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Articles 6421 - 6450 of 9024
Full-Text Articles in Computer Sciences
Innovative Applications And Security Of Internet Of Things, Yingjiu Li, Yingjiu Li, Nai-Wei Lo
Innovative Applications And Security Of Internet Of Things, Yingjiu Li, Yingjiu Li, Nai-Wei Lo
Research Collection School Of Computing and Information Systems
With the advances and falling cost of intelligent things like RFID/USN, sensor networks, NFC, ZigBee, smart phones, and other relevant technologies, the potential applications and implementations of Internet of things have been intensively studied by both the academia and the industry. One potential application is integrating social networks with IoT, which results in the social Internet of things (SIoT). This vision not only provides potential opportunities but also new challenges. Innovative application and security are two main issues toward this paradigm
Mini-Track Introduction: Information Economics, Competition, Regulation, Law And Society, Eric K. Clemons, Robert John Kauffman, Thomas A. Weber
Mini-Track Introduction: Information Economics, Competition, Regulation, Law And Society, Eric K. Clemons, Robert John Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
This mini-track is informed by the most modern thinking in information economics and competitive strategy, and includes many interdisciplinary applications of IS and technology.
Risk Minimization Of Disjunctive Temporal Problem With Uncertainty, Hoong Chuin Lau, Tuan Anh Hoang
Risk Minimization Of Disjunctive Temporal Problem With Uncertainty, Hoong Chuin Lau, Tuan Anh Hoang
Research Collection School Of Computing and Information Systems
The Disjunctive Temporal Problem with Uncertainty (DTPU) is a fundamental problem that expresses temporal reasoning with both disjunctive constraints and contingency. A recent work (Peintner et al, 2007) develops a complete algorithm for determining Strong Controlla- bility of a DTPU. Such a notion that guarantees 100% confidence of execution may be too conservative in practice. In this paper, following the idea of (Tsamardinos 2002), we are interested to find a schedule that minimizes the risk (i.e. probability of failure) of executing a DTPU. We present a problem decomposition scheme that enables us to compute the probability of failure efficiently, followed …
Learning To Recommend Descriptive Tags For Questions In Social Forums, Liqiang Nie, Yiliang Zhao, Xiangyu Wang, Jialie Shen, Tat-Seng Chua
Learning To Recommend Descriptive Tags For Questions In Social Forums, Liqiang Nie, Yiliang Zhao, Xiangyu Wang, Jialie Shen, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Around 40% of the questions in the emerging social-oriented question answering forums have at most one manually labeled tag, which is caused by incomprehensive question understanding or informal tagging behaviors. The incompleteness of question tags severely hinders all the tag-based manipulations, such as feeds for topic-followers, ontological knowledge organization, and other basic statistics. This article presents a novel scheme that is able to comprehensively learn descriptive tags for each question. Extensive evaluations on a representative real-world dataset demonstrate that our scheme yields significant gains for question annotation, and more importantly, the whole process of our approach is unsupervised and can …
Strategic Decision Support System Using Heuristic Algorithm For Practical Outlet Zones Allocation To Dealers In A Beer Supply Distribution Network, Michelle Lee Fong Cheong
Strategic Decision Support System Using Heuristic Algorithm For Practical Outlet Zones Allocation To Dealers In A Beer Supply Distribution Network, Michelle Lee Fong Cheong
Research Collection School Of Computing and Information Systems
We consider a two-echelon beer supply distribution network with the brewer replenishing the dealers and the dealers serving the outlet zones directly, for multiple product types. The allocation of the outlet zones to the dealers will determine the quantity of products the brewer replenishes each dealer, which will in turn impact the total warehousing and transportation costs. The non-linear optimization model formulated is difficult to solve to optimality, and the model itself does not include practical business considerations in the distribution business. A heuristics algorithm is designed and easily implemented using spreadsheets with Visual Basic programming to effectively and efficiently …
Complexity Of The Soundness Problem Of Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong
Complexity Of The Soundness Problem Of Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Classical workflow nets (WF-nets for short) are an important subclass of Petri nets that are widely used to model and analyze workflow systems. Soundness is a crucial property of workflow systems and guarantees that these systems are deadlock-free and bounded. Aalst et al. proved that the soundness problem is decidable for WF-nets and can be polynomially solvable for free-choice WF-nets. This paper proves that the soundness problem is PSPACE-hard for WF-nets. Furthermore, it is proven that the soundness problem is PSPACE-complete for bounded WF-nets. Based on the above conclusion, it is derived that the soundness problem is also PSPACE-complete for …
Inferring The Untold: Mining Software Engineering Research Publication Networks, Santonu Sarkar, Subhajit Datta
Inferring The Untold: Mining Software Engineering Research Publication Networks, Santonu Sarkar, Subhajit Datta
Research Collection School Of Computing and Information Systems
Since the inception of organized research publication in software engineering in 1975, the discipline has gained maturity. This journey has been guided by the synergy of ideas and interactions of individuals. In this paper, we discuss a method for aggregating the corpus of 19,000+ papers and 21,000+ authors across 16 specialized software engineering venues. We focus on the approach of data collection, processing and storage. It can be used to address questions by the software engineering research community. We evaluate three questions: patterns of research topics with time, factors influencing the contribution of individual researchers, and the interaction among the …
