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Articles 6781 - 6810 of 9024

Full-Text Articles in Computer Sciences

Analyzing The Impact Of Cloud Services Brokers On Cloud Computing Markets, Richard D. Shang, Jianhui Huang, Yinping Yang, Robert J. Kauffman Jan 2013

Analyzing The Impact Of Cloud Services Brokers On Cloud Computing Markets, Richard D. Shang, Jianhui Huang, Yinping Yang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

This research offers a theoretical model of brokered services and provides an analysis of their impact on the cloud computing market with risk preference-based stratification of client segments. The model structures the decision problem that clients face when they choose among spot, reserved and brokered services. Although all the three types of services do not indemnify the cloud services client against other kinds of service outages, due to changes in market demand, service interruptions occur most frequently in the spot market, and are lower when brokered services are offered, and no risk of inter-ruption is involved in reserved services. Based …

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Sensor Feature Selection And Combination For Stress Identification Using Combinatorial Fusion, Yong Deng, Zhonghai Wu, Chao-Hsien Chu, Qixun Zhang, D. Frank Hsu Jan 2013

Sensor Feature Selection And Combination For Stress Identification Using Combinatorial Fusion, Yong Deng, Zhonghai Wu, Chao-Hsien Chu, Qixun Zhang, D. Frank Hsu

Research Collection School Of Computing and Information Systems

The identification of stressfulness under certain driving condition is an important issue for safety, security and health. Sensors and systems have been placed or implemented as wearable devices for drivers. Features are extracted from the data collected and combined to predict symptoms. The challenge is to select the feature set most relevant for stress. In this paper, we propose a feature selection method based on the performance and the diversity between two features. The feature sets selected are then combined using a combinatorial fusion. We also compare our results with other combination methods such as naïve Bayes, support vector machine, …

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State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu Jan 2013

State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu

Research Collection School Of Computing and Information Systems

Wireless sensor networks may be used to conduct critical tasks like fire detection or surveillance monitoring. It is thus important to guarantee the correctness of such systems by systematically analyzing their behaviors. Formal verification of wireless sensor networks is an extremely challenging task as the state space of sensor networks is huge, e.g., due to interleaving of sensors and intra-sensor interrupts. In this work, we develop a method to reduce the state space significantly so that state space exploration methods can be applied to a much smaller state space without missing a counterexample. Our method explores the nature of networked …

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Not All That Glitters Is Gold: The Effect Of Attention And Blogs On The Investors' Investing Behaviors, Nan Hu, Yi Dong, Ling Liu, Lee J. Yao Jan 2013

Not All That Glitters Is Gold: The Effect Of Attention And Blogs On The Investors' Investing Behaviors, Nan Hu, Yi Dong, Ling Liu, Lee J. Yao

Research Collection School Of Computing and Information Systems

This article investigates the relationship between a firm’s visibility in blogspaces, termed blog exposure, and the cross-sectional stock returns. We show that blog exposure is fundamentally different from the traditional media coverage, and securities with low blog exposure earn higher returns than stocks with high blog exposure. We further illustrate that such an effect is more prominent for stocks with low institutional ownership. Contrary to traditional media coverage, the return premium associated with blog exposure cannot be explained by either the illiquidity hypothesis or the investor recognition hypothesis based on the rational-agent framework. Instead, our results suggest that blog effect …

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Creating Scalable Location-Based Games: Lessons From Geocaching, Carman Neustaedter, Anthony Tang, Tejinder K. Judge Jan 2013

Creating Scalable Location-Based Games: Lessons From Geocaching, Carman Neustaedter, Anthony Tang, Tejinder K. Judge

Research Collection School Of Computing and Information Systems

Location-based games seek to move computer gaming out from behind the PC and into the “real world” of cities, streets, parks, and other locations. This real-world physicality makes the experience fun for game players, yet it brings the unique challenge of creating and orchestrating such a game. That is, location-based games are often difficult to create, grow, and maintain over long periods of time. Our research investigates how location-based games can be designed to overcome this challenge of scalability. We studied the well-established location-based game of Geocaching through active participation and an online survey to better understand how it has …

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Utility Of Potential Misdiagnoses In Predicting Foodborne Outbreaks, Lucia Lucia, Artur Dubrawski, Lujie Chen Jan 2013

Utility Of Potential Misdiagnoses In Predicting Foodborne Outbreaks, Lucia Lucia, Artur Dubrawski, Lujie Chen

Research Collection School Of Computing and Information Systems

To investigate utility of using inpatient and emergency room diagnoses to detect outbreaks of Salmonellosis in humans. To quantify the impact of including in the analysis cases diagnosed with conditions that may have physiological appearance similar to Salmonellosis.

