary Berg-Cross, Leo Obrst, Amit P. Sheth, Timothy Finin, Isabel F. Cruz

Kno.e.sis Publications

In this document, we give a high-level overview of selected Semantic (Web) technologies, methods, and other important considerations, that are relevant for the success of EarthCube. The goal of this initial document is to provide entry points and references for discussions between the Semantic Technologies experts and the domain experts within EarthCube. The selected topics are intended to ground the EarthCube roadmap in the state of the art in semantics research and ontology engineering.

We anticipate that this document will evolve as EarthCube progresses. Indeed, all EarthCube parties are asked to provide topics of importance that should be treated in …

Trust Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, semantic sensor web, etc. As collaborating agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update become critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and secure system for managing trust, to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics …

Extending Description Logic Rules, David Carral Martinez, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Description Logics – the logics underpinning the Web Ontology Language OWL – and rules are currently the most prominent paradigms used for modeling knowledge for the Semantic Web. While both of these approaches are based on classical logic, the paradigms also differ significantly, so that naive combinations result in undesirable properties such as undecidability. Recent work has shown that many rules can in fact be expressed in OWL. In this paper we extend this work to include some types of rules previously excluded. We formally define a set of first order logic rules, C-Rules, which can be expressed within OWL …

Towards Self-Emancipation In Ict For Development Research: Narratives About Respect, Traditional Leadership And Building Networks Of Friendships In Rural South Africa, Kirstin Krauss

The African Journal of Information Systems

In this paper, the author contends that if the outsider-researcher involved in Information and Communication Technology for Development really wants to make a difference and honestly address the emancipatory interests of the developing community, social transformation will have to occur on both sides of the “development divide.” This statement implies both an understanding of the researcher’s own ethnocentrism, prejudice, assumptions and inabilities as well as local concerns, needs, expectations and realities. Using critical social theory as a position of inquiry and learning from the enculturation phases of critical ethnographic fieldwork in a deep rural part of South Africa, the paper …

Hearts And Minds: Examining The Evolution Of The Egyptian Excerebration And Evisceration Traditions Through The Impact Mummy Database, Andrew D. Wade

Electronic Thesis and Dissertation Repository

Egyptian mummification and funerary rituals were a transformative process, making the deceased a pure being; free of disease, injury, and disfigurements, as well as ethical and moral impurities. Consequently, the features of mummification available to specific categories of individuals hold social and ideological significance. This study refutes long-held classical stereotypes, particularly dogmatic class associations; demonstrates the apocryphal nature of universal heart retention; and expands on the purposes of excerebration and evisceration implied by synthetic and radiological analyses.

Features of the embalming traditions, specifically the variable excerebration and evisceration traditions, represented the Egyptian view of death. Fine-grain analyses, through primary imaging …

Structural Analysis In Multi-Relational Social Networks, Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Modern social networks often consist of multiple relationsamong individuals. Understanding the structureof such multi-relational network is essential. In sociology,one way of structural analysis is to identify differentpositions and roles using blockmodels. In thispaper, we generalize stochastic blockmodels to GeneralizedStochastic Blockmodels (GSBM) for performing positionaland role analysis on multi-relational networks.Our GSBM generalizes many different kinds of MultivariateProbability Distribution Function (MVPDF) tomodel different kinds of multi-relational networks. Inparticular, we propose to use multivariate Poisson distributionfor multi-relational social networks. Our experimentsshow that GSBM is able to identify the structuresfor both synthetic and real world network data.These structures can further be used for predicting …

Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso

Kno.e.sis Publications

The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. Standard quantification techniques attempt to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition. These techniques fail to account for adjacent signals which can lead to drastic quantification errors. Attempts at full spectrum deconvolution have been limited in adoption and development due to the computational resources required. Herein, we develop a novel localized deconvolution algorithm for general purpose quantification of NMR-based metabolomics studies. Localized deconvolution decreases average absolute quantification error by 97% and …

Designer Satellite Collisions From Covert Cyber War, Jan Kallberg

Jan Kallberg

Outer space has enjoyed two decades of fairly peaceful development since the Cold War, but once again it is becoming more competitive and contested, with increased militarization. Therefore, it is important the United States maintain its space superiority to ensure it has the capabilities required by modern warfare for successful operations. Today is different from earlier periods of space development,1 because there is not a blatantly overt arms race in space,2 but instead a covert challenge to US interests in maintaining superiority, resilience, and capability. A finite number of states consider themselves geopolitical actors; however, as long as the United …

Framework For The Analysis Of Coordination In Crisis Response, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach

Kno.e.sis Publications

Social Media play a critical role during crisis events, revealing a natural coordination dynamic. We propose a computational framework guided by social science principles to measure, analyze, and understand coordination among the different types of organizations and actors in crisis response. The analysis informs both the scientific account of cooperative behavior and the design of applications and protocols to support crisis management.

The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar

Research Collection School Of Computing and Information Systems

The social network perspective has served as a useful framework for studying scientific research collaboration in different disciplines. Although collaboration in computer science research has received some attention, software engineering research collaboration has remained unexplored to a large extent. In this paper, we examine the collaboration networks based on co-authorship information of papers from ten software engineering publication venues over the 1976-2010 time period. We compare time variations of certain parameters of these networks with corresponding parameters of collaboration networks from other disciplines. We also explore whether software engineering collaboration networks manifest symptoms of the small-world phenomenon, conform to the …

Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth

Kno.e.sis Publications

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system …

A Semantic Problem Solving Environment For Integrative Parasite Research: Identification Of Intervention Targets For Trypanosoma Cruzi, Priti Parikh, Todd Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H. Asiaee, Satya S. Sahoo, Prashant Doshi, Rick L. Tarleton, Amit P. Sheth

Kno.e.sis Publications

Background: Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites, and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external …