Digital Commons Network^™

Why Fuzzy Cognitive Maps Are Efficient, Vladik Kreinovich, Chrysostomos Stylios

Departmental Technical Reports (CS)

In many practical situations, the relation between the experts' degrees of confidence in different related statements is well described by Fuzzy Cognitive Maps (FCM). This empirical success is somewhat puzzling, since from the mathematical viewpoint, each FCM relation corresponds to a simplified one-neuron neural network, and it is well known that to adequately describe relations, we need multiple neurons. In this paper, we show that the empirical success of FCM can be explained if we take into account that human's subjective opinions follow Miller's seven plus minus two law.

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

New packages in CRAN task views

New contributed packages

Other changes

Trust Management: Multimodal Data Perspective, Krishnaprasad Thirunarayan

Kno.e.sis Publications

No abstract provided.

A Cultural Diffusion Model For The Rise And Fall Of Programming Languages, Sergi Valverde, Ricard V. Solé

Human Biology Open Access Pre-Prints

Our interaction with complex computing machines is mediated by programming languages (PLs) which constitute one of the major innovations in the evolution of technology. PLs allowed a flexible, scalable and fast use of hardware and are largely responsible for shaping the history of information technology since the rise of computers in the 1950s. The rapid growth and impact of computers was followed closely by the development of programming languages. As it occurs with natural, human languages, they emerged and got extinct. There has been always a diversity of coexisting PLs that somewhat compete among them, while occupying special niches. Here …

Information Filtering By Multiple Examples, Mingzhu Zhu

Dissertations

A key to successfully satisfy an information need lies in how users express it using keywords as queries. However, for many users, expressing their information needs using keywords is difficult, especially when the information need is complex. Search By Multiple Examples (SBME), a promising method for overcoming this problem, allows users to specify their information needs as a set of relevant documents rather than as a set of keywords.

Most of the studies on SBME adopt the Positive Unlabeled learning (PU learning) techniques by treating the user's provided examples (denoted as query examples) as positive set and the entire data …

Malware Detection Using Dynamic Analysis, Swapna Vemparala

Master's Projects

In this research, we explore the field of dynamic analysis which has shown promis- ing results in the field of malware detection. Here, we extract dynamic software birth- marks during malware execution and apply machine learning based detection tech- niques to the resulting feature set. Specifically, we consider Hidden Markov Models and Profile Hidden Markov Models. To determine the effectiveness of this dynamic analysis approach, we compare our detection results to the results obtained by using static analysis. We show that in some cases, significantly stronger results can be obtained using our dynamic approach.

Identifying Common Characteristics Of Malicious Insiders, Nan Liang, David Biros

Annual ADFSL Conference on Digital Forensics, Security and Law

Malicious insiders account for large proportion of security breaches or other kinds of loss for organizations and have drawn attention of both academics and practitioners. Although methods and mechanism have been developed to monitor potential insider via electronic data monitoring, few studies focus on predicting potential malicious insiders. Based on the theory of planned behavior, certain cues should be observed or expressed when an individual performs as a malicious insider. Using text mining to analyze various media content of existing insider cases, we strive to develop a method to identify crucial and common indicators that an individual might be a …

An Open Source Advertisement Server, Pushkar Umaranikar

Master's Projects

This report describes a new online advertisement system and its implementation for the Yioop open source search engine. This system was implemented for my CS298 project. It supports both selling advertisements and displaying them within search results. The selling of advertisement is done using a novel auction system, which we describe in this paper. With this auction system, it is possible to create an advertisement, attach keywords to it, and add it to the advertisement inventory. An advertisement is displayed on a search results page if the search keyword matches the keywords attached to the advertisement. Display of advertisements is …

Developing A Bilingual, Computer-Tailored, Hpv Vaccination Promotion Intervention Targeting Latino Parents, Angela Chia-Chen Chen, Ashish Amresh

Publications

In this paper we present an innovative, computer-tailored application aimed at increasing Latino parents' intention to vaccinate their adolescent children against Human Papilloma Virus (HPV). HPV infection is the most common sexually transmitted infection in the United States. Latinas have the highest age-adjusted incidence rate for HPV-associated cervical cancer compared with their counterparts in other racial/ethnic groups. HPV vaccines offer hope against HPV-associated diseases. Because parental consent is required for children under age 18 to receive t h e HPV vaccination in most U. S. states, parents' attitudes and intention to have their children vaccinated are keys for promoting HPV …