Loki: A Privacy-Conscious Platform For Crowdsourced Surveys, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Boreli
Loki: A Privacy-Conscious Platform For Crowdsourced Surveys, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Boreli
Research Collection School Of Computing and Information Systems
Emerging platforms such as Amazon Mechanical Turk and Google Consumer Surveys are increasingly being used by researchers and market analysts to crowdsource large-scale survey data from on-line populations at extremely low-cost. However, by participating in successive surveys, users risk being profiled and targeted, both by surveyors and by the platform itself. In this paper we propose, develop, and evaluate the design of a crowdsourcing platform, called Loki, that is privacy conscious. Our contributions are three-fold: (a) We propose Loki, a system that allows users to obfuscate their (ratings-based or multiple-choice) responses at-source based on their chosen privacy level, and gives …
How Can Consumer Preferences Be Leveraged For Targeted Upselling In Cable Tv Services?, Bing Tian Dai
How Can Consumer Preferences Be Leveraged For Targeted Upselling In Cable Tv Services?, Bing Tian Dai
Research Collection School Of Computing and Information Systems
Internet TV has attracted a significant amount of attention from the conventional cable TV service providers, by providing customized TV programs at preferred time slots. The cable TV service providers are seeking to retain their customers by giving them a better experience: by understanding their customers’ preferences and upselling them the right products to cater to their interests. It is not easy to understand customer preferences though, since customers are not able to watch channels to which they have not subscribed. This makes it difficult to predict what they will like to watch, as a result. In this paper, I …
Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi
Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation …
Privacy-Preserving Ad-Hoc Equi-Join On Outsourced Data, Hwee Hwa Pang, Xuhua Ding
Privacy-Preserving Ad-Hoc Equi-Join On Outsourced Data, Hwee Hwa Pang, Xuhua Ding
Research Collection School Of Computing and Information Systems
In IT outsourcing, a user may delegate the data storage and query processing functions to a third-party server that is not completely trusted. This gives rise to the need to safeguard the privacy of the database as well as the user queries over it. In this article, we address the problem of running ad hoc equi-join queries directly on encrypted data in such a setting. Our contribution is the first solution that achieves constant complexity per pair of records that are evaluated for the join. After formalizing the privacy requirements pertaining to the database and user queries, we introduce a …
Online Multiple Kernel Similarity Learning For Visual Search, Hao Xia, Chu Hong Hoi, Rong Jin, Peilin Zhao
Online Multiple Kernel Similarity Learning For Visual Search, Hao Xia, Chu Hong Hoi, Rong Jin, Peilin Zhao
Research Collection School Of Computing and Information Systems
Recent years have witnessed a number of studies on distance metric learning to improve visual similarity search in content-based image retrieval (CBIR). Despite their successes, most existing methods on distance metric learning are limited in two aspects. First, they usually assume the target proximity function follows the family of Mahalanobis distances, which limits their capacity of measuring similarity of complex patterns in real applications. Second, they often cannot effectively handle the similarity measure of multimodal data that may originate from multiple resources. To overcome these limitations, this paper investigates an online kernel similarity learning framework for learning kernel-based proximity functions …
Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Research Collection School Of Computing and Information Systems
This paper investigates a framework of search-based face annotation (SBFA) by mining weakly labeled facial images that are freely available on the World Wide Web (WWW). One challenging problem for search-based face annotation scheme is how to effectively perform annotation by exploiting the list of most similar facial images and their weak labels that are often noisy and incomplete. To tackle this problem, we propose an effective unsupervised label refinement (ULR) approach for refining the labels of web facial images using machine learning techniques. We formulate the learning problem as a convex optimization and develop effective optimization algorithms to solve …
Detecting Click Fraud In Online Advertising: A Data Mining Approach, Richard Oentaryo, Ee Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar
Detecting Click Fraud In Online Advertising: A Data Mining Approach, Richard Oentaryo, Ee Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar
Research Collection School Of Computing and Information Systems
Click fraud - the deliberate clicking on advertisements with no real interest on the product or service offered - is one of the most daunting problems in online advertising. Building an elective fraud detection method is thus pivotal for online advertising businesses. We organized a Fraud Detection in Mobile Advertising (FDMA) 2012 Competition, opening the opportunity for participants to work on real-world fraud data from BuzzCity Pte. Ltd., a global mobile advertising company based in Singapore. In particular, the task is to identify fraudulent publishers who generate illegitimate clicks, and distinguish them from normal publishers. The competition was held from …
How Can Substitution And Complementarity Effects Be Leveraged For Broadband Internet Services Strategy?, Gwangjae Jung, Young Soo Kim, Robert J. Kauffman
How Can Substitution And Complementarity Effects Be Leveraged For Broadband Internet Services Strategy?, Gwangjae Jung, Young Soo Kim, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
