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“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau Aug 2013

“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Queuing is a common phenomenon in theme parks which negatively affects visitor experience and revenue yields. There is thus a need for park operators to infer the real queuing delays without expensive investment in human effort or complex tracking infrastructure. In this paper, we depart from the classical queuing theory approach and provide a data-driven and online approach for estimating the time-varying queuing delays experienced at different attractions in a theme park. This work is novel in that it relies purely on empirical observations of the entry time of individual visitors at different attractions, and also accommodates the reality that …

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Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying Aug 2013

Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying

Research Collection School Of Computing and Information Systems

As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an "organized" way, such that we can gradually improve our PPV estimation in an incremental manner, and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub based realization, where we adopt the …

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The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim Aug 2013

The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim

Research Collection School Of Computing and Information Systems

Given that users are simultaneously connected in multiple communication channels in a social networking service site (e.g., chat, message, and group message), we explore user's collective networking behavior. We collected the data from a mobile social networking site with 4.8 million registered users. The empirical estimation shows interesting results: (1) there are cross-effects across the communication channels: substitute effects for "chat and message" and complementary effects for "message and group message" and "chat and group message" (2) there is significant local network effect but global network effect is not observed, (3) users utilize communication channels for different purposes according to …

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Volatility Occupation Times, Jia Li, Viktor Todorov, George Tauchen Aug 2013

Volatility Occupation Times, Jia Li, Viktor Todorov, George Tauchen

Research Collection School Of Economics

We propose nonparametric estimators of the occupation measure and the occupation density of the diffusion coefficient (stochastic volatility) of a discretely observed Itô semimartingale on a fixed interval when the mesh of the observation grid shrinks to zero asymptotically. In a first step we estimate the volatility locally over blocks of shrinking length, and then in a second step we use these estimates to construct a sample analogue of the volatility occupation time and a kernel-based estimator of its density. We prove the consistency of our estimators and further derive bounds for their rates of convergence. We use these results …

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Testing For Multiple Bubbles 2: Limit Theory Of Real Time Detectors, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu Aug 2013

Testing For Multiple Bubbles 2: Limit Theory Of Real Time Detectors, Peter C. B. Phillips, Shu-Ping Shi, Jun Yu

Research Collection School Of Economics

This paper provides the limit theory of real time dating algorithms for bubble detection that were suggested in Phillips, Wu and Yu (2011, PWY) and Phillips, Shi and Yu (2013b, PSY). Bubbles are modeled using mildly explosive bubble episodes that are embedded within longer periods where the data evolves as a stochastic trend, thereby capturing normal market behavior as well as exuberance and collapse. Both the PWY and PSY estimates rely on recursive right tailed unit root tests (each with a di§erent recursive algorithm) that may be used in real time to locate the origination and collapse dates of bubbles. …

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A Psychology Of Choice Of Laws, Gary Low Aug 2013

A Psychology Of Choice Of Laws, Gary Low

Research Collection Yong Pung How School Of Law

There is certainly a lot of choice going around in the market for contract law. This is a good thing, since choice is key to self-determination and may help improve our laws. Yet there may be such a thing as choice overload, and the introduction of the Common European Sales law is a timely reminder to consider its effect for the market for contract law. This article does just that. It explains what choice overload is, why it comes about, and what can be done to ameliorate its effects. The conclusion is that CESL will not cause choice overload but …

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An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, Loganathan Ponnanbalam, A. Tan, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh Aug 2013

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, Loganathan Ponnanbalam, A. Tan, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

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How Many Researchers Does It Take To Make Impact? Mining Software Engineering Publication Data For Collaboration Insights, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar Aug 2013

How Many Researchers Does It Take To Make Impact? Mining Software Engineering Publication Data For Collaboration Insights, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar

Research Collection School Of Computing and Information Systems

In the three and half decades since the inception of organized research publication in software engineering, the discipline has gained a significant maturity. This journey to maturity has been guided by the synergy of ideas, individuals and interactions. In this journey software engineering has evolved into an increasingly empirical discipline. Empirical sciences involve significant collaboration, leading to large teams working on research problems. In this paper we analyze a corpus of 19,000+ papers, written by 21,000+ authors from 16 publication venues between 1975 to 2010, to understand what is the ideal team size that has produced maximum impact in software …

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Robust Median Reversion Strategy For On-Line Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Steven Hoi, Shuigeng Zhou Aug 2013

Robust Median Reversion Strategy For On-Line Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Steven Hoi, Shuigeng Zhou

Research Collection School Of Computing and Information Systems

On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal …

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A Psychology Of Choice Of Laws, Gary Low Aug 2013

A Psychology Of Choice Of Laws, Gary Low

Research Collection Yong Pung How School Of Law

There is certainly a lot of choice going around in the market for contract law. This is a good thing, since choice is key to self-determination and may help improve our laws. Yet there may be such a thing as choice overload, and the introduction of the Common European Sales law is a timely reminder to consider its effect for the market for contract law. This article does just that. It explains what choice overload is, why it comes about, and what can be done to ameliorate its effects. The conclusion is that CESL will not cause choice overload but …

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Inconsistent Var Regression With Common Explosive Roots, Peter C. B. Phillips, Tassos Magdalinos Aug 2013

Inconsistent Var Regression With Common Explosive Roots, Peter C. B. Phillips, Tassos Magdalinos

Research Collection School Of Economics

Nielsen (Working paper, University of Oxford, 2009) shows that vector autoregression is inconsistent when there are common explosive roots with geometric multiplicity greater than unity. This paper discusses that result, provides a coexplosive system extension and an illustrative example that helps to explain the finding, gives a consistent instrumental variable procedure, and reports some simulations. Some exact limit distribution theory is derived and a useful new reverse martingale central limit theorem is proved.

