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Articles 6091 - 6120 of 8479
Full-Text Articles in Computer Sciences
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model dynamic phenomena such as the spread of information, wildlife, or social influence. Our work addresses the problem of learning the underlying parameters that govern such a diffusion process by observing the time at which nodes become active. A key advantage of our approach is that, unlike previous work, it can tolerate missing observations for some nodes in the diffusion process. Having incomplete observations is characteristic of offline networks used to model the spread of wildlife. We develop an EM algorithm to address parameter learning in such settings. Since both the E …
Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi
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, …
Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu
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 …
Robust Median Reversion Strategy For On-Line Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Steven Hoi, Shuigeng Zhou
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 …
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
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, …
An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen
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 …
Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models, Siyuan Liu, Yisong Yue, Ramayya Krishnan
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 …
Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu
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 …
Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang
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 …
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Research Collection School Of Computing and Information Systems
The open source movement has provided software users with more choices, lower software acquisition cost, more flexible software customization, and possibly higher quality software product. Although the development of open source software is dynamic and it encourages innovations, the process can be chaotic. An Open Source Software Development (OSSD) process model to enhance the survivability of OSSD projects is needed. This research uses the grounded theory approach to derive a Phase-Role-Skill-Responsibility (PRSR) OSSD process model. The three OSSD process phases -- Launch Stage, Before the First Release, and Between Releases -- address the characteristics of the OSSD process as well …
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Research Collection School Of Computing and Information Systems
Road traffic prediction is a critical component in modern smart transportation systems. It provides the basis for traffic management agencies to generate proactive traffic operation strategies for alleviating congestion. Existing work on near-term traffic prediction (forecasting horizons in the range of 5 minutes to 1 hour) relies on the past and current traffic conditions. However, once the forecasting horizon is beyond 1 hour, i.e., in longer-term traffic prediction, these techniques do not work well since additional factors other than the past and current traffic conditions start to play important roles.To address this problem, in this paper, for the first time, …
Performance Measurement Design For A Parcel Delivery Company, Junyu Choy, Nang Laik Ma, Ping Shung Koo
Performance Measurement Design For A Parcel Delivery Company, Junyu Choy, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
There were extensive researches on the topic of performance management in various organizations across multiple fields. Literature on performance measurements in logistics can be divided into specific measures and their application in the context or complete framework for performance measurements. In this paper, the focus of the discussion will be the formulation of the framework which handles performance measurements for package delivery service and how the metrics measure the performance and their application in the context of package delivery service.
Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo
Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Concept detection is probably the most important research problem in the area of multimedia. The need to model with sufficient and diverse training instances, however, makes the task computationally and resourcefully expensive. Meanwhile, the popularity of social media has generated massive amount of weakly tagged images which could be leveraged for concept model learning. Therefore, in this paper, we consider exploring weakly taggedWeb images to shed some light on video concept detection. Particularly, two sets of Web images downloaded from Flickr are utilized as training data for concept detection on two real-world large-scale video datasets released by TRECVID. Our experiments …
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Real-life vehicle routing problems comprise of a number of complexities that are not considered by the classical models found in vehicle routing literature. I present, in this paper, a two-stage sweep-based heuristic to find good solutions to a real-life Vehicle Routing Problem (VRP). The problem I shall consider, will deal with some non-standard constraints beyond those normally associated with the classical VRP. Other than considering the capacity constraints for vehicles and the time windows for deliveries, I shall introduce four additional non-standard constraints: merging of customer orders, controlling the maximum number of drop points, matching orders to vehicle types, and …
Improving Tool Support For Software Reverse Engineering In A Security Context, Brendan Cleary, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
