Computer Sciences Commons^™

Developer Involvement Considered Harmful? An Empirical Examination Of Android Bug Resolution Times, Subhajit Datta, Proshanta Sarkar, Subhashis Majumder

Research Collection School Of Computing and Information Systems

In large scale software development ecosystems, there is a common perception that higher developer involvement leads to faster resolution of bugs. This is based on conjectures around more ``eyeballs" making bugs "shallow" -- whose validity and applicability are not without dispute. In this paper, we posit that the level of developer attention as well as its extent of diversity influence how quickly bugs get resolved. We report results from a study of 1,000+ Android bugs. We find statistically significant evidence that attention and diversity have contrasting relationships with the resolution time of bugs, even after controlling for factors such as …

An Ecological Model For Digital Platforms Maintenance And Evolution, Paolo Rocchi, Paolo Spagnoletti, Subhajit Datta

Research Collection School Of Computing and Information Systems

The maintenance of software products has been studied extensively in both software engineering and management information systems. Such studies are mainly focused on the activities that take place prior to starting the maintenance phase. Their contribution is either related to the improvement of software quality or to validating contingency models for reducing maintenance efforts. The continuous maintenance philosophy suggests to shift the attention within the maintenance phase for better coping with the evolutionary trajectories of digital platforms. In this paper, we examine the maintenance process of a digital platform from the perspective of the software vendor. Based on our empirical …

Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen

Research Collection School Of Computing and Information Systems

In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under realworld environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …

Hybrid Euclidean-And-Riemannian Metric Learning For Image Set Classification, Zhiwu Huang, R. Wang, S. Shan, X. Chen

Research Collection School Of Computing and Information Systems

We propose a novel hybrid metric learning approach to combine multiple heterogenous statistics for robust image set classification. Specifically, we represent each set with multiple statistics – mean, covariance matrix and Gaussian distribution, which generally complement each other for set modeling. However, it is not trivial to fuse them since the mean vector with dd-dimension often lies in Euclidean space RdRd, whereas the covariance matrix typically resides on Riemannian manifold Sym+dSymd+. Besides, according to information geometry, the space of Gaussian distribution can be embedded into another Riemannian manifold Sym+d+1Symd+1+. To fuse these statistics from heterogeneous spaces, we propose a Hybrid …

Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu

Research Collection School Of Computing and Information Systems

Manual annotation of celebrities in Web videos is an essential task in many people-related Web services. The task, however, poses a significant challenge even to skillful annotators, mainly due to the large quantity of unfamiliar and greatly varied celebrities, and the lack of a customized system for it. This work develops CeleLabel, an interactive system for manually annotating celebrities in the Web video domain. The peculiarity of CeleLabel is to exploit and display multiple types of information that could assist the annotation, including video content, context surrounding and within a video, celebrity images on the Web, and human factors. Using …

Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

We address the problem of visual instance mining, which is to extract frequently appearing visual instances automatically from a multimedia collection. We propose a scalable mining method by exploiting Thread of Features (ToF). Specifically, ToF, a compact representation that links consistent features across images, is extracted to reduce noises, discover patterns, and speed up processing. Various instances, especially small ones, can be discovered by exploiting correlated ToFs. Our approach is significantly more effective than other methods in mining small instances. At the same time, it is also more efficient by requiring much fewer hash tables. We compared with several state-of-the-art …

Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of comparing textual keywords with visual image content. Image search engines therefore highly depend on the surrounding texts, which are often noisy or too few to accurately describe the image content. Second, ranking functions are trained on query-image pairs labeled by human labelers, making the annotation intellectually expensive and thus cannot be scaled up. We demonstrate that the above two fundamental challenges …

Band Selection For Hyperspectral Images Using Probabilistic Memetic Algorithm, Liang Feng, Ah-Hwee Tan, Meng-Hiot Lim, Si Wei Jiang

Research Collection School Of Computing and Information Systems

Band selection plays an important role in identifying the most useful and valuable information contained in the hyperspectral images for further data analysis such as classification, clustering, etc. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving the NP-hard band selection problem. In this paper, we propose a formal probabilistic memetic algorithm for band selection, which is able to adaptively control the degree of global exploration against local exploitation as the search progresses. To verify the effectiveness of the proposed probabilistic mechanism, empirical studies conducted on five well-known hyperspectral images against two …

Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao

Research Collection School Of Computing and Information Systems

Geographical characteristics derived from the historical check-in data have been reported effective in improving location recommendation accuracy. However, previous studies mainly exploit geographical characteristics from a user’s perspective, via modeling the geographical distribution of each individual user’s check-ins. In this paper, we are interested in exploiting geographical characteristics from a location perspective, by modeling the geographical neighborhood of a location. The neighborhood is modeled at two levels: the instance-level neighborhood defined by a few nearest neighbors of the location, and the region-level neighborhood for the geographical region where the location exists. We propose a novel recommendation approach, namely Instance-Region Neighborhood …

Modloc: Localizing Multiple Objects In Dynamic Indoor Environment, Xiaonan Guo, Dian Zhang, Kaishun Wu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

Radio frequency (RF) based technologies play an important role in indoor localization, since Radio Signal Strength (RSS) can be easily measured by various wireless devices without additional cost. Among these, radio map based technologies (also referred as fingerprinting technologies) are attractive due to high accuracy and easy deployment. However, these technologies have not been extensively applied on real environment for two fatal limitations. First, it is hard to localize multiple objects. When the number of target objects is unknown, constructing a radio map of multiple objects is almost impossible. Second, environment changes will generate different multipath signals and severely disturb …

Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu

Research Collection School Of Computing and Information Systems

Human computation games (HCGs) are applications that use games to harness human intelligence to perform computations that cannot be effectively done by software systems alone. Despite their increasing popularity, insufficient research has been conducted to examine the predictors of player acceptance for HCGs. In particular, prior work underlined the important role of game enjoyment in predicting acceptance of entertainment technology without specifying its driving factors. This study views game enjoyment through a taxonomy of aesthetic experiences and examines the effect of aesthetic experience, usability and information quality on player acceptance of HCGs. Results showed that aesthetic experience and usability were …

On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …

Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We investigate online active learning techniques for classification tasks in data stream mining applications. Unlike traditional learning approaches (either batch or online learning) that often require to request the class label of each incoming instance, online active learning queries only a subset of informative incoming instances to update the classification model, which aims to maximize classification performance using minimal human labeling effort during the entire online stream data mining task. In this paper, we present a new family of algorithms for online active learning called Passive-Aggressive Active (PAA) learning algorithms by adapting the popular Passive-Aggressive algorithms in an online active …

Client/Server Data Synchronization In Ios Development, Dmitry Tumanov

Undergraduate Honors Theses

Electronic gadgets such as touchpads and smartphones are becoming more popular in business and everyday life. The main advantage of mobile devices over personal computers is their portability. Cellular data plans allow Internet access without having permanent access point. There is a number of web-based applications available for gadgets. The primary goal of these apps is to provide their services through constant Internet access. However, it may affect the operation of both devices and applications. The objective of this thesis is to find a better way of client/server data synchronization in iOS development that can reduce the negative consequences of …

The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao

Research Collection School Of Computing and Information Systems

The importance of multimedia travel guide search and recommender systems has led to a substantial amount of research spanning different computer science and information system disciplines in recent years. The five core research streams we identify here incorporate a few multimedia computing and information retrieval problems that relate to the alternative perspectives of algorithm design for optimizing search/recommendation quality and different methodological paradigms to assess system performance at large scale. They include (1) query analysis, (2) diversification based on different criteria, (3) ranking and reranking, (4) personalization and (5) evaluation. Based on a comprehensive discussion and analysis of these streams, …

Online Transfer Learning, Peilin Zhao, Steven C. H. Hoi, Jialei Wang, Bin Li

Research Collection School Of Computing and Information Systems

This paper investigates a new machine learning framework of Online Transfer Learning (OTL), which aims to attack an online learning task on a target domain by transferring knowledge from some source domain. We do not assume data in the target domain follows the same distribution as that in the source domain, and the motivation of our work is to enhance a supervised online learning task on a target domain by exploiting the existing knowledge that had been learnt from training data in source domains. OTL is in general a challenging problem since data in both source and target domains not …

