Databases and Information Systems Commons^™

[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.

Technological, Organizational, And Environmental Factors Affecting The Adoption Of Cloud Enterprise Resource Planning (Erp) Systems, John Njenga Kinuthia

Master's Theses and Doctoral Dissertations

The purpose of this study was to determine the differences between organizations that adopted Cloud Enterprise Resource Planning (Cloud ERP) systems and organizations that did not adopt Cloud ERP systems based on the Technological, Organizational, and Environmental (TOE) factors. Relevant technological factors were identified as relative advantage of Cloud ERP systems, compatibility of Cloud ERP systems, and security concern of Cloud ERP system environment. Organizational factors included top management support, organizational readiness, size of the organization, centralization, and formalization. External environment factors were identified as competitive pressure and vendor support.

A survey was developed using constructs from existing studies of …

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 …

Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth

Kno.e.sis Publications

Industry and researchers have identified numerous ways to monetize microblogs for personalization and recommendation. A common challenge across these different works is the identification of user interests. Although techniques have been developed to address this challenge, a flexible approach that spans multiple levels of granularity in user interests has not been forthcoming. In this work, we focus on exploiting hierarchical semantics of concepts to infer richer user interests expressed as a Hierarchical Interest Graph. To create such graphs, we utilize users' tweets to first ground potential user interests to structured background knowledge such as Wikipedia Category Graph. We then adapt …

Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen

Computer Science Faculty Publications

With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually …

Reliability Guided Resource Allocation For Large-Scale Supercomputing Systems, Shruti Umamaheshwaran

Open Access Theses

In high performance computing systems, parallel applications request a large number of resources for long time periods. In this scenario, if a resource fails during the application runtime, it would cause all applications using this resource to fail. The probability of application failure is tied to the inherent reliability of resources used by the application. Our investigation of high performance computing systems operating in the field has revealed a significant difference in the measured operational reliability of individual computing nodes. By adding awareness of the individual system nodes' reliability to the scheduler along with the predicted reliability needs of parallel …

A Farm Management Information System With Task-Specific, Collaborative Mobile Apps And Cloud Storage Services, Jonathan Tyler Welte

Open Access Theses

Modern production agriculture is beginning to advance beyond deterministic, scheduled operations between relatively few people to larger scale, information-driven efficiency in order to respond to the challenges of field variability and meet the needs of a growing population. Since no two farms are the same with respect to information and management structure, a specialized farm management information system (FMIS) which is tailored to the realities on the ground of individual farms is likely to be more effective than generalized FMIS available today.

This thesis presents the design of a FMIS using proven user-centered design principles. This approach resulted in the …

A Sandbox Development For Demonstrating Bom Transmission In A Plm And Erp Integrated System, Zhen Zeng

Open Access Theses

Integrating Product Lifecycle Management (PLM) and Enterprise Resource Planning (ERP) in a company is important. Currently, many companies have difficulties on integrating PLM and ERP systems. This study developed a prototype (sandbox) of PLM and ERP integrated system for demonstrating BOM transmission in a PLM and ERP integrated system, describing key aspects of system integration and BOM transmission. This sandbox will facilitate users' knowledge on how to process transactions in a PLM and ERP integrated system. The BOM accuracy was examined by comparing BOM data in PLM system to BOM data in ERP system after implementing engineering changes. This study …

A Computer-Based Approach For Identifying Student Conceptual Change, Junchao Yan

Open Access Theses

Misconceptions are commonly encountered in many areas of science and engineering where a to-be-learned concept conflicts with prior knowledge. Conceptual change is an approach for identifying and repairing the misconceptions. One of the ways to promote student conceptual change is providing students with ontological schema training. However, assessment of conceptual change relies on qualitative analysis of student responses. With the exponential growth of qualitative data in the form of graphical representations or written responses, the process of data analysis relying on human experts has become time-consuming and costly. This study took the advantages of natural language processing and machine learning …

Community Discovery In Social Networks Via Heterogeneous Link Association And Fusion, Lei Meng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a prior, do not address the weighting problem for fusing heterogeneous types of links and have a heavy computational cost. In this paper, we explore the feasibility of a newly proposed heterogeneous data clustering algorithm, called Generalized Heterogeneous Fusion Adaptive Resonance Theory (GHF-ART), for discovering communities in heterogeneous social networks. Different from existing algorithms, GHF-ART performs real-time matching of patterns and one-pass learning which guarantee its low computational cost. With a vigilance parameter to …

On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …

Latent Factor Transition For Dynamic Collaborative Filtering, Chengyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

No abstract provided.

Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn

Research Collection School Of Computing and Information Systems

With the widespread adoption of the Web, many companies and organizations have established websites that provide information and support online transactions (e.g., buying products or viewing content). Unfortunately, users have limited attention to spare for interacting with online sites. Hence, it is of utmost importance to design sites that attract user attention and effectively guide users to the product or content items they like. Thus, we propose a novel and scalable experimentation approach to evaluate the effectiveness of online site designs. Our case study focuses on the effects of an authority message on visitors' browsing behavior on workshop and seminar …

On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo

Research Collection School Of Computing and Information Systems

Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …

Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

See https://ink.library.smu.edu.sg/sis_research/2924/. Distance metric learning (DML) is an important technique to improve similarity search in content-based image retrieval. Despite being studied extensively, most existing DML approaches typically adopt a single-modal learning framework that learns the distance metric on either a single feature type or a combined feature space where multiple types of features are simply concatenated. Such single-modal DML methods suffer from some critical limitations: (i) some type of features may significantly dominate the others in the DML task due to diverse feature representations; and (ii) learning a distance metric on the combined high-dimensional feature space can be extremely …

Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh

Research Collection School Of Computing and Information Systems

Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, …

Adoption Of Mobile Information Services: An Empirical Study, S. Gao, J. Krogstie, Keng Siau

Research Collection School Of Computing and Information Systems

This study investigates the adoption of mobile information services at a Norwegian university. By expanding the Technology Acceptance Model (TAM), a new research model, known as the mobile services acceptance model (MSAM), is proposed. Based on the research model, seven research hypotheses are presented. The proposed research model and research hypotheses were empirically tested using data collected from a survey of users of a mobile service, extended Mobile Student Information Systems (eMSIS), at a Norwegian university. The findings indicate that the fitness of the research model is good. Support was also found for the seven research hypotheses. Among the factors, …

Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang

Research Collection School Of Computing and Information Systems

Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …

Laser: A Living Analytics Experimentation System For Large-Scale Online Controlled Experiments, Kwan-Hui Lim, Ee Peng Lim, Achananuparp Palakorn, Adrian Vu, Agus Trisnajaya Kwee, Feida Zhu

Research Collection School Of Computing and Information Systems

Tracking user browsing data and measuring the effectiveness of website design and web services are important to businesses that want to attract the consumers today who spend much more time online than before. Instead of using randomized controlled experiments, the existing approach simply tracks user browsing behaviors before and after a change is made to website design or web services, and evaluate the differences. To address the effects caused by hidden factors (e.g. promotion activities on the website) and to give fair comparison of different website designs, we propose the LASER system, a unified experimentation platform that enables randomized online …

A Trust-Aware System For Personalized User Recommendations In Social Networks, Magdalini Eirinaki, Malamati Louta, Iraklis Varlamis

Faculty Publications

Social network analysis has recently gained a lot of interest because of the advent and the increasing popularity of social media, such as blogs, social networking applications, microblogging, or customer review sites. In this environment, trust is becoming an essential quality among user interactions and the recommendation for useful content and trustful users is crucial for all the members of the network. In this paper, we introduce a framework for handling trust in social networks, which is based on a reputation mechanism that captures the implicit and explicit connections between the network members, analyzes the semantics and dynamics of these …

Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar

Engineering Management & Systems Engineering Theses & Dissertations

The delivery of health care services has been impacted by advances in Knowledge Management Information Systems (KMIS) and Information Technology (IT). The literature reveals that Electronic Health Records Systems (EHRs) are a comprehensive KMIS. There is a wide recognition in the body of knowledge that demonstrates the potential of EHRs to transform all aspects of health care services and, in consequence, the performance of Health Care Delivery Organizations (HCDO). Authors of published research also agree that there is a need for more empirical contributions that demonstrate the impact of EHRs upon HCDO. It is argued that in most cases, studies …

Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user's past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We …

Just-For-Me: An Adaptive Personalization System For Location-Aware Social Music Recommendation, Zhiyong Cheng, Jialie Shen

