Databases and Information Systems Commons^™

Gamification Of Education: A Review Of Literature, Fiona Fui-Hoon Nah, Qing Zeng, Venkata R. Telaprolu, Abhishek Padmanabhuni Ayyappa, Brenda Eschenbrenner

Research Collection School Of Computing and Information Systems

We synthesized the literature on gamification of education by conducting a review of the literature on gamification in the educational and learning context. Based on our review, we identified several game design elements that are used in education. These game design elements include points, levels/stages, badges, leaderboards, prizes, progress bars, storyline, and feedback. We provided examples from the literature to illustrate the application of gamification in the educational context.

On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In marketing and advertising, developing and managingbrands value represent the core activities performedby companies. Successful brands attract buyers andadopters, which in turn increase the companies’ value.Given a set of user-item adoption data, can we inferbrand effects from users adopting items? To answerthis question, we develop the Brand Item Topic Model(BITM) that incorporates users’ brand preferences inthe process of item adoption by the users. We evaluateour model using synthetic and two real world datasetsagainst baseline models which do not consider brand effects.The results show that BITM can determine userswho demonstrate brand preferences and predict itemadoptions more accurately.

On Efficient Reverse Skyline Query Processing, Yunjun Gao, Qing Liu, Baihua Zheng, Gang Chen

Research Collection School Of Computing and Information Systems

Given a D-dimensional data set P and a query point q, a reverse skyline query (RSQ) returns all the data objects in P whose dynamic skyline contains q. It is important for many real life applications such as business planning and environmental monitoring. Currently, the state-of-the-art algorithm for answering the RSQ is the reverse skyline using skyline approximations (RSSA) algorithm, which is based on the precomputed approximations of the skylines. Although RSSA has some desirable features, e.g., applicability to arbitrary data distributions and dimensions, it needs for multiple accesses of the same nodes, incurring redundant I/O and CPU costs. In …

Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

As the central notion in semi-supervised learning, smoothness is often realized on a graph representation of the data. In this paper, we study two complementary dimensions of smoothness: its pointwise nature and probabilistic modeling. While no existing graph-based work exploits them in conjunction, we encompass both in a novel framework of Probabilistic Graph-based Pointwise Smoothness (PGP), building upon two foundational models of data closeness and label coupling. This new form of smoothness axiomatizes a set of probability constraints, which ultimately enables class prediction. Theoretically, we provide an error and robustness analysis of PGP. Empirically, we conduct extensive experiments to show …

Hydrographic Surface Modeling Through A Raster Based Spline Creation Method, Julie G. Alexander

LSU New Orleans Theses and Dissertations

The United States Army Corp of Engineers relies on accurate and detailed surface models for various construction projects and preventative measures. To aid in these efforts, it is necessary to work for advancements in surface model creation. Current methods for model creation include Delaunay triangulation, raster grid interpolation, and Hydraulic Spline grid generation. While these methods produce adequate surface models, attempts for improved methods can still be made.

A method for raster based spline creation is presented as a variation of the Hydraulic Spline algorithm. By implementing Hydraulic Splines in raster data instead of vector data, the model creation process …

With Whom To Coordinate, Why And How In Ad-Hoc Social Media Communications During Crisis Response, Hemant Purohit, Shreyansh Bhatt, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach

Kno.e.sis Publications

During crises affected people, well-wishers, and observers join social media communities to discuss the event. They often share useful information relevant to response coordination, for example, specific resource needs. However, responders face the challenge of massive data overload and lack the time to monitor social media traffic for important information. Analysis shows that only a small number of event related conversations are actionable. Moreover, responders do not know which sources are trustworthy. To address these challenges, response teams may apply manual filtering methods, resulting in limited coverage and quality. We propose a framework and interface for extracting specific resource-related information …

Mining Contrast Subspaces, Lei Duan, Guanting Tang, Jian Pei, James Bailey, Guozhu Dong, Akiko Campbell, Changjie Tang

Kno.e.sis Publications

In this paper, we tackle a novel problem of mining contrast subspaces. Given a set of multidimensional objects in two classes C₊  and C₋ and a query object o, we want to find top-k subspaces S that maximize the ratio of likelihood of o in C₊  against that in C₋. We demonstrate that this problem has important applications, and at the same time, is very challenging. It even does not allow polynomial time approximation. We present CSMiner, a mining method with various pruning techniques. CSMiner is substantially faster than the baseline method. Our …

Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao

Research Collection School Of Computing and Information Systems

No abstract provided.

Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu

Research Collection School Of Computing and Information Systems

Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …

Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The wide spread use of smart phones has ushered in a wave of context-based advertising services that operate on pre-defined user events. A prime example is Location Based Advertising. What is missing though, is the ability to experiment with these services under varying event conditions with real users using their regular phones in real-world environments. Such experiments provide greater insight into user needs for and responsiveness towards context-based advertising applications. However, these event-driven experiments rely on data that arrive from sources such as mobile sensors which have inherent uncertainties associated with them. This effects the interpretation of the outcome of …

Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni

Research Collection School Of Computing and Information Systems

Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …

Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin

Research Collection School Of Computing and Information Systems

It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge …

On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

There is a growing interest in applying multiagent systems for smart-home environment supporting self-caring elderly. In this paper we investigate situations and conditions for coordination for such kind of system. We specify a high level architecture of it based on the notions of beliefs, desires, and intentions for both individual and group behavior of the agents including the human occupant's. The framework enables flexible coordinations among loosely-coupled heterogeneous agents that converse with the user. This work is conducted towards producing a coordination framework for agents and people in such a kind of smart-home environment as mentioned.

Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Detecting anomaly collections is an important task with many applications, including spam and fraud detection. In an anomaly collection, entities often operate in collusion and hold different agendas to normal entities. As a result, they usually manifest collective extreme traits, i.e., members of an anomaly collection are consistently clustered toward the top or bottom ranks on certain features. We therefore propose to detect these anomaly collections by extreme feature ranks. We introduce a novel anomaly definition called Extreme Rank Anomalous Collection or ERAC. We propose a new measure of anomalousness capturing collective extreme traits based on a statistical model. As …

Creating An Information Systems Security Culture Through An Integrated Model Of Employees Compliance, Mohammad I. Merhi

Theses and Dissertations - UTB/UTPA

Employees’ non-compliance with information systems security policies has been identified as a major threat to organizational data and information systems. This dissertation investigates the process underlying information systems security compliance in organizations with the focus on employees. The process model is complex, comprising many normative, attitudinal, psychological, environmental, and organizational factors. Therefore, the study of information security compliance requires a holistic assessment of all these factors. This dissertation seeks to achieve this objective by offering a comprehensive and integrated model of employee behavior especially focused towards information security compliance. The research framework is influenced by the Reciprocal Determinism Theory which …

Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang

Research Collection School Of Computing and Information Systems

Group exercise provides motivation to follow and maintain a healthy daily exercise schedule while enjoying beneficial encouragement and social support from friends and exercise partners. However, mobility and transportation issues frequently prevent seniors from engaging in group activities. To address this problem, we investigated the exercise needs of seniors and developed a prototype remote exercise system. Our system uses haptic feedback to simulate assistive pushing and pulling of limbs when exercising with a partner. We developed three distinct vibration metaphors -- constant push/pull, corrective feedback, and notification -- to convey engagement and connection between exercise partners. We conducted a preliminary …

An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components — users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user …

The Promises And Challenges Of Innovating Through Big Data And Analytics In Healthcare, Donald E. Wynn, Renée M. E. Pratt

MIS/OM/DS Faculty Publications

In this article, we present the promises and challenges of big data and analytics (BD&A) in healthcare, informed by our observations of and interviews with healthcare providers in the US and European Union (EU). We then provide a set of recommendations for capitalizing on the extraordinary innovation opportunities available through big data.

[Sabbatical Report], Huanjing Wang

Sabbatical Reports

My sabbatical leave was conducted during Spring semester 2014. The leave was successful because it strengthened my research in data mining and software engineering domains and resulted four full-paper publications in peer-reviewed international conferences and one journal paper (to be submitted to a peer-reviewed journal). The purpose of my sabbatical was to complete two main projects: (1) Investigate the stability and defect prediction model performance of feature selection techniques together on real-world software metrics data and (2) Design a novel, robust, and efficient metric selection method for imbalanced data.

Leveraging Social Media And Web Of Data For Crisis Response Coordination, Carlos Castillo, Fernando Diaz, Hemant Purohit

Kno.e.sis Publications

There is an ever increasing number of users in social media (1B+ Facebook users, 500M+ Twitter users) and ubiquitous mobile access (6B+ mobile phone subscribers) who share their observations and opinions. In addition, the Web of Data and existing knowledge bases keep on growing at a rapid pace. In this scenario, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a …