Deep Learning For Content-Based Image Retrieval: A Comprehensive Study, Ji Wan, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, Jintao Li

Research Collection School Of Computing and Information Systems

Learning effective feature representations and similarity measures are crucial to the retrieval performance of a content-based image retrieval (CBIR) system. Despite extensive research efforts for decades, it remains one of the most challenging open problems that considerably hinders the successes of real-world CBIR systems. The key challenge has been attributed to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human. Among various techniques, machine learning has been actively investigated as a possible direction to bridge the semantic gap in the long term. Inspired by recent successes of deep …

Historical Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Historical traffic information is valuable for transportation analysis and planning, as well as for route search services. In view of these applications, we propose the k traffic-tolerant paths problem (TTP) on road networks, which takes a source-destination pair and historical traffic information as input, and returns k paths that minimize the aggregate (historical) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to compute. We propose an exact algorithm and a heuristic algorithm for this problem. Experiments on real traffic data demonstrate the effectiveness of TTP paths and …

Dynamic Clustering Of Contextual Multi-Armed Bandits, Trong T. Nguyen, Hady W. Lauw

Research Collection School Of Computing and Information Systems

With the prevalence of the Web and social media, users increasingly express their preferences online. In learning these preferences, recommender systems need to balance the trade-off between exploitation, by providing users with more of the "same", and exploration, by providing users with something "new" so as to expand the systems' knowledge. Multi-armed bandit (MAB) is a framework to balance this trade-off. Most of the previous work in MAB either models a single bandit for the whole population, or one bandit for each user. We propose an algorithm to divide the population of users into multiple clusters, and to customize the …

Generative Modeling Of Entity Comparisons In Text, Maksim Tkachenko, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Users frequently rely on online reviews for decision making. In addition to allowing users to evaluate the quality of individual products, reviews also support comparison shopping. One key user activity is to compare two (or more) products based on a specific aspect. However, making a comparison across two different reviews, written by different authors, is not always equitable due to the different standards and preferences of individual authors. Therefore, we focus instead on comparative sentences, whereby two products are compared directly by a review author within a single sentence. We study the problem of comparative relation mining. Given a set …

Improving The Efficacy Of Web-Based Educational Outreach In Ecology, Gregory R. Goldsmith, Andrew D. Fulton, Colin D. Witherill, Javier F. Espeleta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Scientists are increasingly engaging the web to provide formal and informal science education opportunities. Despite the prolific growth of web-based resources, systematic evaluation and assessment of their efficacy remains limited. We used clickstream analytics, a widely available method for tracking website visitors and their behavior, to evaluate 60,000 visits over three years to an educational website focused on ecology. Visits originating from search engine queries were a small proportion of the traffic, suggesting the need to actively promote websites to drive visitation. However, the number of visits referred to the website per social media post varied depending on the social …

Networked Employment Discrimination, Tamara Kneese

Media Studies

Employers often struggle to assess qualified applicants, particularly in contexts where they receive hundreds of applications for job openings. In an effort to increase efficiency and improve the process, many have begun employing new tools to sift through these applications, looking for signals that a candidate is “the best fit.” Some companies use tools that offer algorithmic assessments of workforce data to identify the variables that lead to stronger employee performance, or to high employee attrition rates, while others turn to third party ranking services to identify the top applicants in a labor pool. Still others eschew automated systems, but …

The Information Value Methodology: How Users Assess The Quality Of Web Information, Marilou Haines

Theses and Dissertations

The Internet is a self-regulating complex system in which users decide what is relevant through their actions. Since the burden of locating and evaluating information depends on knowledge, experience, and skill, this study rigorously and holistically investigates the Web users' experience. The study began with a multidisciplinary literature review to determine how academics assess IQ on the Web. While individual models are narrowly focused, in aggregate, they delineate the boundaries of IQ needs, and identify the dimensions that are significant to the Web community. These dimensions, categorized into six knowledge domains, are the core of the information value methodology (IVM). …

