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Articles 6631 - 6660 of 9024
Full-Text Articles in Computer Sciences
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
Research Collection School Of Computing and Information Systems
Threaded discussion forums provide an important social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot issues from forum threads is an important and useful task. In this paper, we propose a novel latent variable model for viewpoint discovery from threaded forum posts. Our model is a principled generative latent variable model which captures three important factors: viewpoint specific topic preference, user identity and user interactions. Evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering …
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. Experiments with two tasks show that the learned latent factor representation can give good performance on a relation polarity prediction task and improve the performance of a subgroup detection task.
Architectural Control And Value Migration In Layered Ecosystems: The Case Of Open-Source Cloud Management Platforms, Richard Tee, C. Jason Woodard
Architectural Control And Value Migration In Layered Ecosystems: The Case Of Open-Source Cloud Management Platforms, Richard Tee, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Our paper focuses on strategic decision making in layered business ecosystems, highlighting the role of cross-layer interactions in shaping choices about product design and platform governance. Based on evidence from the cloud computing ecosystem, we analyze how concerns about architectural control and expectations regarding future value migration influence the design of product interfaces and the degree of openness to external contributions. We draw on qualitative longitudinal data to trace the development of two open-source platforms for managing cloudbased computing resources. We focus in particular on the emergence of a layered "stack" in which these platforms must compete with both vertically …
When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim
When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim
Research Collection School Of Computing and Information Systems
This study is motivated by the premise that online consumers can make a purchase at any time of day if they have even a tiny time slot along with Internet access. To identify the increased shopping time flexibility, we first characterize the patterns of online purchase timing in comparison to those in the offline market. The results show (1) the breakdown of purchase timing regularity and (2) the change of weekly spike purchase occurrence. Second, we build online inter-purchase time model and estimate it with the data collected from one of the premier online vendors in Korea. We verify new …
Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter
Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter
Research Collection School Of Computing and Information Systems
This paper presents StopWatch , a system that defends against timing-based side-channel attacks that arise from coresidency of victims and attackers in infrastructure-as-a-service clouds. StopWatchtriplicates each cloud-resident guest virtual machine (VM) and places replicas so that the three replicas of a guest VM are coresident with nonoverlapping sets of (replicas of) other VMs. StopWatch uses thetiming of I/O events at a VM's replicas collectively to determine the timings observed by each one or by an external observer, so that observable timing behaviors are similarly likely in the absence of any other individual, coresident VM. We detail the design and implementation …
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
Approximate Inference In Collective Graphical Models, Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich
Approximate Inference In Collective Graphical Models, Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich
Research Collection School Of Computing and Information Systems
We study the problem of approximate inference in collective graphical models (CGMs), which were recently introduced to model the problem of learning and inference with noisy aggregate observations. We first analyze the complexity of inference in CGMs: unlike inference in conventional graphical models, exact inference in CGMs is NP-hard even for tree-structured models. We then develop a tractable convex approximation to the NP-hard MAP inference problem in CGMs, and show how to use MAP inference for approximate marginal inference within the EM framework. We demonstrate empirically that these approximation techniques can reduce the computational cost of inference by two orders …
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Enforcing Secure And Privacy-Preserving Information Brokering In Distributed Information Sharing, Fengjun Li, Bo Luo, Peng Liu, Dongwon Lee, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Today’s organizations raise an increasing need for information sharing via on-demand access. Information brokering systems (IBSs) have been proposed to connect large-scale loosely federated data sources via a brokering overlay, in which the brokers make routing decisions to direct client queries to the requested data servers. Many existing IBSs assume that brokers are trusted and thus only adopt server-side access control for data confidentiality. However, privacy of data location and data consumer can still be inferred from metadata (such as query and access control rules) exchanged within the IBS, but little attention has been put on its protection. In this …
Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta
Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta
Research Collection School Of Computing and Information Systems
Pair programming is a key characteristic of the Extreme Programming (XP) method. Through a controlled experiment we investigate pair programming behaviour of programmers without prior experience in XP. The factors investigated are: (a) characteristics of pair programming that are less favored (b) perceptions of team effectiveness and how they relate to product quality, and (c) whether it is better to train a pair by giving routine tasks first or by giving complex tasks first. Our results show that: (a) the least liked aspects of pair programming were having to share the screen, keyboard and mouse, and having to switch between …
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Cybersecurity is a national priority in this big data era. Because of negative externalities and the resulting lack of economic incentives, companies often underinvest in security controls, despite government and industry recommendations. Although many existing studies on security have explored technical solutions, only a few have looked at the economic motivations. To fill the gap, we propose an approach to increase the incentives of organizations to address security problems. Specifically, we utilize and process existing security vulnerability data, derive explicit security performance information, and disclose the information as feedback to organizations and the public. We regularly release information on the …
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this demo, we introduce SocioPhone, a novel initiative toward everyday face-to-face interaction monitoring platform. Among diverse verbal, aural, visual cues expressed during face-to-face interaction, SocioPhone captures diverse meta-linguistic information from conversations and provides interaction-aware applications on-the-fly. Undoubtedly, conversations are a key channel for face-to-face interaction. Specifically, monitoring conversational turns, i.e., alternation of different speakers (including none speaking), is the first crucial step to derive diverse interesting aspects of conversations, e.g., who is talking right now, how long and often one talks, how quickly one responds to another, and so on. In this demo, we will show the core technique …
Hunts: A Trajectory Recommendation System For Effective And Efficient Hunting Of Taxi Passengers, Ye Ding, Siyuan Liu, Jiansu Pu, Lionel Ni
Hunts: A Trajectory Recommendation System For Effective And Efficient Hunting Of Taxi Passengers, Ye Ding, Siyuan Liu, Jiansu Pu, Lionel Ni
Research Collection School Of Computing and Information Systems
Nowadays, there are many taxis traversing around the city searching for available passengers, but their hunts of passengers are not always efficient. To the dynamics of traffic and biased passenger distributions, current offline recommendations based on place of interests may not work well. In this paper, we define a new problem, global-optimal trajectory retrieving (GOTR), as finding a connected trajectory of high profit and high probability to pick up a passenger within a given time period in real-time. To tackle this challenging problem, we present a system, called HUNTS, based on the knowledge from both historical and online GPS data …
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
Research Collection School Of Computing and Information Systems
Nowadays, big cities are suffering from severe traffic congestion as a result of the continuing increase in vehicles. Taxis equipped with GPS can be viewed as sensors of the traffic situation in city. However, trajectory data generated by taxi’s GPS traces are often high-dimensional and contain large spatial and temporal attributes, which pose challenges for analysts. In this paper, based on taxi trajectory data, we present an interactive visual analytics system, T-Watcher, for monitoring and analyzing complex traffic situations in big cities. Users are able to use a carefully designed interface to monitor and inspect data interactively from three levels …
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
The execution of an agent's complex activities, comprising sequences of simpler actions, sometimes leads to the clash of conflicting functions that must be optimized. These functions represent satisfaction, short-term as well as long-term objectives, costs and individual preferences. The way that these functions are weighted is usually unknown even to the decision maker. But if we were able to understand the individual motivations and compare such motivations among individuals, then we would be able to actively change the environment so as to increase satisfaction and/or improve performance. In this work, we approach the problem of providing highlevel and intelligible descriptions …
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Discrete Time Markov Chains (DTMCs) are widely used to model probabilistic systems in many domains, such as biology, network and communication protocols. There are two main approaches for probability reachability analysis of DTMCs, i.e., solving linear equations or using value iteration. However, both approaches have drawbacks. On one hand, solving linear equations can generate accurate results, but it can be only applied to relatively small models. On the other hand, value iteration is more scalable, but often suffers from slow convergence. Furthermore, it is unclear how to parallelize (i.e., taking advantage of multi-cores or distributed computers) these two approaches. In …