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The Impact Of Smartphone Adoption On Consumers’ Switching Behavior In Broadband And Cable Tv Services, Gwangjae Jung Jan 2013

The Impact Of Smartphone Adoption On Consumers’ Switching Behavior In Broadband And Cable Tv Services, Gwangjae Jung

Research Collection School Of Computing and Information Systems

The emergence of smartphones has brought a technology disruption to the telecom business. Due to the various services offered in association with smartphones, people can surf the web or watch TV. This research is related to telecom services overall, and has the goal of finding the impact of smartphone adoption to consumers’ switching behavior in broadband and cable TV services. This research adopts a quasi-experimental design and investigates the causal effect of smartphone service adoption on broadband and cable TV service choices. The data collection involves five years of consumer service subscriptions in a Singaporean telecommunications company. I tested for …

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Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen Jan 2013

Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen

Research Collection School Of Computing and Information Systems

Community Question Answering (CQA) websites, where people share expertise on open platforms, have become large repositories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retrieve archived similar questions and recommend best answers to new questions. To tackle this cluster of closely related problems in a principled approach, we proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis. Based on TEM results, …

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Verifiable And Private Top-K Monitoring, Xuhua Ding, Hwee Hwa Pang Jan 2013

Verifiable And Private Top-K Monitoring, Xuhua Ding, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

In a data streaming model, records or documents are pushed from a data owner, via untrusted third-party servers, to a large number of users with matching interests. The match in interest is calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to the servers, which gives rise to the need to protect the privacy of the documents and user queries. In addition, the users need to guard against the eventuality of a server distorting the correlation score of the documents to manipulate which documents are highlighted to certain …

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Guardian: Hypervisor As Security Foothold For Personal Computers, Yueqiang Cheng, Xuhua Ding Jan 2013

Guardian: Hypervisor As Security Foothold For Personal Computers, Yueqiang Cheng, Xuhua Ding

Research Collection School Of Computing and Information Systems

Personal computers lack of a security foothold to allow the end-users to protect their systems or to mitigate the damage. Existing candidates either rely on a large Trusted Computing Base (TCB) or are too costly to widely deploy for commodity use. To fill this gap, we propose a hypervisor-based security foothold, named as Guardian, for commodity personal computers. We innovate a bootup and shutdown mechanism to achieve both integrity and availability of Guardian. We also propose two security utilities based on Guardian. One is a device monitor which detects malicious manipulation on camera and network adaptors. The other is hyper-firewall …

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Valuation Of Participation In Social Gaming, Kwansoo Kim, Byungjoon Yoo, Robert J. Kauffman Jan 2013

Valuation Of Participation In Social Gaming, Kwansoo Kim, Byungjoon Yoo, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

This study examines the value of the time that a user spends to participate in a social game. We focus on how a massive multiplayer online role-playing game (MMORPG) vendor can establish prices to encourage participation and retain its players. We estimate value through an application of the hedonic pricing model and analyze a data set for an MMORPG in Korea. The results permit us to estimate the value of game-playing time in monetary terms. Based on our empirical results, we propose an economic model and conduct numerical simulation to show how a game vendor can apply differential pricing in …

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Do Household Cable Tv Viewing Patterns Demonstrate Efficiency And Concentration?, Rae Chang, Pulak Ghosh, Gwangjae Jung, Robert J. Kauffman, Peiran Zhang Jan 2013

Do Household Cable Tv Viewing Patterns Demonstrate Efficiency And Concentration?, Rae Chang, Pulak Ghosh, Gwangjae Jung, Robert J. Kauffman, Peiran Zhang

Research Collection School Of Computing and Information Systems

No abstract provided.

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Improving Internet Security Through Information Disclosure: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston Jan 2013

Improving Internet Security Through Information Disclosure: 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 …

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Competition Between Software-As-A-Service Vendors, Robert J. Kauffman, Dan Ma Jan 2013

Competition Between Software-As-A-Service Vendors, Robert J. Kauffman, Dan Ma

Research Collection School Of Computing and Information Systems

No abstract provided.