With growth in mobile Internet services, the relationship between mobile and fixed broadband has become an issue in telecom firm strategy. Previous research focused on aggregate penetration for mobile and fixed broadband services. Our research analyzes the economic relationship between mobile and fixed broadband services at the household level, as a basis for how senior managers should rethink their strategy approach. Using data on broadband services subscriptions, we examine how changes that occur for mobile broadband services bandwidth (MBB) affect changes in fixed broadband bandwidth (FBB) services subscriptions, inclusive of new subscriptions - and vice versa. We explore the different …
Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu
Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
There have been many approaches towards investing in innovation projects. There has been very little discussion about the need to align such investments with the mission, vision, goals, leadership style, value discipline and risk appetite of an organization. This paper reviews existing approaches to innovation related investments and suggests the setting up of a proper innovation portfolio management process along with three dashboards that will help make innovation related investment decisions in an informed manner. The resulting innovation portfolio will be optimal in its alignment with an organizations mission and vision. We expect this method to be used by all …
A Dynamic Programming Approach To Achieving An Optimal End State Along A Serial Production Line, Shih-Fen Cheng, Blake E. Nicholson, Marina A. Epelman, Daniel J. Reaume, Robert L. Smith
A Dynamic Programming Approach To Achieving An Optimal End State Along A Serial Production Line, Shih-Fen Cheng, Blake E. Nicholson, Marina A. Epelman, Daniel J. Reaume, Robert L. Smith
Research Collection School Of Computing and Information Systems
In modern production systems, it is critical to perform maintenance, calibration, installation, and upgrade tasks during planned downtime. Otherwise, the systems become unreliable and new product introductions are delayed. For reasons of safety, testing, and access, task performance often requires the vicinity of impacted equipment to be left in a specific “end state” when production halts. Therefore, planning the shutdown of a production system to balance production goals against enabling non-production tasks yields a challenging optimization problem. In this paper, we propose a mathematical formulation of this problem and a dynamic programming approach that efficiently finds optimal shutdown policies for …
Dynamic Queue Management For Hospital Emergency Room Services, Kar Way Tan
Dynamic Queue Management For Hospital Emergency Room Services, Kar Way Tan
Dissertations and Theses Collection (Open Access)
The emergency room (ER) – or emergency department (ED) – is often seen as a place with long waiting times and a lack of doctors to serve the patients. However, it is one of the most important departments in a hospital, and must efficiently serve patients with critical medical needs. In the existing literature, addressing the issue of long waiting times in an ED often takes the form of single-faceted queue-management strategies that are either from a demand perspective or from a supply perspective. From the demand perspective, there is work on queue design such as priority queues, or queue …
A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging, Guansong Pang, Shengyi Jiang, Dongyi Chen
A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging, Guansong Pang, Shengyi Jiang, Dongyi Chen
Research Collection School Of Computing and Information Systems
Identifying potential customers among a huge number of users in microblogging is a fundamental problem for microblog marketing. One challenge in potential customer detection in microblogging is how to generate an accurate characteristic description for users, i.e., user profile generation. Intuitively, the preference of a user’s friends (i.e., the person followed by the user in microblogging) is of great importance to capture the characteristic of the user. Also, a user’s self-defined tags are often concise and accurate carriers for the user’s interests. In this paper, for identifying potential customers in microblogging, we propose a method to generate user profiles via …
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Research Collection School Of Computing and Information Systems
Research into software engineering (SE) education is largely concentrated on teaching and learning issues in coursework programs. This paper, in contrast, provides a meta analysis of research publications in software engineering to help with research education in SE. Studying publication patterns in a discipline will assist research students and supervisors gain a deeper understanding of how successful research has occurred in the discipline. We present results from a large scale empirical study covering over three and a half decades of software engineering research publications. We identify how different factors of publishing relate to the number of papers published as well …
Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong
Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different …
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Research Collection School Of Computing and Information Systems
This paper addresses the difficult problem of finding dense correspondence across images with large appearance variations. Our method uses multiple feature samples at each pixel to deal with the appearance variations based on our observation that pre-defined single feature sample provides poor results in nearest neighbor matching. We apply the idea in a flow-based matching framework and utilize the best feature sample for each pixel to determine the flow field. We propose a novel energy function and use dual-layer loopy belief propagation to minimize it where the correspondence, the feature scale and rotation parameters are solved simultaneously. Our method is …
Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition, M. Liu, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition, M. Liu, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we propose a method for video-based human emotion recognition. For each video clip, all frames are represented as an image set, which can be modeled as a linear subspace to be embedded in Grassmannian manifold. After feature extraction, Class-specific One-to-Rest Partial Least Squares (PLS) is learned on video and audio data respectively to distinguish each class from the other confusing ones. Finally, an optimal fusion of classifiers learned from both modalities (video and audio) is conducted at decision level. Our method is evaluated on the Emotion Recognition In The Wild Challenge (EmotiW 2013). The experimental results on …
A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang
A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
In global mobility networks, anonymous user authentication is an essential task for enabling roaming service. In a recent paper, Jiang et al. proposed a smart card based anonymous user authentication scheme for roaming service in global mobility networks. This scheme can protect user privacy and is believed to have many abilities to resist a range of network attacks, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Jiang et al.’s scheme, and show that the scheme is in fact insecure against the stolen-verifier attack and replay attack. Then, we …
Coupling Alignments With Recognition For Still-To-Video Face Recognition, Zhiwu Huang, X. Zhao, S. Shan, R. Wang, X. Chen
Coupling Alignments With Recognition For Still-To-Video Face Recognition, Zhiwu Huang, X. Zhao, S. Shan, R. Wang, X. Chen
Research Collection School Of Computing and Information Systems
The Still-to-Video (S2V) face recognition systems typically need to match faces in low-quality videos captured under unconstrained conditions against high quality still face images, which is very challenging because of noise, image blur, low face resolutions, varying head pose, complex lighting, and alignment difficulty. To address the problem, one solution is to select the frames of `best quality' from videos (hereinafter called quality alignment in this paper). Meanwhile, the faces in the selected frames should also be geometrically aligned to the still faces offline well-aligned in the gallery. In this paper, we discover that the interactions among the three tasks-quality …
Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh
Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh
Research Collection School Of Computing and Information Systems
Increase in the frequency of disruptions in the recent times and their impact have increased the attention in supply chain disruption management research. The objective of this paper is to understand as to how a disruption might affect the supply chain network - depending upon the network structure, the node that is disrupted, the disruption in production capacity of the disrupted node and the period of the disruption - via decision trees. To this end, we first developed a 5-tier agent-based supply chain model and then simulated it for various what-if disruptive scenarios for 3 different network structures (80 trials …
An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee
An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee
Research Collection School Of Computing and Information Systems
In this paper, I shall propose an integrated model of worker skills and team motivation for a computer-based simulation game that can be used to provide experiential learning to students. They can act as project managers here without being burdened by the costs and risks associated with unsuccessful projects. I shall present an approach of classifying skills into five different types (relevant to IT projects) and apply a five-point competency scale to each skill type. The Pearson Correlation will be applied to the scores of each skill type to generate an efficiency index that will characterize the effectiveness of a …
Singapore Management University Wins Inaugural Teradata University Network Teaching Innovation Award, Singapore Management University
Singapore Management University Wins Inaugural Teradata University Network Teaching Innovation Award, Singapore Management University
SMU Press Releases and News
Teradata Corporation, a leading global provider of analytic data platforms, marketing applications and analytics related consulting services, announced today the winner of the 2013 Teradata University Network (TUN) Teaching Innovation Award. Associate Professor Michelle Cheong and Mr Murphy Choy from the School of Information Systems at Singapore Management University (SMU) received the Award for their teaching case on "Effective Use of Data & Decision Analytics to Improve Order Distribution in a Supply Chain".
Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee
Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee
Research Collection School Of Computing and Information Systems
Addressing issue of crowding in an Emergency Department (ED) typically takes the form of process engineering or single-faceted queue management strategies such as demand restriction, queue prioritization or staffing the ED. This work provides an integrated framework to manage queue dynamically from both demand and supply perspectives. More precisely, we introduce intelligent dynamic patient prioritization strategies to manage the demand concurrently with dynamic resource adjustment policies to manage supply. Our framework allows decision-makers to select both the demand-side and supply-side strategies to suit the needs of their ED. We verify through a simulation that such a framework improves the patients' …
Hibernating Process: Modeling Mobile Calls At Multiple Scales, Siyuan Liu, Lei Li, Ramayya Krishnan
Hibernating Process: Modeling Mobile Calls At Multiple Scales, Siyuan Liu, Lei Li, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
Do mobile phone calls at larger granularities behave in the same pattern as in smaller ones? How can we forecast the distribution of a whole month's phone calls with only one day's observation? There are many models developed to interpret large scale social graphs. However, all of the existing models focus on graph at one time scale. Many dynamical behaviors were either ignored, or handled at one scale. In particular new users might join or current users quit social networks at any time. In this paper, we propose HiP, a novel model to capture longitudinal behaviors in modeling degree distribution …