Improving Tool Support For Software Reverse Engineering In A Security Context, Brendan Cleary, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
Research Collection School Of Computing and Information Systems
Illegal cyberspace activities are increasing rapidly and many software engineers are using reverse engineering methods to respond to attacks. The security-sensitive nature of these tasks, such as the understanding of malware or the decryption of encrypted content, brings unique challenges to reverse engineering: work has to be done offline, files can rarely be shared, time pressure is immense, and there is a lack of tool and process support for capturing and sharing the knowledge obtained while trying to understand assembly code. To help us gain an understanding of this reverse engineering work, we conducted an exploratory study at a government …
Psyhcos: Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong, Shang-Wei Lin
Psyhcos: Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong, Shang-Wei Lin
Research Collection School Of Computing and Information Systems
Real-time systems are often hard to control, due to their complicated structures, quantitative time factors and even unknown delays. We present here PSyHCoS, a tool for analyzing parametric real-time systems specified using the hierarchical modeling language PSTCSP. PSyHCoS supports several algorithms for parameter synthesis and model checking, as well as state space reduction techniques. Its architecture favors reusability in terms of syntax, semantics, and algorithms. It comes with a friendly user interface that can be used to edit, simulate and verify PSTCSP models. Experiments show its efficiency and applicability
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Research Collection School Of Computing and Information Systems
Testing provides a probabilistic assurance of system correctness. In general, testing relies on the assumptions that the system under test is deterministic so that test cases can be sampled. However, a challenge arises when a system under test behaves non-deterministiclly in a dynamic operating environment because it will be unknown how to sample test cases.In this work, we propose a method combining hypothesis testing and probabilistic model checking so as to provide the ``assurance" and quantify the error bounds. The idea is to apply hypothesis testing to deterministic system components and use probabilistic model checking techniques to lift the results …
Using Case Studies To Design And Deliver Technology-Centered Computing Education Courses: An Innovative Approach From An Undergraduate Information Systems Program In Singapore, Ilse Baumgartner
Research Collection School Of Computing and Information Systems
While the advantages of using case studies as an educational vehicle in computing education appear to be more than obvious, there is a very limited amount of research works or practice papers reporting on actual implementations of undergraduate or graduate computing courses which would be largely based on case studies. This conference contribution reports on selected best practices of course design and delivery implemented in one of the core courses of the Bachelor of Science (Information Systems Management) degree program (BSc (ISM)) offered by the School of Information Systems (SIS) at the Singapore Management University (SMU). Nearly all assessments, exercises, …
Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper we identify a novel query type, the top-K assignment query (αTop-K). Consider a set of objects and a set of suppliers, where each object must be assigned to one supplier. Assume that there is a cost associated with every object-supplier pair. If we allocate each object to the server with the smallest cost (for the specific object), the derived overall assignment will have the minimum total cost. In many scenarios, however, runner-up assignments may be required too, like for example when a decision maker needs to make additional considerations, not captured by individual object-supplier costs. In this …
Orion: A Software Project Search Engine With Integrated Diverse Software Artifacts, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Orion: A Software Project Search Engine With Integrated Diverse Software Artifacts, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Research Collection School Of Computing and Information Systems
Software projects produce a wealth of data that is leveraged in different tasks and for different purposes: researchers collect project data for building experimental datasets; software programmers reuse code from projects; developers often explore the opportunities for getting involved in the development of a project to gain or offer expertise. Finding relevant projects that suit one needs is however currently challenging with the capabilities of existing search systems. We propose Orion, an integrated search engine architecture that combines information from different types of software repositories from multiple sources to facilitate the construction and execution of advanced search queries. Orion provides …
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Research Collection School Of Computing and Information Systems
Programming languages have been proposed even before the era of the modern computer. As years have gone, computer resources have increased and application domains have expanded, leading to the proliferation of hundreds of programming languages, each attempting to improve over others or to address new programming paradigms. These languages range from procedural languages like C, object oriented languages like Java, and functional languages such as ML and Haskell. Unfortunately, there is a lack of large scale and comprehensive studies that examine the “popularity”, “interoperability”, and “impact” of various programming languages. To fill this gap, this study investigates a hundred thousands …