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Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng Jan 2013

Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Social network has been touted as the No. 2 innovation in a recent IEEE Spectrum Special Report on “Top 11 Technologies of the Decade”, and it has cemented its status as a bona fide Internet phenomenon. With more and more people starting using social networks to share ideas, activities, events, and interests with other members within the network, social networks contain a huge amount of content. However, it might not be easy to navigate social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to …

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Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua Jan 2013

Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

Empowered by advances in information technology, such as social media network, digital library and mobile computing, there emerges an ever-increasing amounts of multimedia data. As the key technology to address the problem of information overload, multimedia recommendation system has been received a lot of attentions from both industry and academia. This course aims to 1) provide a series of detailed review of state-of-the-art in multimedia recommendation; 2) analyze key technical challenges in developing and evaluating next generation multimedia recommendation systems from different perspectives and 3) give some predictions about the road lies ahead of us.

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Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet Jan 2013

Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we seek robust policies for uncertain Markov Decision Processes (MDPs). Most robust optimization approaches for these problems have focussed on the computation of maximin policies which maximize the value corresponding to the worst realization of the uncertainty. Recent work has proposed minimax regret as a suitable alternative to the maximin objective for robust optimization. However, existing algorithms for handling minimax regret are restricted to models with uncertainty over rewards only. We provide algorithms that employ sampling to improve across multiple dimensions: (a) Handle uncertainties over both transition and reward models; (b) Dependence of model uncertainties across state, …

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Visual-Textual Joint Relevance Learning For Tag-Based Social Image Search, Yue Gao, Meng Wang, Zheng-Jun Zha, Jialie Shen, Xuelong Li, Xindong Wu Jan 2013

Visual-Textual Joint Relevance Learning For Tag-Based Social Image Search, Yue Gao, Meng Wang, Zheng-Jun Zha, Jialie Shen, Xuelong Li, Xindong Wu

Research Collection School Of Computing and Information Systems

With the popularity of social media websites, extensive research efforts have been dedicated to tag-based social image search. Both visual information and tags have been investigated in the research field. However, most existing methods use tags and visual characteristics either separately or sequentially in order to estimate the relevance of images. In this paper, we propose an approach that simultaneously utilizes both visual and textual information to estimate the relevance of user tagged images. The relevance estimation is determined with a hypergraph learning approach. In this method, a social image hypergraph is constructed, where vertices represent images and hyperedges represent …

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Mining Indirect Antagonistic Communities From Social Interactions, Kuan Zhang, David Lo, Ee Peng Lim, Philips Kokoh Prasetyo Jan 2013

Mining Indirect Antagonistic Communities From Social Interactions, Kuan Zhang, David Lo, Ee Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Antagonistic communities refer to groups of people with opposite tastes, opinions, and factions within a community. Given a set of interactions among people in a community, we develop a novel pattern mining approach to mine a set of antagonistic communities. In particular, based on a set of user-specified thresholds, we extract a set of pairs of communities that behave in opposite ways with one another. We focus on extracting a compact lossless representation based on the concept of closed patterns to prevent exploding the number of mined antagonistic communities. We also present a variation of the algorithm using a divide …

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Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo Jan 2013

Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo

Research Collection School Of Computing and Information Systems

This paper is concerned with automated classification of Combinatorial Optimization Problem instances for instance-specific parameter tuning purpose. We propose the CluPaTra Framework, a generic approach to CLUster instances based on similar PAtterns according to search TRAjectories and apply it on parameter tuning. The key idea is to use the search trajectory as a generic feature for clustering problem instances. The advantage of using search trajectory is that it can be obtained from any local-search based algorithm with small additional computation time. We explore and compare two different search trajectory representations, two sequence alignment techniques (to calculate similarities) as well as …

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Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui Jan 2013

Multimedia Recommendation: Technology And Techniques, Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui

Research Collection School Of Computing and Information Systems

In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history …

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Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan Jan 2013

Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Nowadays, content-based retrieval methods are still the development trend of the traditional retrieval systems. Image labels, as one of the most popular approaches for the semantic representation of images, can fully capture the representative information of images. To achieve the high performance of retrieval systems, the precise annotation for images becomes inevitable. However, as the massive number of images in the Internet, one cannot annotate all the images without a scalable and flexible (i.e., training-free) annotation method. In this paper, we particularly investigate the problem of accelerating sparse coding based scalable image annotation, whose off-the-shelf solvers are generally inefficient on …

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Uncertain Congestion Games With Assorted Human Agent Populations , Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng Jan 2013

Uncertain Congestion Games With Assorted Human Agent Populations , Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Congestion games model a wide variety of real-world resource congestion problems, such as selfish network routing, traffic route guidance in congested areas, taxi fleet optimization and crowd movement in busy areas. However, existing research in congestion games assumes: (a) deterministic movement of agents between resources; and (b) perfect rationality (i.e. maximizing their own expected value) of all agents. Such assumptions are not reasonable in dynamic domains where decision support has to be provided to humans. For instance, in optimizing the performance of a taxi fleet serving a city, movement of taxis can be involuntary or nondeterministic (decided by the specific …

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Symbolic Model-Checking Of Stateful Timed Csp Using Bdd And Digitization, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong Dec 2012

Symbolic Model-Checking Of Stateful Timed Csp Using Bdd And Digitization, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Stateful Timed CSP has been recently proposed to model (and verify) hierarchical real-time systems. It is an expressive modeling language which combines data structure/operations, complicated control flows (modeled using compositional process operators adopted from Timed CSP), and real-time requirements like deadline and within. It has been shown that Stateful Timed CSP is equivalent to closed timed automata with silent transitions, which implies that the timing constraints of Stateful Timed CSP can be captured using explicit tick events, through digitization. In order to tackle the state space explosion problem, we develop a BDD-based symbolic model checking approach to verify Stateful Timed …

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Investigating Intelligent Agents In A 3d Virtual World, Yilin Kang, Fiona Fui-Hoon Nah, Ah-Hwee Tan Dec 2012

Investigating Intelligent Agents In A 3d Virtual World, Yilin Kang, Fiona Fui-Hoon Nah, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Web 3.0 involves " intelligent " web applications that utilize natural language processing, machine-based learning and reasoning, and intelligent techniques to analyze and understand user behavior. In this research, we empirically assess a specific form of Web 3.0 application in the form of intelligent agents that offer assistance to users in the virtual world. Using media naturalness theory, we hypothesize that the use of intelligent agents in the virtual world can enhance user experience by offering a more natural way of communication and assistance to users. We are interested to test if media naturalness theory holds in the context of …

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Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah Dec 2012

Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Co-Space refers to interactive virtual environment modelled after the real world in terms of look-and-feel, functionalities and services. We have developed a 3D virtual world named Nanyang Technological University (NTU) CoSpace populated with virtual human characters. Three key requirements of realistic virtual humans in the virtual world have been identified, namely (1) autonomy: agents can function on their own; (2) interactivity: agents can interact naturally with players; and (3) personality: agents can exhibit human traits and characteristics. Working towards these challenges, we propose a brain-inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personality. We conducted an …

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Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin Dec 2012

Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

This paper studies the importance of visualization for discerning and interpreting patterns of data and its application for solving real problems, such as anomaly detection and data management. There are various ways to realize visualization to cater to the needs of numerous real life applications. Depending on needs, a combination of some of these ways may be required for presenting an effective visualization. The authors present visualization schemes for anomaly detection/condition monitoring and data management by leveraging network techniques and combining them with modern techniques such as sensor, database, mobile communication, GPS and GIS techniques. Two case studies are presented …

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Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng Dec 2012

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …

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Semi-Automated Verification Of Defense Against Sql Injection In Web Applications, Kaiping Liu, Hee Beng Kuan Tan, Lwin Khin Shar Dec 2012

Semi-Automated Verification Of Defense Against Sql Injection In Web Applications, Kaiping Liu, Hee Beng Kuan Tan, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Recent reports reveal that majority of the attacks to Web applications are input manipulation attacks. Among these attacks, SQL injection attack malicious input is submitted to manipulate the database in a way that was unintended by the applications' developers is one such attack. This paper proposes an approach for assisting to code verification process on the defense against SQL injection. The approach extracts all such defenses implemented in code. With the use of the proposed approach, developers, testers or auditors can then check the defenses extracted from code to verify their adequacy. We have evaluated the feasibility, effectiveness, and usefulness …

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Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan Dec 2012

Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Exploration is necessary during reinforcement learning to discover new solutions in a given problem space. Most reinforcement learning systems, however, adopt a simple strategy, by randomly selecting an action among all the available actions. This paper proposes a novel exploration strategy, known as Knowledge-based Exploration, for guiding the exploration of a family of self-organizing neural networks in reinforcement learning. Specifically, exploration is directed towards unexplored and favorable action choices while steering away from those negative action choices that are likely to fail. This is achieved by using the learned knowledge of the agent to identify prior action choices leading to …

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