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Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi Aug 2013

Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Malicious Uniform Resource Locator (URL) detection is an important problem in web search and mining, which plays a critical role in internet security. In literature, many existing studies have attempted to formulate the problem as a regular supervised binary classification task, which typically aims to optimize the prediction accuracy. However, in a real-world malicious URL detection task, the ratio between the number of malicious URLs and legitimate URLs is highly imbalanced, making it very inappropriate for simply optimizing the prediction accuracy. Besides, another key limitation of the existing work is to assume a large amount of training data is available, …

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Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu Aug 2013

Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) the …

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Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao Aug 2013

Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao

Research Collection School Of Computing and Information Systems

Automated face annotation aims to automatically detect human faces from a photo and further name the faces with the corresponding human names. In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW. Given a query facial image for annotation, the idea of SBFA is to first search for top-n similar facial images from a web facial image database and then exploit these top-ranked similar facial images and their weak labels for naming the query facial image. To fully mine those information, …

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Trial And Error In Influential Social Networks, Xiaohui Bei, Ning Chen, Liyu Dou, Xiangru Huang, Ruixin Qiang Aug 2013

Trial And Error In Influential Social Networks, Xiaohui Bei, Ning Chen, Liyu Dou, Xiangru Huang, Ruixin Qiang

Research Collection School Of Economics

In this paper, we introduce a trial-And-error model to study information diffusion in a social network. Specifically, in every discrete period, all individuals in the network concurrently try a new technology or product with certain respective probabilities. If it turns out that an individual observes a better utility, he will then adopt the trial; otherwise, the individual continues to choose his prior selection. We first demonstrate that the trial and error behavior of individuals characterizes certain global community structures of a social network, from which we are able to detect macro-communities through the observation of microbehavior of individuals. We run …

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Using Contracts To Guide The Search-Based Verification Of Concurrent Programs, Christopher M. Poskitt, Simon Poulding Aug 2013

Using Contracts To Guide The Search-Based Verification Of Concurrent Programs, Christopher M. Poskitt, Simon Poulding

Research Collection School Of Computing and Information Systems

Search-based techniques can be used to identify whether a concurrent program exhibits faults such as race conditions, deadlocks, and starvation: a fitness function is used to guide the search to a region of the program’s state space in which these concurrency faults are more likely occur. In this short paper, we propose that contracts specified by the developer as part of the program’s implementation could be used to provide additional guidance to the search. We sketch an example of how contracts might be used in this way, and outline our plans for investigating this verification approach.

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Applying Search In An Automatic Contract-Based Testing Tool, Alexey Kolesnichenko, Christopher M. Poskitt, Bertrand Meyer Aug 2013

Applying Search In An Automatic Contract-Based Testing Tool, Alexey Kolesnichenko, Christopher M. Poskitt, Bertrand Meyer

Research Collection School Of Computing and Information Systems

Automated random testing has been shown to be effective at finding faults in a variety of contexts and is deployed in several testing frameworks. AutoTest is one such framework, targeting programs written in Eiffel, an object-oriented language natively supporting executable pre- and postconditions; these respectively serving as test filters and test oracles. In this paper, we propose the integration of search-based techniques—along the lines of Tracey—to try and guide the tool towards input data that leads to violations of the postconditions present in the code; input data that random testing alone might miss, or take longer to find. Furthermore, we …

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Usmmc: A Self-Contained Model Checker For Uml State Machines, Shuang Liu, Yang Liu, Jun Sun, Manchun Zheng, Bimlesh Wadhwa, Jin Song Dong Aug 2013

Usmmc: A Self-Contained Model Checker For Uml State Machines, Shuang Liu, Yang Liu, Jun Sun, Manchun Zheng, Bimlesh Wadhwa, Jin Song Dong

Research Collection School Of Computing and Information Systems

UML diagrams are gaining increasing usage in Object-Oriented system designs. UML state machines are specifically used in modeling dynamic behaviors of classes. It has been widely agreed that verification of system designs at an early stage will dramatically reduce the development cost. Tool support for verification UML designs can also encourage consistent usage of UML diagrams throughout the software development procedure. In this work, we present a tool, named USMMC, which turns model checking of UML state machines into practice. USMMC is a self-contained toolkit, which provides editing, interactive simulation as well as powerful model checking support for UML state …

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Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu Aug 2013

Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation …

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An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen Aug 2013

