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.

Learning Euclidean-To-Riemannian Metric For Point-To-Set Classification, Zhiwu Huang, R. Wang, S. Shan, X. Chen

Research Collection School Of Computing and Information Systems

In this paper, we focus on the problem of point-to-set classification, where single points are matched against sets of correlated points. Since the points commonly lie in Euclidean space while the sets are typically modeled as elements on Riemannian manifold, they can be treated as Euclidean points and Riemannian points respectively. To learn a metric between the heterogeneous points, we propose a novel Euclidean-to-Riemannian metric learning framework. Specifically, by exploiting typical Riemannian metrics, the Riemannian manifold is first embedded into a high dimensional Hilbert space to reduce the gaps between the heterogeneous spaces and meanwhile respect the Riemannian geometry of …

Flow In Gaming: Literature Synthesis And Framework Development, Fiona Fui-Hoon Nah, B. Eschenbrenner, Q. Zeng, V. Telaprolu, S. Sepehr

Research Collection School Of Computing and Information Systems

Flow, a state of optimal experience where one is completely absorbed and immersed in an activity, is an important phenomenon for studying and designing games. In this article, we synthesise the literature on flow in gaming to discern existing research streams, and identify the antecedents, dimensions, and outcomes of flow which are then integrated into a framework. Based on the findings, we provide suggestions for game design elements that practitioners, such as game designers, may find useful for creating or inducing flow in gaming. We also discuss implications for research and practice as well as provide suggestions for future research.

Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu

Research Collection School Of Computing and Information Systems

Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy …

Air Indexing For On-Demand Xml Data Broadcast, Weiwei Sun, Rongrui Qin, Jinjin Wu, Baihua Zheng

Research Collection School Of Computing and Information Systems

XML data broadcast is an efficient way to disseminate semi-structured information in wireless mobile environments. In this paper, we propose a novel two-tier index structure to facilitate the access of XML document in an on-demand broadcast system. It provides the clients with an overall image of all the XML documents available at the server side and hence enables the clients to locate complete result sets accordingly. A pruning strategy is developed to cut down the index size and a two-tier structure is proposed to further remove any redundant information. In addition, two index distribution strategies, namely naive distribution and partial …

Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we argue for expanded research into an area called Socio-Physical Analytics, that focuses on combining the behavioral insight gained from mobile-sensing based monitoring of physical behavior with the inter-personal relationships and preferences deduced from online social networks. We highlight some of the research challenges in combining these heterogeneous data sources and then describe some examples of our ongoing work (based on real-world data being collected at SMU) that illustrate two aspects of socio-physical analytics: (a) how additional demographic and online analytics based attributes can potentially provide better insights into the preferences and behaviors of individuals or groups …

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.

Hydra: Large-Scale Social Identity Linkage Via Heterogeneous Behavior Modeling, Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

We study the problem of large-scale social identity linkage across different social media platforms, which is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. This paper proposes HYDRA, a solution framework which consists of three key steps: (I) modeling heterogeneous behavior by long-term behavior distribution analysis and multi-resolution temporal information matching; (II) constructing structural consistency graph to measure the high-order structure consistency on users' core social structures across different platforms; and (III) learning the mapping function by multi-objective optimization composed of both the supervised learning on pair-wise ID …

An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu

Research Collection School Of Computing and Information Systems

Spatial queries such as range query and kNN query in road networks have received a growing number of attention in real life. Considering the large population of the users and the high overhead of network distance computation, it is extremely important to guarantee the efficiency and scalability of query processing. Motivated by the scalable and secure properties of wireless broadcast model, this paper presents an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast. The main idea is to partition the road network into a number of regions and then …

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 …

Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

A top-k query shortlists the k records in a dataset that best match the user's preferences. To indicate her preferences, the user typically determines a numeric weight for each data dimension (i.e., attribute). We refer to these weights collectively as the query vector. Based on this vector, each data record is implicitly mapped to a score value (via a weighted sum function). The records with the k largest scores are reported as the result. In this paper we propose an auxiliary feature to standard top-k query processing. Specifically, we compute the maximal locus within which the query vector incurs no …

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 …

Joint Virtual Machine And Bandwidth Allocation In Software Defined Network (Sdn) And Cloud Computing Environments, Jonathan David Chase, Rakpong Kaewpuang, Wen Yonggang, Dusit Niyato

Research Collection School Of Computing and Information Systems

Cloud computing provides users with great flexibility when provisioning resources, with cloud providers offering a choice of reservation and on-demand purchasing options. Reservation plans offer cheaper prices, but must be chosen in advance, and therefore must be appropriate to users' requirements. If demand is uncertain, the reservation plan may not be sufficient and on-demand resources have to be provisioned. Previous work focused on optimally placing virtual machines with cloud providers to minimize total cost. However, many applications require large amounts of network bandwidth. Therefore, considering only virtual machines offers an incomplete view of the system. Exploiting recent developments in software …

Information Systems User Competency: A Conceptual Foundation, B. Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Research has identified a variety of factors that influence people’s intentions to use IS and their degree of IS use. However, what has not been well understood are the characteristics of competent IS users who are proficient in using IS and are able to achieve quality IS usage. Considering that improving IS users’ abilities to more efficiently and effectively use IS has always been and remains a challenge, research that provides a comprehensive view of the characteristics associated with competent IS users is warranted. This paper addresses this research question by proposing a conceptual foundation for IS user competency. Based …

Institutional Boundaries And Trust Of Virtual Teams In Collaborative Design: An Experimental Study In A Virtual World Environment, Shu Z. Schiller, Brian Mennecke, Fiona Fui-Hoon Nah, Andy Luse

Research Collection School Of Computing and Information Systems

Members of virtual teams often collaborate within and across institutional boundaries. This research investigates the effects of boundary spanning conditions on the development of team trust and team satisfaction. Two hundred and eighty-two participants carried out a collaborative design task over several weeks in a virtual world, Second Life. Multigroup structural equation modeling was used to examine our research model, which compares individual level measurement between two boundary spanning team conditions. The results indicate that trusting beliefs have a positive impact on team trust, which in turn, influences team satisfaction. Further, we found that, compared to cross-boundary teams, within-boundary teams …

Defy: A Deniable File System For Flash Memory, Timothy M. Peters

Master's Theses

While solutions for file system encryption can prevent an adversary from determining the contents of files, in situations where a user wishes to hide even the existence of data, encryption alone is not enough. Indeed, encryption may draw attention to those files, as they most likely contain information the user wishes to keep secret, and coercion can be a very strong motivator for the owner of an encrypted file system to surrender their secret key.

Herein we present DEFY, a deniable file system designed to work exclusively with solid-state drives, particularly those found in mobile devices. Solid-state drives have unique …

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 …

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 …