From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring,
2016
University of Science and Technology of China
From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan
Research Collection School Of Computing and Information Systems
With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence,
2016
Singapore Management University
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Automatically identifying characters in movies has attracted researchers' interest and led to several significant and interesting applications. However, due to the vast variation in character appearance as well as the weakness and ambiguity of available annotation, it is still a challenging problem. In this paper, we investigate this problem with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely, Cast2Face, is featured by: 1) we restrict the assigned names within the set of character names in the cast; 2) for each character, by using the corresponding actor and movie name as keywords, we retrieve …
Careermapper: An Automated Resume Evaluation Tool,
2016
Singapore Management University
Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo
Research Collection School Of Computing and Information Systems
The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called 'CareerMapper'. Our tool is designed to conduct …
The Development Of An Automated Testing Framework For Data-Driven Testing Utilizing The Uml Testing Profile,
2016
Dakota State University
The Development Of An Automated Testing Framework For Data-Driven Testing Utilizing The Uml Testing Profile, James Edward Hearn
Masters Theses & Doctoral Dissertations
The development of increasingly-complex Web 2.0 applications, along with a rise in end-user expectations, have not only made the testing and quality assurance processes of web application development an increasingly-important part of the SDLC, but have also made these processes more complex and resource-intensive. One way to effectively test these applications is by implementing an automated testing solution along with manual testing, as automation solutions have been shown to increase the total amount of testing that can be performed, and help testing team achieve consistency in their testing efforts. The difficulty, though, lies in how to best go about developing …
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts,
2016
University of Nebraska-Lincoln
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
School of Computing: Dissertations, Theses, and Student Research
Online reviews increase consumer visits, increase the time spent on the website, and create a sense of community among the frequent shoppers. Because of the importance of online reviews, online retailers such as Amazon.com and eOpinions provide detailed guidelines for writing reviews. However, though these guidelines provide instructions on how to write reviews, reviewers are not provided instructions for writing product-specific reviews. As a result, poorly-written reviews are abound and a customer may need to scroll through a large number of reviews, which could be up to 6000 pixels down from the top of the page, in order to find …
Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea,
2016
Singapore Management University
Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea, Soon-Goo Hong, Keng Siau, Jong-Weon Kim
Research Collection School Of Computing and Information Systems
Purpose: This paper aims to assess how enterprise resource planning (ERP) performance of Korean small and medium enterprises in manufacturing differs according to different levels of business process reengineering (BPR), information strategic planning (ISP) and ERP customization. Design/methodology/approach: A questionnaire survey was carried out in this research. Responses from 96 small and medium manufacturing companies that have adopted ERP systems were analyzed. Findings: The results of this study suggest that ISP and BPR implementation are positively correlated to ERP performance. Originality/value: While consulting and customization costs have positive impacts on ERP performance, the level of customization does not influence performance. …
Validating Social Media Data For Automatic Persona Generation,
2016
Singapore Management University
Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen
Research Collection School Of Computing and Information Systems
Using personas during interactive design has considerable potential for product and content development. Unfortunately, personas have typically been a fairly static technique. In this research, we validate an approach for creating personas in real time, based on analysis of actual social media data in an effort to automate the generation of personas. We validate that social media data can be implemented as an approach for automating generating personas in real time using actual YouTube social media data from a global media corporation that produces online digital content. Using the organization's YouTube channel, we collect demographic data, customer interactions, and topical …
Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets,
2016
Singapore Management University
Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets, Guansong Pang, Kai Ming Ting, David Albrecht, Huidong Jin
Research Collection School Of Computing and Information Systems
This paper introduces a new unsupervised anomaly detector called ZERO++ which employs the number of zero appearances in subspaces to detect anomalies in categorical data. It is unique in that it works in regions of subspaces that are not occupied by data; whereas existing methods work in regions occupied by data. ZERO++ examines only a small number of low dimensional subspaces to successfully identify anomalies. Unlike existing frequencybased algorithms, ZERO++ does not involve subspace pattern searching. We show that ZERO++ is better than or comparable with the state-of-the-art anomaly detection methods over a wide range of real-world categorical and numeric …
Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings,
2016
Singapore Management University
Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu
Research Collection School Of Computing and Information Systems
Proper feature selection for unsupervised outlier detection can improve detection performance but is very challenging due to complex feature interactions, the mixture of relevant features with noisy/redundant features in imbalanced data, and the unavailability of class labels. Little work has been done on this challenge. This paper proposes a novel Coupled Unsupervised Feature Selection framework (CUFS for short) to filter out noisy or redundant features for subsequent outlier detection in categorical data. CUFS quantifies the outlierness (or relevance) of features by learning and integrating both the feature value couplings and feature couplings. Such value-to-feature couplings capture intrinsic data characteristics and …