Advances Of Scientific Research On Technology Enhanced Learning In Social Networks And Mobile Contexts: Towards High Effective Educational Platforms For Next Generation Education, Leyla Zhuhadar, Miltiadis Lytras, Jacky Xi Zhang, Eugenius Kurilovas

Analytics & Information Systems Faculty Publications

This editorial presents the latest advances of scientific Research on Technology enhanced learning in social networks and mobile contexts. It summarizes the key finding and promotes three main pillars for future scientific contribution to the domain namely: Enabling Technologies, Educational Strategies, and Next Generation Social Networks for Educational Purposes. It can serve as a position document for scientific debate fostering international collaboration and empirical research in the various aspects of the well-defined agenda. It can also serve as a reference edition for researchers interested in the adoption of Social Networks, in the Education Sector.

Promoting Information Systems Major To Undergraduate Students - A Comprehensive Investigation, Lei Li, Chi Zhang, Guangzhi Zheng

Faculty Articles

Weak enrollment growth has been a concern for many Information Systems (IS) programs in recent years although the IT/IS job market remains strong. Stimulating undergraduate students’ interest to IS programs have been a challenge. In this paper, the researchers took a comprehensive approach to study how to effectively promote a Management Information Systems (MIS) program to undergraduate students at a medium-size public university in the southeastern US. Using a survey-based method, the researchers first investigated the factors that impact students’ selection of majors and identified students’ perceptions on an MIS program. In this paper, an MIS program promotion strategy was …

Data Analytics For Power Utility Storm Planning, Lan Lin, Aldo Dagnino, Derek Doran, Swapna S. Gokhale

Kno.e.sis Publications

As the world population grows, recent climatic changes seem to bring powerful storms to populated areas. The impact of these storms on utility services is devastating. Hurricane Sandy is a recent example of the enormous damages that storms can inflict on infrastructure, society, and the economy. Quick response to these emergencies represents a big challenge to electric power utilities. Traditionally utilities develop preparedness plans for storm emergency situations based on the experience of utility experts and with limited use of historical data. With the advent of the Smart Grid, utilities are incorporating automation and sensing technologies in their grids and …

International Student Portal, Radha Krishna Yalamanchili

All Capstone Projects

(from the Introduction)

This is an web based application which provides information to International students about GSU university. GSU International student portal is an internet based application that can be accessed throughout world .Students can also know updates of university like cultural events, news ,weather reports etc. Students can fill the contact details so that school can contact him. The proposed system is completely integrated online system. Students can fill form to get airport pick from international office.

Administrative System For A Speech Pathology Office, Devin Raymond Peterman

All Capstone Projects

The office that this application was designed for is a Speech Pathology office. Therapists are sent to the houses of patients to treat them. After each visit, the speech pathologists record the data collected from the treatment. This data is then collected and type manually into an excel sheet by the office administrator.

The way the office is currently run is inefficient and outdated. Because all the information from the visits has to be typed manually into the excel sheets there is a back log of information that has to be entered. This leads to disorganization and possible loss of …

Online Simulations For Conceptual Understanding Of Thermoelectric Devices, Maria De Rosario Uribe

Open Access Theses

Computer simulations have been extensively used with educational purposes. However, the successful implementation in order to improve learning has been a matter of debate in research in education. The purpose of this case study is to analyze how a set of computer simulations can improve student understanding of thermoelectric devices. The study was developed in a learning context characterized by the advanced degree of difficulty of the topics treated, the high academic level of education of the students, and the online nature of the learning environment. As part of the course, students were provided with instructional materials that guided the …

The Indiana Cybersecurity Services Center (Incsc): A Cost-Benefit Analysis For K-12 Schools, Hans Christian Vargas Silva

Open Access Theses

The aim of this thesis is to determine if there are greater benefits than costs associated in the participation of public K-12 school corporations in the Indiana Cybersecurity Services Center (INCSC). This thesis is an ex-antecost-benefit analysis policy assessment of the INCSC. The study consisted of a sample of 6 school corporations from which 5 were classified as small and 1 was large. Three methods were considered for data collection; however conducting interviews was the most effective method due to the interaction with IT personnel from each organization in order to analyze current costs related to 4 areas of …