Active Semi-Supervised Defect Categorization, Ferdian Thung, Xuan-Bach D. Le, David Lo

Research Collection School Of Computing and Information Systems

Defects are inseparable part of software development and evolution. To better comprehend problems affecting a software system, developers often store historical defects and these defects can be categorized into families. IBM proposes Orthogonal Defect Categorization (ODC) which include various classifications of defects based on a number of orthogonal dimensions (e.g., symptoms and semantics of defects, root causes of defects, etc.). To help developers categorize defects, several approaches that employ machine learning have been proposed in the literature. Unfortunately, these approaches often require developers to manually label a large number of defect examples. In practice, manually labelling a large number of …

Tasknav: Task-Based Navigation Of Software Documentation, Christoph Treude, Mathieu Sicard, Marc Klocke, Martin P. Robillard

Research Collection School Of Computing and Information Systems

To help developers navigate documentation, we introduce Task Nav, a tool that automatically discovers and indexes task descriptions in software documentation. With Task Nav, we conceptualize tasks as specific programming actions that have been described in the documentation. Task Nav presents these extracted task descriptions along with concepts, code elements, and section headers in an auto-complete search interface. Our preliminary evaluation indicates that search results identified through extracted task descriptions are more helpful to developers than those found through other means, and that they help bridge the gap between documentation structure and the information needs of software developers. Video: https://www.youtube.com/watch?v=opnGYmMGnqY.

Micro-Policies: Formally Verified, Tag-Based Security Monitors, Arthur Azevedo De Amorim, Maxime Denes, Nick Giannarakis, Cătălin Hriţcu, Benjamin C. Pierce, Antal Spector-Zabusky, Andrew Tolmach

Computer Science Faculty Publications and Presentations

Recent advances in hardware design have demonstrated mechanisms allowing a wide range of low-level security policies (or micro-policies) to be expressed using rules on metadata tags. We propose a methodology for defining and reasoning about such tag-based reference monitors in terms of a high-level “symbolic machine,” and we use this methodology to define and formally verify micro-policies for dynamic sealing, compartmentalization, control-flow integrity, and memory safety; in addition, we show how to use the tagging mechanism to protect its own integrity. For each micro-policy, we prove by refinement that the symbolic machine instantiated with the policy’s rules embodies a high-level …

Flutcha: Using Fluency To Distinguish Humans From Computers, Kotaro Hara, Mohammad Taghi Hajiaghayi, Benjamin B. Benderson

Research Collection School Of Computing and Information Systems

Improvements in image understanding technologies aremaking it possible for computers to pass traditionalCAPTCHA tests with high probability. This suggests theneed for new kinds of tasks that are easy to accomplishfor humans but remain difficult for computers. In thispaper, we introduce Fluency CAPTCHA (FluTCHA), anovel method to distinguish humans from computersusing the fact that humans are better than machines atimproving the fluency of sentences. We propose a wayto let users work on FluTCHA tests and simultaneouslycomplete useful linguistic tasks. Evaluation studiesdemonstrate the feasibility of using FluTCHA todistinguish humans from computers.

Rclinker: Automated Linking Of Issue Reports And Commits Leveraging Rich Contextual Information, Tien-Duy B. Le, Mario Linares Vasquez, David Lo, Denys Poshyvanyk

Research Collection School Of Computing and Information Systems

Links between issue reports and their corresponding commits in version control systems are often missing. However, these links are important for measuring the quality of a software system, predicting defects, and many other tasks. Several approaches have been designed to solve this problem by automatically linking bug reports to source code commits via comparison of textual information in commit messages and bug reports. Yet, the effectiveness of these techniques is oftentimes suboptimal when commit messages are empty or contain minimum information; this particular problem makes the process of recovering traceability links between commits and bug reports particularly challenging. In this …

Advances In Knowledge Discovery And Data Mining Part Ii, Tru Cao, Ee Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda

Research Collection School Of Computing and Information Systems

No abstract provided.

Characterizing Silent Users In Social Media Communities, Wei Gong, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Silent users often constitute a significant proportion of an online user-generated content system. In the context of social media such as Twitter, users can opt to be silent all or most of the time. They are often called the invisible participants or lurkers. As lurkers contribute little to the online content, existing analysis often overlooks their presence and voices. However, we argue that understanding lurkers is important in many applications such as recommender systems, targeted advertising, and social sensing. This research therefore seeks to characterize lurkers in social media and propose methods to profile them. We examine 18 weeks of …

A Multi-Level Analysis Of Collaborations In Computer Science, Pramod Divakarmurthy

Theses and Dissertations

Working in collaboration is common in today’s highly connected scientific community. By collaborating, researchers can solve challenging multi-disciplinary problems, increase knowledge dissemination as well as productivity. These and other advantages motivate the study of the collaboration patterns of researchers. Such patterns can be observed directly in networks of manuscript co-authorship. In such a network, nodes represent authors and the links between them indicate that they have co-authored a paper. Several researchers constructed and studied large-scale networks representing collaborations in Mathematics, Biology, Physics, and Neuroscience. Most studies have performed bibliometric analysis of scientific publications, evaluated and ranked scholars on their research …

Handling Human Hacking: Creating A Comprehensive Defensive Strategy Against Modern Social Engineering, Charles Snyder

Senior Honors Theses

Social engineering is one of the most devastating threats to any company or business. Rather than relying upon technical flaws in order to break into computer networks, social engineers utilize a suave personality in order to deceive individuals through clever conversation. These devious conversations frequently provide the attacker with sufficient information to compromise the company’s computer network. Unlike common technical attacks, social engineering attacks cannot be prevented by security tools and software. Instead of attacking a network directly, a social engineer exploits human psychology in order to coerce the victim to inadvertently divulge sensitive information. Further complicating the issue, the …

Differences In Cognitive Processing Between Deaf And Hearing Individuals When Presented With Linguistic Stimuli, Aubrey Hatch, Michael Jones

Journal of Undergraduate Research

My project was designed to increase our understanding of the neurological processes of deaf individuals to shape future adaptive technologies to facilitate better education for the deaf community. More specifically, my goal was to focus on the cognitive differences between deaf and hearing individuals when presented with different types of linguistic stimuli such as: a spoken word, a written word, a signed video of a word, or a picture that represents a specific word. By increasing our understanding of these cognitive differences, I hoped to help increase the capabilities of future adaptive technological devices that would be beneficial for those …

A Corpus For Investigating English-Language Learners' Dialog Behaviors, Nigel Ward, Paola Gallardo

Departmental Technical Reports (CS)

We are interested in developing methods for the semi-automatic discovery of prosodic patterns in dialog and how they differ between languages and among populations. We are starting by examining how the prosody of Spanish-native learners of English differs from that of native speakers. To support this work, we have collected a new corpus of conversations among college students. This includes dialogs between a nonnative speaker of English and a native, dialogs between native speakers of English, and Spanish conversations.

A Novel Root Based Arabic Stemmer, Mohammed N. Al-Kabi, Saif A. Kazakzeh, Belal M. Abu Ata, Saif A. Al-Rababah, Izzat M. Alsmadi

Computer Science Faculty Publications and Presentations

Stemming algorithms are used in information retrieval systems, indexers, text mining, text classifiers etc., to extract stems or roots of different words, so that words derived from the same stem or root are grouped together. Many stemming algorithms were built in different natural languages. Khoja stemmer is one of the known and widely used Arabic stemmers. In this paper, we introduced a new light and heavy Arabic stemmer. This new stemmer is presented in this study and compared with two well-known Arabic stemmers. Results showed that accuracy of our stemmer is slightly better than the accuracy yielded by each one …

Governance And Organizational Sponsorship As Success Factors In Free/Libre And Open Source Software Development: An Empirical Investigation Using Structural Equation Modeling, Aleksandr Blekh

CCAC Theses and Dissertations

Recent advances in information technologies and subsequent explosive growth of computer software use in practically all aspects of everyday life provide tremendous opportunities and benefits for improving people's lives. However, significant proportion of software projects represents cancelled, abandoned or otherwise failed projects. This situation exists not only in commercial software products or government information systems, but also in an increasingly popular and important domain of free/libre and open source software (FLOSS).

The problem of failures in software development projects requires identification and understanding of the factors of success and their interrelationships. Practice and previous research suggest that governance of software …

News Feeds Clustering Research Study, Haytham Abuel-Futuh

CCAC Theses and Dissertations

With over 0.25 billion web pages hosted in the World Wide Web, it is virtually impossible to navigate through the Internet. Many applications try to help users achieve this task. For example, search engines build indexes to make the entire World Wide Web searchable, and news curators allow users to browse topics of interest on different structured sites. One problem that arises for these applications and others with similar goals is identifying documents with similar contents. This helps the applications show users documents with unique contents as well as group various similar documents under similar topics. There has been a …

Exploring Cyberbullying And Other Toxic Behavior In Team Competition Online Games, Haewoon Kwak, Jeremy Blackburn, Seungyeop. Han

Research Collection School Of Computing and Information Systems

In this work we explore cyberbullying and other toxic behavior in team competition online games. Using a dataset of over 10 million player reports on 1.46 million toxic players along with corresponding crowdsourced decisions, we test several hypotheses drawn from theories explaining toxic behavior. Besides providing large-scale, empirical based understanding of toxic behavior, our work can be used as a basis for building systems to detect, prevent, and counter-act toxic behavior.

Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang

Research Collection School Of Computing and Information Systems

Online social networks release user attributes, which is important for many applications. Due to the sparsity of such user attributes online, many works focus on profiling user attributes automatically. However, in order to profile a specific user attribute, an unique model is built and such model usually does not fit other profiling tasks. In our work, we design a novel, flexible general user profiling model which naturally models users’ friendships with user attributes. Experiments show that our method simultaneously profile multiple attributes with better performance.

Towards An Integrated Model Of The Mental Lexicon, Natawut Monaikul

All Student Theses and Dissertations

Several models have been proposed attempting to describe the mental lexicon-the abstract organization of words in the human mind. Numerous studies have shown that by representing the mental lexicon as a network, where nodes represent words and edges connect similar words using a metric based on some word feature, a small-world structure is formed. This property, pervasive in many real-world networks, implies processing efficiency and resiliency to node deletion within the system, explaining the need for such a robust network as the mental lexicon. However, each model considered a single word feature at a time, such as semantic or phonological …

Neurological Research To Supplement Hmd Technology Development For The Benefit Of Deaf And Hard-Of-Hearing Students, Tyler Foulger, Michael Jones

Journal of Undergraduate Research

Introduction: The purpose of this MRI study was an attempt to discover and understand how communication is processed via the neural pathways of children ages 8-10. Analysis of the data we obtained would possibly help us in better adapting our head-mounted display (HMD) technology for deaf and hard-of-hearing children in educational settings where communication is common. Since HMDs utilize a sign language interpreter within a screen on the glasses, this technology would eliminate the need for deaf/hard-of-hearing users to constantly alternate their attention back and forth between a live interpreter in the room and the presentation by the teacher. Having …

Multilingual Extraction Ontologies, David W. Embley, Stephen W. Liddle, Deryle W. Lonsdale, Yuri Tijerino

Journal of Undergraduate Research

On December 29, 2009 we were informed that our application for a 2010 MEG grant was approved. This final report sketches the accomplishments attained during the project’s timeframe since then.

Unknown Threat Detection With Honeypot Ensemble Analsyis Using Big Datasecurity Architecture, Michael Eugene Sanders

Theses and Dissertations

The amount of data that is being generated continues to rapidly grow in size and complexity. Frameworks such as Apache Hadoop and Apache Spark are evolving at a rapid rate as organizations are building data driven applications to gain competitive advantages. Data analytics frameworks decomposes our problems to build applications that are more than just inference and can help make predictions as well as prescriptions to problems in real time instead of batch processes.

Information Security is becoming more important to organizations as the Internet and cloud technologies become more integrated with their internal processes. The number of attacks and …

An Interpretive Phenomenological Analysis Inquiry Into Facebook Newcomer Motivations For Participatory Activities, Kristin Raub

CCAC Theses and Dissertations

This qualitative study provided insight into the phenomenon of newcomers in social networking, in particular, to understand what role specific Facebook features play in motivating content sharing and contribution among newcomers. Research indicated that the first several months or years of social networking site (SNS) membership are the most crucial in terms of indicating long-term participation and commitment to the SNS. Long-term participation is specifically manifested through interactions with peers who are members of the same website and through interactivity such as content sharing and contribution. A number of quantitative studies have focused on motivations for user contribution in social …