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Research Collection School Of Computing and Information Systems
Social network users connect and interact with one another to fulfil different kinds of social and information needs. When interaction ceases between two users, we say that their tie becomes dormant. While there are different underlying reasons of dormant ties, it is important to find means to revive such ties so as to maintain vibrancy in the relationships. In this work, we thus focus on designing an online experiment to evaluate the effectiveness of personalized social messages to revive dormant ties. The experiment carefully selects users with dormant ties so that no user gets mixed treatments and be affected by …
The Case For Mobile Forensics Of Private Data Leaks: Towards Large-Scale User-Oriented Privacy Protection, Joseph Joo Keng Chan, Kiat Wee Tan, Lingxiao Jiang, Rajesh Krishna Balan
The Case For Mobile Forensics Of Private Data Leaks: Towards Large-Scale User-Oriented Privacy Protection, Joseph Joo Keng Chan, Kiat Wee Tan, Lingxiao Jiang, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Privacy protection against mobile applications on mobile devices is becoming a serious concern as user sensitive data may be leaked without proper justification. Most current leak detection tools only report leaked private data, but provide inadequate information about the causes of the leaks for end users to take preventive measures. Hence, users often cannot reconcile the way they have used an application to a reported leak — i.e., they are unable to comprehend the (il)legitimacy of the leak or make a decision on whether to allow the leak. This paper aims to demonstrate the feasibility and benefits of identifying the …
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
Research Collection School Of Computing and Information Systems
While a large body of research has examined the advantages and disadvantages of modularity in product design, studies of modularization have tended to focus on settings in which a product’s architecture is determined by a single designer or designers within a single organization. In this paper, we ask whether modularity can arise in a decentralized setting where high-value designs are rewarded but designers’ ability to coordinate with each other and anticipate the consequences of their actions is limited—in short, whether modularity can evolve. To answer this question, we developed an agent-based model in which boundedly rational firms combine components into …
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Research Collection School Of Computing and Information Systems
This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real …
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Research Collection School Of Computing and Information Systems
Surveillance codestreams coded by H.264/SVC (scalable video coding), which consists of one base layer and one or more enhancement layers, supply flexible and various quality, resolution, and temporal (sub)codestreams such that clients with different network bandwidth and terminal devices can seamlessly access them. In this paper, we present a robust authentication scheme for them in order to insure the integrity of SVC surveillance codestreams, named AUSSC (Authenticating SVC Surveillance Codestreams). AUSSC exploits cryptographic-based authentication for base layer and content-based authentication for enhancement layers. For content-based authentication, AUSSC extracts full features from the first frame of each GOP (group of picture) …
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Research Collection School Of Computing and Information Systems
On a "marketplace" platform, where two sides of users trade, the platform owner has an incentive to regulate its marketplace for a higher profit. This study focuses on a monopoly platform's nonpricing, regulatory strategies in governing quality heterogeneity of competing sellers. In contrast to related studies, we endogenize strategic interactions among platform users. Our model extends the circular city model to capture seller heterogeneity in both variety and quality. The closed-form equilibrium solution reveals a ripple effect that exerts competitive pressure from seller to seller at a diminishing magnitude. The equilibrium analysis enables us to connect the economic mechanisms in …
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
In software engineering, testing is a crucial activity that is designed to ensure the quality of program code. For this activity, software teams spend substantial resources constructing test cases to thoroughly assess the correctness of software functionality. What is the proportion of open source projects that include test cases? What is the effect of number of developers on the number of test cases? In this study, we explore open source projects and investigate the correlation between the presence of test cases and various project development characteristics, including the number of lines of code, the size of development teams and the …
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
Research Collection School Of Computing and Information Systems
Build system converts source code, libraries and other data into executable programs by orchestrating the execution of compilers and other tools. The whole building process is managed by a software build system, such as Make, Ant, CMake, Maven, Scons, and QMake. The reliability of software build systems would affect the reliability of the build process. In this paper, we perform an empirical study on bugs in software build systems. We analyze four software build systems, Ant, Maven, CMake and QMake, which are four typical and widely-used software build systems, and can be used to build Java, C, C++ systems. We …
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.