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
Research Collection School Of Computing and Information Systems
UML is a widely used notation, and formalizing its semantics is an important issue. Here, we concentrate on formalizing UML state machines, used to express the dynamic behaviour of software systems. We propose a formal operational semantics covering all features of the latest version (2.4.1) of UML state machines specification. We use labelled transition systems as the semantic model, so as to use automatic verification techniques like model checking. Furthermore, our proposed semantics includes synchronous and asynchronous communications between state machines. We implement our approach in USM2C, a model checker supporting editing, simulation and automatic verification of UML state machines. …
Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou
Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou
Research Collection School Of Computing and Information Systems
iOS is Apple’s mobile operating system, which is used on iPhone, iPad and iPod touch. Any third-party applications developed for iOS devices are required to go through Apple’s application vetting process and appear on the official iTunes App Store upon approval.When an application is downloaded from the store and installed on an iOS device, it is given a limited set of privileges, which are enforced by iOS application sandbox. Although details of the vetting process and the sandbox are kept as black box by Apple, it was generally believed that these iOS security mechanisms are effective in defending against malwares. …
Energy-Efficient Collaborative Query Processing Framework For Mobile Sensing Services, Jin Yang, Tianli Mo, Lipyeow Lim, Kai Uwe Sattler, Archan Misra
Energy-Efficient Collaborative Query Processing Framework For Mobile Sensing Services, Jin Yang, Tianli Mo, Lipyeow Lim, Kai Uwe Sattler, Archan Misra
Research Collection School Of Computing and Information Systems
Many emerging context-aware mobile applications involve the execution of continuous queries over sensor data streams generated by a variety of on-board sensors on multiple personal mobile devices (aka smartphones). To reduce the energyoverheads of such large-scale, continuous mobile sensing and query processing, this paper introduces CQP, a collaborative query processing framework that exploits the overlap (in both the sensor sources and the query predicates) across multiple smartphones. The framework automatically identifies the shareable parts of multiple executing queries, and then reduces the overheads of repetitive execution and data transmissions, by having a set of 'leader' mobile nodes execute and disseminate …
Cugar: A Model For Open Innovation In Science And Technology Parks, Arcot Desai Narasimhalu
Cugar: A Model For Open Innovation In Science And Technology Parks, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper reviews key elements of a Science or Technology Park in the context of open innovation. Insights into and recommendations on key issues related to intellectual property, licensing and venture capital that would be of interest to any Science Park are presented later.
Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this paper, we propose SocioPhone, a novel initiative to build a mobile platform for face-to-face interaction monitoring. Face-to-face interaction, especially conversation, is a fundamental part of everyday life. Interaction-aware applications aimed at facilitating group conversations have been proposed, but have not proliferated yet. Useful contexts to capture and support face-to-face interactions need to be explored more deeply. More important, recognizing delicate conversational contexts with commodity mobile devices requires solving a number of technical challenges. As a first step to address such challenges, we identify useful meta-linguistic contexts of conversation, such as turn-takings, prosodic features, a dominant participant, and pace. …
Cameo: A Middleware For Mobile Advertisement Delivery, Azeem J. Khan, Kasthuri Jayarajah, Dongsu Han, Archan Misra, Rajesh Krishna Balan, Srinivasan Seshan
Cameo: A Middleware For Mobile Advertisement Delivery, Azeem J. Khan, Kasthuri Jayarajah, Dongsu Han, Archan Misra, Rajesh Krishna Balan, Srinivasan Seshan
Research Collection School Of Computing and Information Systems
Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users' critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more "user-friendly". To this end, we present the design and implementation of CAMEO, a …
Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng
Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Online Social Networks (OSNs) have become one of the major platforms for social interactions. Privacy control is deployed in popular OSNs to protect user’s data. However, user’s sensitive information could still be leaked even when privacy rules are properly configured. We investigate the effectiveness of privacy control against privacy leakage from the perspective of information flow. Our analysis reveals that the existing privacy control mechanisms do not protect the flow of personal information effectively. By examining typical OSNs including Facebook, Google+, and Twitter, we discover a series of privacy exploits which are caused by the conflicts between privacy control and …
