Digital Commons Network^™

Toward More Composable Software-Security Policies: Tools And Techniques, Daniel Lomsak

USF Tampa Graduate Theses and Dissertations

Complex software-security policies are dicult to specify, understand, and update. The

same is true for complex software in general, but while many tools and techniques exist

for decomposing complex general software into simpler reusable modules (packages, classes,

functions, aspects, etc.), few tools exist for decomposing complex security policies into simpler

reusable modules. The tools that do exist for modularizing policies either encapsulate

entire policies as atomic modules that cannot be decomposed or allow ne-grained policy

modularization but require expertise to use correctly.

This dissertation presents a policy-composition tool called PoliSeer [27, 26] and the

PoCo policy-composition software-security language. PoliSeer is …

Playing In Trelis Weyr: Investigating Collaborative Practices In A Dragons Of Pern Role-Play-Game Forum, Kathleen Marie Alley

USF Tampa Graduate Theses and Dissertations

This descriptive case study examined adolescents' and emerging adults' literate and social practices within the context of a role-play-game (RPG) forum, investigating the ways participants read and collaboratively composed within this space. As a researcher, I was interested in how this space functioned and how the interactions between members impacted their composing processes, with particular attention to the role of online spaces and popular culture in adolescents' motivation to engage in this forum. This study was guided by three research questions: (1) In what ways is Trelis Weyr, an RPG forum, organized as a virtual environment?; (2) In what ways, …

Lexis In Chemical Engineering Discourse: Analyzing Style In Chemical Engineering Research Articles Through A Rhetorical Lens, David Lamar Young

Masters Theses

"This study examines the style of chemical engineering research articles to discover stylistic trends that may be applicable to authors looking to publish their own research. Rhetorical stylistic analysis was used as a research method to allow for thorough analysis of all articles in the sample. Ten research articles from the two prominent chemical engineering journals were chosen using specific criteria to constitute a sample of articles that could most accurately represent the population of chemical engineering research articles. Each article was then analyzed line by line to identify markers of chemical engineering research article style, including the following: ▬Use …

Polarization And Opinion Analysis In An Online Argumentation System For Collaborative Decision Support, Ravi Santosh Arvapally

Doctoral Dissertations

"Argumentation is an important process in a collaborative decision making environment. Argumentation from a large number of stakeholders often produces a large argumentation tree. It is challenging to comprehend such an argumentation tree without intelligent analysis tools. Also, limited decision support is provided for its analysis by the existing argumentation systems. In an argumentation process, stakeholders tend to polarize on their opinions, and form polarization groups. Each group is usually led by a group leader. Polarization groups often overlap and a stakeholder is a member of multiple polarization groups. Identifying polarization groups and quantifying a stakeholder's degree of membership in …

Accuracy And Timeliness In Ml Based Activity Recognition, Robert J. Ross, John D. Kelleher

Conference papers

While recent Machine Learning (ML) based techniques for activity recognition show great promise, there remain a number of questions with respect to the relative merits of these techniques. To provide a better understanding of the relative strengths of contemporary Activity Recognition methods, in this paper we present a comparative analysis of Hidden Markov Model, Bayesian, and Support Vector Machine based human activity recognition models. The study builds on both pre-existing and newly annotated data which includes interleaved activities. Results demonstrate that while Support Vector Machine based techniques perform well for all data sets considered, simple representations of sensor histories regularly …

A Comparative Study Of The Effect Of Sensor Noise On Activity Recognition Models, Robert J. Ross, John D. Kelleher

Conference papers

To provide a better understanding of the relative strengths of Machine Learning based Activity Recognition methods, in this paper we present a comparative analysis of the robustness of three popular methods with respect to sensor noise. Specifically we evaluate the robustness of Naive Bayes classifier, Support Vector Machine, and Random Forest based activity recognition models in three cases which span sensor errors from dead to poorly calibrated sensors. Test data is partially synthesized from a recently annotated activity recognition corpus which includes both interleaved activities and a range of both temporally long and short activities. Results demonstrate that the relative …

Toward Digitizing The Human Experience : A New Resource For Natural Language Processing, Jerry Scott Weltman

LSU Doctoral Dissertations

A long-standing goal of Artificial Intelligence is to program computers that understand natural language. A basic obstacle is that computers lack the common sense that even small children acquire simply by experiencing life, and no one has devised a way to program this experience into a computer. This dissertation presents a methodology and proof-of-concept software system that enables non-experts, with some training, to create simple experiences. For the purposes of this dissertation, an experience is a series of time-ordered comic frames, annotated with the changing intentional and physical states of the characters and objects in each frame. Each frame represents …

Business Intelligence And Analytics: Research Directions, Ee Peng Lim, Hsinchun Chen, Guoqing Chen

Research Collection School Of Computing and Information Systems

Business intelligence and analytics (BIA) is about the development of technologies, systems, practices, and applications to analyze critical business data so as to gain new insights about business and markets. The new insights can be used for improving products and services, achieving better operational efficiency, and fostering customer relationships. In this article, we will categorize BIA research activities into three broad research directions: (a) big data analytics, (b) text analytics, and (c) network analytics. The article aims to review the state-of-the-art techniques and models and to summarize their use in BIA applications. For each research direction, we will also determine …

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 …

Fuzzy-Excom Software Project Risk Assessment, Luiz Fernando Capretz, Ekananta Manalif, Ali Bou Nassif, Danny Ho

Electrical and Computer Engineering Publications

A software development project can be considered to be risky project due to the uncertainty of the information (customer requirements), the complexity of the process, and the intangible nature of the product. Under these conditions, risk management in software development projects is mandatory, but often it is difficult and expensive to implement.

Expert COCOMO is an efficient approach to software project risk management, which leverages existing knowledge and expertise from previous effort estimation activities to assess the risk in a new software project. However, the original method has a limitation because it cannot effectively deal with imprecise and uncertain inputs …

An Affordance-Based Framework For Human Computation And Human-Computer Collaboration, R. Jordan Crouser, Remco Chang

Computer Science: Faculty Publications

Visual Analytics is “the science of analytical reasoning facilitated by visual interactive interfaces” [70]. The goal of this field is to develop tools and methodologies for approaching problems whose size and complexity render them intractable without the close coupling of both human and machine analysis. Researchers have explored this coupling in many venues: VAST, Vis, InfoVis, CHI, KDD, IUI, and more. While there have been myriad promising examples of human-computer collaboration, there exists no common language for comparing systems or describing the benefits afforded by designing for such collaboration. We argue that this area would benefit significantly from consensus about …

Effective Computer Programming Instruction For Pre-University Albanian Students, Robert Mccloud, Ardiana Sula

School of Computer Science & Engineering Faculty Publications

The relationship between pre-university students and technology is frequently overrated. While we receive glowing reports about how young people are knowledgeable about computers, the truth is that their knowledge is typically about computer content and the manipulation of applications. Young students too often treat the actual programming and understanding of computers as a sort of magical mystery.

In this paper we look at a new Albanian initiative to identify and nurture the most talented of our pre-university students. In particular we look at contributions to the goal of making Albanians the most talented programmers in this area of Europe.

The …

Cross-Lingual Identification Of Ambiguous Discourse Connectives For Resource-Poor Language, Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The lack of annotated corpora brings limitations in research of discourse classification for many languages. In this paper, we present the first effort towards recognizing ambiguities of discourse connectives, which is fundamental to discourse classification for resource-poor language such as Chinese. A language independent framework is proposed utilizing bilingual dictionaries, Penn Discourse Treebank and parallel data between English and Chinese. We start from translating the English connectives to Chinese using a bi-lingual dictionary. Then, the ambiguities in terms of senses a connective may signal are estimated based on the ambiguities of English connectives and word alignment information. Finally, the ambiguity …

Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just …

Finding Thoughtful Comments From Social Media, Gottipati Swapna, Jing Jiang

Research Collection School Of Computing and Information Systems

Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that provide some reasoning is highly valuable in understanding the user’s opinion particularly in sociopolitical opinion mining and aids policy makers, social organizations or government sectors in decision making. In this paper we study the problem of detecting thoughtful comments. We empirically study various textual features, discourse relations and relevance features to predict thoughtful comments. We use logistic regression model and test on the datasets related to sociopolitical content. We found …

Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang

Research Collection School Of Computing and Information Systems

With the growing popularity of opinion-rich resources on the Web, new opportunities and challenges arise and aid people in actively using such information to understand the opinions of others. Opinion mining process currently focuses on extracting the sentiments of the users on products, social, political and economical issues. In many instances, users not only express their sentiments but also contribute their ideas, requests and suggestions through comments. Such comments are useful for domain experts and are referred to as actionable content. Extracting actionable knowledge from online social media has attracted a growing interest from both academia and the industry. We …

Domain Independent Ordering Of Narrative Events, Lucian T. Silcox

Theses and Dissertations - UTB/UTPA

A key aspect towards gaining a rich understanding of a text is the ability to order the events that occur in the narrative. For us, as readers, this is a simple task, accomplished without effort by recognizing subtle contextual and linguistic clues. For natural language systems, however, the task is considerably more difficult. It is the intent of this research to automate the process of annotating and ordering temporal events in a narrative, and to measure the success of techniques trained on news articles when applied to less sequentially-structured texts. We build on the earlier work of Mani et al …

Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram, Qianru Sun, Hong Liu

Research Collection School Of Computing and Information Systems

Classifying realistic human actions in video remains challenging for existing intro-variability and inter-ambiguity in action classes. Recently, Spatial-Temporal Interest Point (STIP) based local features have shown great promise in complex action analysis. However, these methods have the limitation that they typically focus on Bag-of-Words (BoW) algorithm, which can hardly discriminate actions’ ambiguity due to ignoring of spatial-temporal occurrence relations of visual words. In this paper, we propose a new model to capture this contextual relationship in terms of pairwise features’ co-occurrence. Normalized Google-Like Distance (NGLD) is proposed to numerically measuring this co-occurrence, due to its effectiveness in semantic correlation analysis. …

Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish

Research Collection School Of Computing and Information Systems

Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by …

Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth

Kno.e.sis Publications

We present iExplore, a Semantic Web based application that helps biomedical researchers study and explore biomedical knowledge interactively. iExplore uses the Biomedical Knowledge Repository (BKR), which integrates knowledge from various sources ranging from information extracted from biomedical literature (from PubMed) to many structured vocabularies in the Unified Medical Language System (UMLS). The current version of BKR provides a unified provenance representation for 12 million semantic predications (triples with a predicate connecting a subject and an object) derived from 87 vocabulary families in the UMLS and 14 million predications extracted from 21 million PubMed abstracts. To engage the domain experts in …

Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin

Research Collection School Of Computing and Information Systems

This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …

Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou

Research Collection School Of Computing and Information Systems

Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in SinaWeibo. Multimedia contents …

Building Semantic Corpus From Wordnet, Lubomir Stanchev

Computer Science and Software Engineering

We propose a novel methodology for extracting semantic similarity knowledge from semi-structured sources, such as WordNet. Unlike existing approaches that only explore the structured information (e.g., the hypernym relationship in WordNet), we present a framework that allows us to utilize all available information, including natural language descriptions. Our approach constructs a semantic corpus. It is represented using a graph that models the relationship between phrases using numbers. The data in the semantic corpus can be used to measure the similarity between phrases, the similarity between documents, or to perform a semantic search in a set of documents that uses the …

Stealthy Plaintext, Naidele Katrumane Manjunath

Master's Projects

Correspondence through email has become a very significant way of communication at workplaces. Information of most kinds such as text, video and audio can be shared through email, the most common being text. With confidential data being easily sharable through this method most companies monitor the emails, thus invading the privacy of employees. To avoid secret information from being disclosed it can be encrypted. Encryption hides the data effectively but this makes the data look important and hence prone to attacks to decrypt the information. It also makes it obvious that there is secret information being transferred. The most effective …

Extraction Of Semantics From Primitive Concepts, Chak Li

Master's Projects

bstract Due to the need to organize a vast amount of documents available in the Internet, the automated semantic extraction representing webpages has become a popular research topic in both industry and academia. The purpose of this project is to introduce a new method to process documents to extract the original contextual representations and yet to extend additional and connect similar representations based on the semantics underneath the extracted representations in an automatic fashion. Among the purposed steps, the core of this project is to tackle the difficulty to construct a mechanism in which machines can computationally understand the lexical …

Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Defects are prevalent in software systems. In order to understand defects better, industry practitioners often categorize bugs into various types. One common kind of categorization is the IBM’s Orthogonal Defect Classification (ODC). ODC proposes various orthogonal classification of defects based on much information about the defects, such as the symptoms and semantics of the defects, the root cause analysis of the defects, and many more. With these category labels, developers can better perform post-mortem analysis to find out what the common characteristics of the defects that plague a particular software project are. Albeit the benefits of having these categories, for …

Handling Interpretation And Representation In Multilingual Research: A Meta-Study Of Pragmatic Issues Resulting From The Use Of Multiple Languages In A Qualitative Information Systems Research Work, Ilse Baumgartner

Research Collection School Of Computing and Information Systems

Although the number of multilingual qualitative research studies appears to be growing, investigations concerned with methodological issues arising from the use of several languages within a single research are still very scarce. Most of these seem to deal exclusively with issues related to the use of interpreters and translators in qualitative research (e.g., Temple & Edwards, 2002; Temple, Edwards & Alexander, 2006; Edwards, 1998; Temple & Young 2004). Methodological investigations going beyond pure translation dilemmas in qualitative research are, however, almost non-existent. The reason for this seems to be simple: the situation where the researcher possesses mother-tongue fluency in all …

In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as …

Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Sufficient training examples are essential for effective learning of semantic visual concepts. In practice, however, acquiring noise-free training examples has always been expensive. Recently the rapid popularization of social media websites, such as Flickr, has made it possible to collect training exemplars without human assistance. This paper proposes a novel and efficient approach to collect training samples from the noisily tagged Web images for visual concept learning, where we try to maximize two important criteria, relevancy and coverage, of the automatically generated training sets. For the former, a simple method named semantic field is introduced to handle the imprecise and …

Message From General Chair And Program Co-Chairs [Of Icec '12, 14th Annual International Conference On Electronic Commerce, Held In Singapore, 7-8 August 2012], Robert J. Kauffman, Martin Bichler, Hoong Chuin Lau, Christopher Yang, Yinping Yang

Research Collection School Of Computing and Information Systems

Singapore, a major hub in the Asia Pacific region well known for its multi-racial and multicultural society, is proud to host the 14th International Conference on Electronic Commerce. Singapore Management University (SMU), the School of Information Systems (SIS) and the Living Analytics Research Center (LARC) are also delighted to be able to support the delivery of this event.