An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen

Research Collection School Of Computing and Information Systems

In this paper, we analyze the network of expertise constructed from the interactions of users on the online questionanswering (QA) community of Stack Overflow. This community was built with the intention of helping users with their programming tasks and, thus, questions are expected to be highly factual. This also indicates that the answers one provides may be highly indicative of one's level of expertise on the subject matter. Therefore, our main concern is how to model and characterize the user's expertise based on the constructed network and its centrality measures. We used the user's reputation established on Stack Overflow as …

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Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models, Siyuan Liu, Yisong Yue, Ramayya Krishnan Aug 2013

Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models, Siyuan Liu, Yisong Yue, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

We consider the problem of adaptively routing a fleet of cooperative vehicles within a road network in the presence of uncertain and dynamic congestion conditions. To tackle this problem, we first propose a Gaussian Process Dynamic Congestion Model that can effectively characterize both the dynamics and the uncertainty of congestion conditions. Our model is efficient and thus facilitates real-time adaptive routing in the face of uncertainty. Using this congestion model, we develop an efficient algorithm for non-myopic adaptive routing to minimize the collective travel time of all vehicles in the system. A key property of our approach is the ability …

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Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang Aug 2013

Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Given a high-dimensional dataset, a top-k query can be used to shortlist the k tuples that best match the user’s preferences. Typically, these preferences regard a subset of the available dimensions (i.e., attributes) whose relative significance is expressed by user-specified weights. Along with the query result, we propose to compute for each involved dimension the maximal deviation to the corresponding weight for which the query result remains valid. The derived weight ranges, called immutable regions, are useful for performing sensitivity analysis, for finetuning the query weights, etc. In this paper, we focus on top-k queries with linear preference functions over …

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Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan Aug 2013

Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan

Research Collection School Of Computing and Information Systems

Mass Rapid Transit using rail is a popular mode of transport employed by millions of people in many urban cities across the world. Typically, these networks are massive, used by many and thus, can be a soft target for criminals. In this paper, we consider the problem of scheduling randomised patrols for improving security of such rail networks. Similar to existing work in randomised patrols for protecting critical infrastructure, we also employ Stackelberg Games to represent the problem. In solving the Stackelberg games for massive rail networks, we make two key contributions. Firstly, we provide an approach called RaPtoR for …

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A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan Aug 2013

A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan

Research Collection School Of Computing and Information Systems

Sustainable supply chain management has been an increasingly important topic of research in recent years. At the strategic level, there are computational models which study supply and distribution networks with environmental considerations. At the operational level, there are, for example, routing and scheduling models which are constrained by carbon emissions. Our paper explores work in tactical planning with regards to vehicle resource allocation from distribution centers to customer locations in a multi-echelon logistics network. We formulate the bi-objective optimization problem exactly and design a memetic algorithm to efficiently derive an approximate Pareto front. We illustrate the applicability of our approach …

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Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis Aug 2013

Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …

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Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau Aug 2013

Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The performance of a heuristic algorithm is highly dependent on its parameter configuration, yet finding a good parameter configuration is often a time-consuming task. In this paper we propose FloTra, a Flower graph mining for graph search Trajectory pattern extraction for generic instance-specific automated parameter tuning. This algorithm provides efficient extraction of compact and discriminative features of the search trajectory, upon which problem instances are clustered and the corresponding optimal parameter configurations are computed. Experimental evaluations of our approach on the Quadratic Assignment Problem (QAP) show that our approach offers promising improvement over existing parameter tuning algorithms. In this work, …

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Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng Aug 2013

Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of …

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Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau Aug 2013

Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The Orienteering Problem (OP), as originally defined by Tsiligirides, is the problem of cross-countr sport in which participants get rewards from visiting a predefined set of checkpoints. As Orienteering Problem can be used to describe a wide variety of real-world problems like route planning for facility inspection, patrolling of strategic location, and reward-weighted traveling salesman problem, it has attracted continuous interests from researchers and a large number of variants and corresponding algorithms for solving them have been introduced.

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Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk Aug 2013

Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk

Research Collection School Of Computing and Information Systems

In political contexts, it is known that people act as "motivated reasoners", i.e., information is evaluated first for emotional affect, and this emotional reaction influences later deliberative reasoning steps. As social media becomes a more and more prevalent way of receiving political information, it becomes important to understand more completely the interaction between information, emotion, social community, and information-sharing behavior. In this paper, we describe a high-precision classifier for politically-oriented tweets, and an accurate classifier of a Twitter user's political affiliation. Coupled with existing sentiment-analysis tools for microblogs, these methods enable us to systematically study the interaction of emotion and …

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Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Resource Allocation Policies, Kar Way Tan, Wei Hao Tan, Hoong Chuin Lau Aug 2013

Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Resource Allocation Policies, Kar Way Tan, Wei Hao Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this work, we consider the problem of allocating doctors in the ambulatory area of a hospital's emergency department (ED) based on a set of policies. Traditional staffing methods are static, hence do not react well to surges in patient demands. We study strategies that intelligently adjust the number of doctors based on current and historical information about the patient arrival. Our main contribution is our proposed data-driven online approach that performs adaptive allocation by utilizing historical as well as current arrivals by running symbiotic simulation in real-time. We build a simulation prototype that models ED process that is close …

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