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Full-Text Articles in Entire DC Network
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 …
Using Contracts To Guide The Search-Based Verification Of Concurrent Programs, Christopher M. Poskitt, Simon Poulding
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.
Applying Search In An Automatic Contract-Based Testing Tool, Alexey Kolesnichenko, Christopher M. Poskitt, Bertrand Meyer
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 …
The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim
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 …
Integration Of Social Media Technologies With Erp:A Prototype Implementation, Venky Shankararaman, Eng Kit Lum
Integration Of Social Media Technologies With Erp:A Prototype Implementation, Venky Shankararaman, Eng Kit Lum
Research Collection School Of Computing and Information Systems
Many organizations use social media to enhance collaboration both internally among employees and externally with customers and partners. However, it is not sufficient to just create a presence in some key social environments such as Facebook or YouTube. In order to fully leverage the value of social media, organizations must integrate social media with their business processes, which means new solutions have to be developed that extend existing enterprise systems. In this paper, we present a prototype solution that demonstrates the integration of social media with the order processing process. The implemented solution brings together the embedded best practice processes …
Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan
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 …
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Research Collection School Of Computing and Information Systems
With increased complexity, supply chain networks (SCNs) of modern era face higher risks and lower efficiency due to limited visibility. Hence, there is an immediate need to provide end-to-end supply chain visibility for efficient management of complex supply chains. This paper proposes a visualization scheme based on multi-hierarchical modular design and develops a supply chain visualization platform with risk management and real-time monitoring, named RiskVis, for realizing better Supply Chain Risk Management (SCRM). A Supply Chain Visualizer (SCV) with a graphical visualization platform is mounted as a part of a SCRM management decision-making dashboard and it provides senior management a …
Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Resource Allocation Policies, Kar Way Tan, Wei Hao Tan, Hoong Chuin Lau
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 …
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 …
Near-Duplicate Video Retrieval: Current Research And Future Trends, Jiajun Liu, Zi Huang, Hongyun Cai, Heng Tao Shen, Chong-Wah Ngo, Wei Wang
Near-Duplicate Video Retrieval: Current Research And Future Trends, Jiajun Liu, Zi Huang, Hongyun Cai, Heng Tao Shen, Chong-Wah Ngo, Wei Wang
Research Collection School Of Computing and Information Systems
The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of an already large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted …
Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo
Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns or relevant training examples from the initial search results. Ideally, these patterns and examples can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns and examples without understanding query is …
Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan
Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Three key requirements of realistic characters or agents in virtual world can be identified as autonomy, interactivity, and personification. Working towards these challenges, this paper proposes a brain inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personification. Based on self-organizing neural models, the agent architecture maintains explicit mental representation of desires, intention, personalities, self-awareness, situation awareness and user awareness. Autonomous behaviors are generated via evaluating the current situation with active goals and learning the most appropriate social or goal-directed rule from the available knowledge, in accordance with the personality of each individual agent. We have built …
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
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 …
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 …
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
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 …
Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau
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.
Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk
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 …
Automated Generation Of Interaction Graphs For Value-Factored Decentralized Pomdps, William Yeoh, Akshat Kumar, Shlomo Zilberstein
Automated Generation Of Interaction Graphs For Value-Factored Decentralized Pomdps, William Yeoh, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
The Decentralized Partially Observable Markov Decision Process (Dec-POMDP) is a powerful model for multi-agent planning under uncertainty, but its applicability is hindered by its high complexity – solving Dec-POMDPs optimally is NEXP-hard. Recently, Kumar et al. introduced the Value Factorization (VF) framework, which exploits decomposable value functions that can be factored into subfunctions. This framework has been shown to be a generalization of several specialized models such as TI-Dec-MDPs, ND-POMDPs and TD-POMDPs, which leverage different forms of sparse agent interactions to improve the scalability of planning. Existing algorithms for these models assume that the interaction graph of the problem is …
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 …
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 …
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 …
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
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social networks provide a wealth of data to study relationship dynamics among people. Most social networks such as Epinions and Facebook allow users to declare trusts or friendships with other users. Some of them also allow users to declare distrusts or negative relationships. When both positive and negative links co-exist in a network, some interesting community structures can be studied. In this work, we mine Direct Antagonistic Communities (DACs) within such signed networks. Each DAC consists of two sub-communities with positive relationships among members of each sub-community, and negative relationships among members of the other sub-community. Identifying direct antagonistic communities …
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 …
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 …
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.