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction,
2016
Singapore Management University
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang
Research Collection School Of Computing and Information Systems
The indistinguishability security of a public-key cryptosystem can be reduced to a computational hard assumption in the random oracle model, where the solution to a computational hard problem is hidden in one of the adversary’s queries to the random oracle. Usually, there is a finding loss in finding the correct solution from the query set, especially when the decisional variant of the computational problem is also hard. The problem of finding loss must be addressed towards tight(er) reductions under this type. In EUROCRYPT 2008, Cash, Kiltz and Shoup proposed a novel approach using a trapdoor test that can solve the …
Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy,
2016
Singapore Management University
Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy, Gottipati Swapna, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Experiential learning refers to learning from experience or learning by doing. Universities have explored various forms for implementing experiential learning such as apprenticeships, internships, cooperative education, practicums, service learning, job shadowing, fellowships and community activities. However, very little has been done in systematically trying to integrate experiential learning to the main stream academic curriculum. Over the last two years, at the authors’ university, a new program titled UNI-X was launched to achieve this. Combining academic curriculum with experiential learning pedagogy, provides a challenging environment for students to use their disciplinary knowledge and skills to tackle real world problems and issues …
Coherence, Richness And Cognitive Absorption In Website Design,
2016
Singapore Management University
Coherence, Richness And Cognitive Absorption In Website Design, L. Visinescu, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Kaplan’s theory on environmental preferences can offer a holistic perspective on cognitive absorption in ecommerce website design. Drawing on Kaplan’s theory, this paper proposes that coherence and richness of a website can enhance cognitive absorption of users. The findings from our study not only support the hypotheses, but also suggest that coherence and richness can reach an optimal proportion in website design, after which they are inversely correlated.
An Interview With The Scorpion: Walter O’Brien,
2016
Scorpion Computer Services
An Interview With The Scorpion: Walter O’Brien, Walter O'Brien
The Transdisciplinary STEAM+ Journal
An interview with Walter O'Brien (hacker handle: "Scorpion"), known as a businessman, information technologist, executive producer, and media personality who is the founder and CEO of Scorpion Computer Services, Inc. O'Brien is also the inspiration for and executive producer of the CBS television series, Scorpion.
Inferred Error Rates For Entity Resolution,
2016
University of Arkansas Little Rock
Inferred Error Rates For Entity Resolution, Melody Lynn Penning
Theses and Dissertations
This dissertation is focused on the methodology of determining the quality of the results of entity resolution. Entity resolution methodologies results in different success rates. Until now these success rates have been measured by counting all of the correctly and incorrectly matched results. This is quickly becoming an intractable task as datasets grow in size. In order to address this problem this research tests and describes the results of count based measures as compared with inferred measures borrowed from the information retrieval community. The key contribution of this research is a proof of concept in a controlled environment that demonstrates …
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks,
2016
Singapore Management University
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata
Research Collection School Of Computing and Information Systems
We address the challenge of detecting and addressing advanced persistent threats (APTs) in a computer network, focusing in particular on the challenge of detecting data exfiltration over Domain Name System (DNS) queries, where existing detection sensors are imperfect and lead to noisy observations about the network’s security state. Data exfiltration over DNS queries involves unauthorized transfer of sensitive data from an organization to a remote adversary through a DNS data tunnel to a malicious web domain. Given the noisy sensors, previous work has illustrated that standard approaches fail to satisfactorily rise to the challenge of detecting exfiltration attempts. Instead, we …
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification,
2016
Singapore Management University
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we study cross-domain sentiment classification with neural network architectures. We borrow the idea from Structural Correspondence Learning and use two auxiliary tasks to help induce a sentence embedding that supposedly works well across domains for sentiment classification. We also propose to jointly learn this sentence embedding together with the sentiment classifier itself. Experiment results demonstrate that our proposed joint model outperforms several state-of-the-art methods on five benchmark datasets.
Media Reinvented,
2016
Singapore Management University
Media Reinvented, Geoff Tan
Asian Management Insights
The brave new world of digital media.
Asean's Digital Economy,
2016
Singapore Management University
Asean's Digital Economy, Naveen Menon
Asian Management Insights
Transforming industries, enriching lives and propelling progress.
Connecting India,
2016
Singapore Management University
Connecting India, Sam Pitroda
Asian Management Insights
Great inventions will not be born in the absence of the will and intent to embrace change and solve wideranging societal problems.
Summarization Of Egocentric Videos: A Comprehensive Survey,
2016
Singapore Management University
Summarization Of Egocentric Videos: A Comprehensive Survey, Ana Garcia Del Molino, Cheston Tan, Joo-Hwee Lim, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The introduction of wearable video cameras (e.g., GoPro) in the consumer market has promoted video life-logging, motivating users to generate large amounts of video data. This increasing flow of first-person video has led to a growing need for automatic video summarization adapted to the characteristics and applications of egocentric video. With this paper, we provide the first comprehensive survey of the techniques used specifically to summarize egocentric videos. We present a framework for first-person view summarization and compare the segmentation methods and selection algorithms used by the related work in the literature. Next, we describe the existing egocentric video datasets …