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Research Collection School Of Computing and Information Systems
Event detection has been an important task for a long time. When it comes to Twitter, new problems are presented. Twitter data is a huge temporal data flow with much noise and various kinds of topics. Traditional sophisticated methods with a high computational complexity aren’t designed to handle such data flow efficiently. In this paper, we propose a mixture Gaussian model for bursty word extraction in Twitter and then employ a novel time-dependent HDP model for new topic detection. Our model can grasp new events, the location and the time an event becomes bursty promptly and accurately. Experiments show the …
A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu
A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu
Research Collection School Of Computing and Information Systems
Despite the wealth of research on frequent graph pattern mining, how to efficiently mine the complete set of those with constraints still poses a huge challenge to the existing algorithms mainly due to the inherent bottleneck in the mining paradigm. In essence, mining requests with explicitly-specified constraints cannot be handled in a way that is direct and precise. In this paper, we propose a direct mining framework to solve the problem and illustrate our ideas in the context of a particular type of constrained frequent patterns — the “skinny” patterns, which are graph patterns with a long backbone from which …
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Credit risk assessment for consumers has been a cornerstone of risk management in financial institutions and constitutes a component of the three pillars of Basel II. Traditionally, the concept of 5 ‘C’s was widely adopted by financial institutions as the key basis for credit risk assessment for loan applications by prospective borrowers. With the evolution of the credit risk management practices, more quantitative methods such as credit scorecards have been developed, which is implemented through the use of logistic regression, decision trees and neural networks. However, such approaches proved to be inadequate with the validity and effectiveness of the approaches …
Main-Stream Media Behaviour Analysis On Twitter: A Case Study On Uk General Election, Zhongyu Wei, Yulan He, Wei Gao, Binyang Li, Lanjun Zhou, Kam-Fai Wong
Main-Stream Media Behaviour Analysis On Twitter: A Case Study On Uk General Election, Zhongyu Wei, Yulan He, Wei Gao, Binyang Li, Lanjun Zhou, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
With the development of social media tools such as Facebook and Twitter, mainstream media organizations including newspapers and TV media have played an active role in engaging with their audience and strengthening their influence on the recently emerged platforms. In this paper, we analyze the behavior of mainstream media on Twitter and study how they exert their influence to shape public opinion during the UK's 2010 General Election. We first propose an empirical measure to quantify mainstream media bias based on sentiment analysis and show that it correlates better with the actual political bias in the UK media than the …
Dhl And Singapore Management University Launch Green Transformation Lab, Singapore Management University
Dhl And Singapore Management University Launch Green Transformation Lab, Singapore Management University
SMU Press Releases and News
DHL, the world’s leading logistics company, is partnering with Singapore Management University (SMU) to accelerate the evolution of sustainable logistics across Asia Pacific with the launch of the Green Transformation Lab. This S$2 million initiative, hosted at the SMU School of Information Systems on the University’s city campus, will focus on the creation of innovative solutions to help organizations transform their businesses towards sustainable green growth and drive beneficial change in supply chains across the region. This joint DHL-SMU initiative will fulfill its mission through education, research and best practice development.
Energy-Neutral Scheduling And Forwarding In Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Weng Seng Soh, Hwee-Pink Tan
Energy-Neutral Scheduling And Forwarding In Environmentally-Powered Wireless Sensor Networks, Alvin Cerdena Valera, Weng Seng Soh, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
In environmentally-powered wireless sensor networks (EPWSNs), low latency wakeup scheduling and packet forwarding is challenging due to dynamic duty cycling, posing time-varying sleep latencies and necessitating the use of dynamic wakeup schedules. We show that the variance of the intervals between receiving wakeup slots affects the expected sleep latency: when the variance of the intervals is low (high), the expected latency is low (high). We therefore propose a novel scheduling scheme that uses the bit-reversal permutation sequence (BRPS) – a finite integer sequence that positions receiving wakeup slots as evenly as possible to reduce the expected sleep latency. At the …
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …