Databases and Information Systems Commons^™

Introduction To Gis Using Open Source Software, 8th Ed, Frank Donnelly

Open Educational Resources

This tutorial was created to accompany the GIS Practicum, a day-long workshop offered by the Newman Library at Baruch College CUNY that introduces participants to geographic information systems (GIS) using the open source software QGIS. The practicum introduces GIS as a concept for envisioning information and as a tool for conducting geographic analyses and creating maps. Participants learn how to navigate a GIS interface, how to prepare layers and conduct a basic geographic analysis, and how to create thematic maps. This tutorial was written using QGIS version 2.18 "Las Palmas", a cross-platform (Windows, Mac, Linux) desktop GIS software package.

Essays On Crowdfunding: Exploring The Funding And Post-Funding Phases And Outcomes, Onochie Fan-Osuala

USF Tampa Graduate Theses and Dissertations

In the recent years, crowdfunding (a phenomenon where individuals collectively contribute money to back different goals and projects through the internet) has been gaining a lot of attention especially for its socio-economic impact. This dissertation explores this phenomenon in three distinct but related essays. The first essay explores the nature and dynamics of backers’ contributions and uses the insights generated to develop a forecasting model that can predict crowdfunding campaign outcomes. The second essay investigates how creators’ crowdfunding campaign design decisions impact their funding and post-funding outcomes. Interestingly, the essay highlights that certain crowdfunding campaign design decisions have differential effects …

Detecting User Demographics In Twitter To Inform Health Trends In Social Media, Christopher R. Markson

Dissertations

The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health conditions thanks to the diversity and abundance of online user-generated information (UGHI) relating to healthcare and well-being. However, users on social media and social networking sites often do not supply their complete demographic information, which greatly undermines the value of the aforementioned information for health 2.0 research, e.g., for discerning disparities across population groups in certain health conditions. To recover the missing user demographic information, existing methods observe a limited scope of user behaviors, such as …

Data Insertion In Bitcoin's Blockchain, Andrew Sward, Vecna Op_0, Forrest Stonedahl

Computer Science: Faculty Scholarship & Creative Works

This paper provides the first comprehensive survey of methods for inserting arbitrary data into Bitcoin's blockchain. Historical methods of data insertion are described, along with lesser-known techniques that are optimized for efficiency. Insertion methods are compared on the basis of efficiency, cost, convenience of data reconstruction, permanence, and potentially negative impact on the Bitcoin ecosystem.

Mining Diverse Consumer Preferences For Bundling And Recommendation, Ha Loc Do

Dissertations and Theses Collection

That consumers share similar tastes on some products does not guarantee their agreement on other products. Therefore, both similarity and dierence should be taken into account for a more rounded view on consumer preferences. This manuscript focuses on mining this diversity of consumer preferences from two perspectives, namely 1) between consumers and 2) between products. Diversity of preferences between consumers is studied in the context of recommendation systems. In some preference models, measuring similarities in preferences between two consumers plays the key role. These approaches assume two consumers would share certain degree of similarity on any products, ignoring the fact …

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Kno.e.sis Publications

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the …

Ehealthportal: A Social Support Hub For The Active Living Of The Elderly, Di Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The absolute and relative increases in the number of elderly are evident worldwide, from the most developed countries to the lowest-income regions. The fast demographic transition poses great challenges to the healthcare system and introduces a significant burden to the elderly and their family. To meet the unprecedented challenges of global aging, various aging-in-place (AIP) solutions have been proposed to enable the elderly to live in their own home and community safely, independently and comfortably. Elderly need support in various aspects, such as physical, cognitive, emotional, and social, in their daily life. However, most existing AIP solutions provide support in …

Effect Of Timing And Source Of Online Product Recommendations: An Eye-Tracking Study, Yan Shi, Qing Zeng, Fiona Fui-Hoon Nah, Chuan-Hoo Tan, Choon Ling Sia, Keng Siau, Jiaqi Yan

Research Collection School Of Computing and Information Systems

Online retail business has become an emerging market for almost all business owners. Online recommender systems provide better service to consumers during their decision making processes. In this study, a controlled lab experiment was conducted to assess the effect of recommendation timing (early, mid, and late) and recommendation source (expert reviews vs. consumer reviews) on online consumers’ interest and attention. Eye-tracking data was extracted from the experiment and analyzed. The results suggest that consumers show more interest in recommendation based on consumer reviews than expert reviews. Earlier recommendations do not receive greater attention than later recommendations.

Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam

School of Computing: Dissertations, Theses, and Student Research

Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …

How To Enable Future Faster Payments? An Evaluation Of A Hybrid Payments Settlement Mechanism, Zhiling Guo, Yuanzhi Huang

Research Collection School Of Computing and Information Systems

In the era of Fintech innovation and e-commerce, faster settlement of massive retail transactions is crucial for business growth and financial system stability. However, speeding up payments settlement can create periodic liquidity shortfalls to banks which would incur high cost of funds in the settlement process. We propose a new hybrid settlement mechanism design that integrates features of real-time gross settlement, deferred net settlement, and central queue management structure. The hybrid mechanism is managed by an intermediary and is particularly suitable to settle large volume of small-value retail payments. We evaluate the mechanism using computer experiments and simulation. We find …

The Role Of Different Tie Strength In Disseminating Different Topics On A Microblog, Felicia Natali, Kathleen M. Carley, Feida Zhu, Binxuan Huang

Research Collection School Of Computing and Information Systems

The study of information flow typically does not distinguish the choices of tie strength on which the information flows. All receivers of the information are assumed to have the same potential to pass on the information. Modifying the SEIZ (susceptible, exposed, infected, skeptic) model, we discover that people choose to retweet strong or weak ties based on the topic. We made two modifications in the model. In the first modification (Model I), we assume that the contact rates of agents in different compartment and the probability of an agent transitioning from one compartment to another are different for strong ties …

Incentivizing The Use Of Bike Trailers For Dynamic Repositioning In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Bike Sharing System (BSS) is a green mode of transportation that is employed extensively for short distance travels in major cities of the world. Unfortunately, the users behaviour driven by their personal needs can often result in empty or full base stations, thereby resulting in loss of customer demand. To counter this loss in customer demand, BSS operators typically utilize a fleet of carrier vehicles for repositioning the bikes between stations. However, this fuel burning mode of repositioning incurs a significant amount of routing, labor cost and further increases carbon emissions. Therefore, we propose a potentially self-sustaining and environment friendly …

Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism, Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan Tan

Research Collection School Of Computing and Information Systems

Automatic discovery of newsworthy themes from sequenced data can relieve journalists from manually poring over a large amount of data in order to find interesting news. In this paper, we propose a novel k -Sketch query that aims to find k striking streaks to best summarize a subject. Our scoring function takes into account streak strikingness and streak coverage at the same time. We study the k -Sketch query processing in both offline and online scenarios, and propose various streak-level pruning techniques to find striking candidates. Among those candidates, we then develop approximate methods to discover the k most representative …

Truly Multi-Modal Youtube-8m Video Classification With Video, Audio, And Text, Zhe Wang, Kingsley Kuan, Mathieu Ravant, Gaurav Manek, Sibo Song, Yuan Fang, Et Al

Research Collection School Of Computing and Information Systems

The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% out of 650 participants using released video and audio features. Beyond that, we extend the original competition by including text information in the classification, making this a truly multi-modal approach with vision, audio and text. The newly introduced text data is termed as YouTube-8M-Text. We present a classification framework for the joint use of text, visual and audio features, and conduct an extensive set of experiments to quantify the benefit that …

Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Computing and Information Systems

Context: Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is also referred as just-in-time defect prediction, could not only ensure software quality in the development process, but also make the developers check and fix the defects in time [1].Objective: Ensemble learning becomes a hot topic in recent years. There have been several studies about applying ensemble learning to defect prediction [2–5]. Traditional ensemble learning approaches only have one layer, i.e., they use ensemble learning once. There are few studies that leverages ensemble learning twice or more. To bridge this research gap, we try to …

Multi-Authority Abs Supporting Dendritic Access Structure, Ruo Mo, Jian-Feng Ma, Ximeng Liu, Qi Li

Research Collection School Of Computing and Information Systems

Attribute-based signature (ABS), which could realize fine-grained access control, was considered to be an importantmethod for anonymous authentication in cloud computing. However, normal ABS only provided simple accesscontrol through threshold structure and thus could not cope with the large-scale attribute sets of users in the cloud. Moreover,the attribute sets were supervised by only one attribute authority, which increased the cost of computation and storage.The whole system was in danger of collapsing once the attribute authority was breached. Aiming at tackling theproblems above, a novel scheme, was proposed called multi-authority ABS supporting dendritic access structure whichsupported any AND, OR and threshold …

Eduform, Olaf Broms

Masters Theses & Doctoral Dissertations

EduForum is a project that has been constructed to fulfil a niche in the learning management system market. The current learning management system market is comprised of mainly large, well-funded, and highly entrenched offerings. The trend in the market has been shifting recently away from some of these legacy offerings towards some of their newer competitors. This trend holds true in the for-profit marker, but no true competitor has emerged to challenge the market’s largest open-source offering, Moodle.

EduForum hopes to be the offering to fill this role by using a number of new methodologies and technologies to create a …

Mining Capstone Project Wikis For Knowledge Discovery, Swapna Gottipati, Venky Shankararaman, Melvrivk Goh

Research Collection School Of Computing and Information Systems

Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to understand the students learning and latest trends in industry. Mining Wikis is useful to educationists and academicians for decision-making about how to modify the educational environment to improve student's learning. The main challenge is that the content or data in project Wikis …

Does Director Interlock Impact The Diffusion Of Accounting Method Choice?, Jie Han, Nan Hu, Ling Liu, Gaoliang Tian

Research Collection School Of Computing and Information Systems

This paper examines the influence of director interlock on firms' discrete accounting method choices from the perspective of behavior diffusion. We argue that firm managers will imitate their interlocked-partner firm's accounting method choices when choosing their own accounting methods. We find that when there is an interlock relationship between two firms, their accounting method choices, including inventory and depreciation methods, are similar to each other, indicating that accounting method choices can diffuse across firms through director interlock. In addition, such similarity is greater the longer the interlock relationship between the two firms is and as uncertainty increases. Further, the interlock …

Deep Learning On Lie Groups For Skeleton-Based Action Recognition, Zhiwu Huang, C. Wan, T. Probst, Gool L. Van

Research Collection School Of Computing and Information Systems

In recent years, skeleton-based action recognition has become a popular 3D classification problem. State-of-the-art methods typically first represent each motion sequence as a high-dimensional trajectory on a Lie group with an additional dynamic time warping, and then shallowly learn favorable Lie group features. In this paper we incorporate the Lie group structure into a deep network architecture to learn more appropriate Lie group features for 3D action recognition. Within the network structure, we design rotation mapping layers to transform the input Lie group features into desirable ones, which are aligned better in the temporal domain. To reduce the high feature …