Research Collection School Of Computing and Information Systems

The fast growth of online communities and increasing popularity of internet-accessing smart devices have significantly changed the way people consume and share music. As an emerging technology to facilitate effective music retrieval on the move, intelligent recommendation has been recently received great attentions in recent years. While a large amount of efforts have been invested in the field, the technology is still in its infancy. One of the major reasons for this stagnation is due to inability of the existing approaches to comprehensively take multiple kinds of contextual information into account. In the paper, we present a novel recommender system …

Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui

Research Collection School Of Computing and Information Systems

In this demonstration, we demonstrate a mobile-based celebrity video browsing system called CeleBrowser. Using this system, users can interactively switch among four views: people-centric, timeline-centric, month-centric and topic-centric, for browsing celebrity-related hot videos. A peculiarity of the demonstration is to highlight the advantage of multiperspective information organization and presentation in engaging users for exploratory browsing of large number of Web videos on a device with small screen. Technology-wise the demonstration shows how query logs collected for six months from two vertical search engines are leveraged for mining hot events and videos of celebrities.

Semantic Privacy Policies For Service Description And Discovery In Service-Oriented Architecture, Diego Z. Garcia, Miriam A M Capretz, M. Beatriz F. Toledo

Electrical and Computer Engineering Publications

Privacy preservation in Service-Oriented Architecture (SOA) is an open problem. This paper focuses on the areas of service description and discovery. The problems in these areas are that currently it is not possible to describe how a service provider deals with information received from a service consumer as well as discover a service that satisfies the privacy preferences of a consumer. There is currently no framework which offers a solution that supports a rich description of privacy policies and their integration in the process of service discovery. Thus, the main goal of this paper is to propose a privacy preservation …

Analysis Of A Scholarly Social Networking Site: The Case Of The Dormant User, Meg Murray

Faculty Articles

Many scholarly social networking sites targeting an audience of academicians and researchers have appeared on the Internet in recent years. Their vision is to change the way researchers connect, share and collaborate to solve real world problems. Despite the hype, however, their impact on higher education is unclear. Studies exist that address the benefits of these sites, but studies that investigate the implications of how scholarly social networking systems vet information, including data related to user profiles and uploaded content, is nonexistent. This paper chronicles the system management of user information for an inactive user of a scholarly social networking …

Algorithmic Accountability, Tamara Kneese

Media Studies

Accountability is fundamentally about checks and balances to power. In theory, both government and corporations are kept accountable through social, economic, and political mechanisms. Journalism and public advocates serve as an additional tool to hold powerful institutions and individuals accountable. But in a world of data and algorithms, accountability is often murky. Beyond questions about whether the market is sufficient or governmental regulation is necessary, how should algorithms be held accountable? For example what is the role of the fourth estate in holding data-oriented practices accountable?

Data Supply Chains, Tamara Kneese

Media Studies

As data moves between actors and organizations, what emerges is a data supply chain. Unlike manufacturing supply chains, transferred data is often duplicated in the process, challenging the essence of ownership. What does ethical data labor look like? How are the various stakeholders held accountable for being good data guardians? What does clean data transfer look like? What kinds of best practices can business and government put into place? What upstream rights to data providers have over downstream commercialization of their data?

Predicting Human Behavior, Tamara Kneese

Media Studies

Countless highly accurate predictions can be made from trace data, with varying degrees of personal or societal consequence (e.g., search engines predict hospital admission, gaming companies can predict compulsive gambling problems, government agencies predict criminal activity). Predicting human behavior can be both hugely beneficial and deeply problematic depending on the context. What kinds of predictive privacy harms are emerging? And what are the implications for systems of oversight and due process protections? For example, what are the implications for employment, health care and policing when predictive models are involved? How should varied organizations address what they can predict?

Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo

Research Collection School Of Computing and Information Systems

Auto face annotation, which aims to detect human faces from a facial image and assign them proper human names, is a fundamental research problem and beneficial to many real-world applications. In this work, we address this problem by investigating a retrieval-based annotation scheme of mining massive web facial images that are freely available over the Internet. In particular, given a facial image, we first retrieve the top n similar instances from a large-scale web facial image database using content-based image retrieval techniques, and then use their labels for auto annotation. Such a scheme has two major challenges: 1) how to …