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Articles 6031 - 6060 of 9024

Full-Text Articles in Computer Sciences

On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li Feb 2015

On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li

Research Collection School Of Computing and Information Systems

In this paper, for the first time, we identify and solve the problem of efficient reverse k-skyband (RkSB) query processing. Given a set P of multi-dimensional points and a query point q, an RkSB query returns all the points in P whose dynamic k-skyband contains q. We formalize RkSB retrieval, and then propose five algorithms for computing the RkSB of an arbitrary query point efficiently. Our methods utilize a conventional data-partitioning index (e.g., R-tree) on the dataset, and employ pre-computation, reuse and pruning techniques to boost the query efficiency. In addition, we extend our solutions to tackle an interesting variant …

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Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua Feb 2015

Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The vocabulary gap between health seekers and providers has hindered the cross-system operability and the interuser reusability. To bridge this gap, this paper presents a novel scheme to code the medical records by jointly utilizing local mining and global learning approaches, which are tightly linked and mutually reinforced. Local mining attempts to code the individual medical record by independently extracting the medical concepts from the medical record itself and then mapping them to authenticated terminologies. A corpus-aware terminology vocabulary is naturally constructed as a byproduct, which is used as the terminology space for global learning. Local mining approach, however, may …

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Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides Feb 2015

Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides

Research Collection School Of Computing and Information Systems

While biometrics have long been promoted as the future of authentication, the recent introduction of Android face unlock and iPhone fingerprint unlock are among the first large-scale deployments of biometrics for consumers. In a 10-participant, within-subjects lab study and a 198-participant online survey, we investigated the usability of these schemes, along with users ’ experiences, attitudes, and adoption decisions. Participants in our lab study found both face unlock and fingerprint unlock easy to use in typical scenarios. The notable exception was that face unlock was completely unusable in a dark room. Most participants preferred fingerprint unlock over face unlock or …

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Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng Feb 2015

Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng

Research Collection School Of Computing and Information Systems

Password leakage is one of the most serious threats for password-based user authentication. Although this problem has been extensively investigated over the last two decades, there is still no widely adopted solution. In this paper, we attempt to systematically understand the challenges behind this problem and investigate the feasibility of solving it. Since password leakage usually happens when a password is input during authentication, we focus on designing leakage-resilient password entry (LRPE) schemes in this study. We develop a broad set of design criteria and use them to construct a practical LRPE scheme named CoverPad, which not only improves leakage …

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Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas Feb 2015

Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Micro-reviews is a new type of user-generated content arising from the prevalence of mobile devices and social media in the past few years. Micro-reviews are bite-size reviews (usually under 200 characters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. However, the abundance of micro-reviews, and their telegraphic nature make it increasingly difficult to go through them and extract the useful information, especially on a mobile device. In this paper, we address the problem of summarizing the micro-reviews of …

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Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao Feb 2015

Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

With the popularity of smart phones and mobile devices, the number of mobile applications (a.k.a. "apps") has been growing rapidly. Detecting semantically similar apps from a large pool of apps is a basic and important problem, as it is beneficial for various applications, such as app recommendation, app search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem. In order to fill this gap, in this paper, we explore multi-modal heterogeneous data in app markets (e.g., description text, images, user reviews, etc.), and present "SimApp" -- a novel framework for detecting similar …

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Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong Feb 2015

Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong

Research Collection School Of Computing and Information Systems

With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according …

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Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman Feb 2015

Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman

Research Collection School Of Computing and Information Systems

Recommender systems are widely used by online retailers to promote products and content that are most likely to be of interest to a specific customer. In such systems, users often implicitly or explicitly rate products they have consumed, and some form of collaborative filtering is used to find other users with similar tastes to whom the products can be recommended. While users can benefit from more targeted and relevant recommendations, they are also exposed to greater risks of privacy loss, which can lead to undesirable financial and social consequences. The use of obfuscation techniques to preserve the privacy of user …

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Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade Feb 2015

Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade

Research Collection School Of Computing and Information Systems

Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of …

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Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang Feb 2015

Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang

Research Collection School Of Computing and Information Systems

In a recent paper (BioMed Research International, 2013/491289), Khan et al. proposed an improved biometrics-based remote user authentication scheme with user anonymity. The scheme is believed to be secure against password guessing attack, user impersonation attack, server masquerading attack, and provide user anonymity, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Khan et al.’s scheme, and demonstrate that their scheme doesn’t provide user anonymity. This also renders that their scheme is insecure against other attacks, such as off-line password guessing attack, user impersonation attacks. Subsequently, we propose a …

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The Power Of Technology In Cre Data And Analytics, Clarence Goh Jan 2015

The Power Of Technology In Cre Data And Analytics, Clarence Goh

Research Collection School of Accountancy

Many companies are using data to drive competitiveadvantage. Across industries, there is rapidly growingappreciation that data-driven insights can substantiallyimprove decision making across a wide range of businessfunctions, and corporate real estate (CRE) is no exception.

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Multimodal Code Search, Shaowei Wang Jan 2015

Multimodal Code Search, Shaowei Wang

Dissertations and Theses Collection (Open Access)

Today’s software is large and complex, consisting of millions of lines of code. New developers of a software project always face significant challenges in finding code related to their development or maintenance tasks (e.g., implementing features, fixing bugs and adding new features). In fact, research has shown that developers typically spend more time on locating and understanding code than modifying it. Thus, we can significantly reduce the cost of software development and maintenance by reducing the time to search and understand code relevant to a software development or maintenance task. In order to reduce the time of searching and understanding …

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Mining User Viewpoints In Online Discussions, Minghui Qiu Jan 2015

Mining User Viewpoints In Online Discussions, Minghui Qiu

Dissertations and Theses Collection (Open Access)

Online discussion forums are a type of social media which contains rich usercontributed facts, opinions, and user interactions on diverse topics. The large volume of opinionated data generated in online discussions provides an ideal testbed for user opinion mining. In particular, mining user opinions on social and political issues from online discussions is useful not only to government organizations and companies but also to social and political scientists. In this dissertation, we propose to study the task of mining user viewpoints or stances from online discussions on social and political issues. Specifically, we will talk about our proposed approaches for …

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Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma Jan 2015

Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma

Research Collection School Of Computing and Information Systems

Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website’s profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it …

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Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter Jan 2015

Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter

Research Collection School Of Computing and Information Systems

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, much fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic …

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Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang Jan 2015

Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang

Research Collection School Of Computing and Information Systems

The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …

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Automatic, High Accuracy Prediction Of Reopened Bugs, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Bo Zhou Jan 2015

Automatic, High Accuracy Prediction Of Reopened Bugs, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Bo Zhou

Research Collection School Of Computing and Information Systems

Bug fixing is one of the most time-consuming and costly activities of the software development life cycle. In general, bugs are reported in a bug tracking system, validated by a triage team, assigned for someone to fix, and finally verified and closed. However, in some cases bugs have to be reopened. Reopened bugs increase software maintenance cost, cause rework for already busy developers and in some cases even delay the future delivery of a software release. Therefore, a few recent studies focused on studying reopened bugs. However, these prior studies did not achieve high performance (in terms of precision and …

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Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman Jan 2015

Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman

Research Collection School Of Computing and Information Systems

The title of this year;s special section of selected papers, whose initial versionswere presented at the “Economics and Electronic Commerce,” and “Information Technologyand Competitive Strategy” mini-tracks of the 2001 Hawaii International Conferenceon Systems Science (HICSS), reflects the increasing convergence of ideas fromEconomics and Information Systems (IS) research. This convergence has been occurringover the last several years and is related to the developments in e-commerce. ISresearch has been rapidly coming of age, driven by the ever-increasing importance ofinformation technology (IT) in the marketplace, and the need for managers, investors,policy-makers, and the public to understand how to more effectively navigate in ourhighly …

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Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam Jan 2015

Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam

Research Collection School Of Computing and Information Systems

Abstract:The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …

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Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang Jan 2015

Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang

Research Collection School Of Computing and Information Systems

Crowdsourcing systems leverage short bursts of focusedattention from many contributors to achieve a goal. Byrequiring people’s full attention, existing crowdsourcingsystems fail to leverage people’s cognitive surplus in themany settings for which they may be distracted, performingor waiting to perform another task, or barely payingattention. In this paper, we study opportunities for loweffortcrowdsourcing that enable people to contribute toproblem solving in such settings. We discuss the designspace for low-effort crowdsourcing, and through a seriesof prototypes, demonstrate interaction techniques, mechanisms,and emerging principles for enabling low-effortcrowdsourcing.

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Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma Jan 2015

Mechanism Design For Near Real-Time Retail Payment And Settlement Systems, Zhiling Guo, Robert John Kauffman, Mei Lin, Dan Ma

Research Collection School Of Computing and Information Systems

have made extensive use of interbank netting systems, in which payments are accumulated for end-of-day settlement. This approach, known as deferred net settlement (DNS), reduces the liquidity needs of a payment system, but bears inherent operational risks. As large dollar volumes of retail payments accumulate swiftly, real-time gross settlement (RTGS) is an attractive option. It permits immediate settlement of transactions during the day, but it brings up other risks that require consideration. We propose a hybrid payment management system involving elements of both DNS and RTGS. We explore several hybrid system mechanism designs to allow payment prioritization, reduce payment delays, …

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Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim Jan 2015

Reputationpro: The Efficient Approaches To Contextual Transaction Trust Computation In E-Commerce Environments, Haibin Zhang, Yan Wang, Xiuzhen Zhang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In e-commerce environments, the trustworthiness of a seller is utterly important to potential buyers, especially when a seller is not known to them. Most existing trust evaluation models compute a single value to reflect the general trustworthiness of a seller without taking any transaction context information into account. With such a result as the indication of reputation, a buyer may be easily deceived by a malicious seller in a transaction where the notorious value imbalance problem is involved—in other words, a malicious seller accumulates a high-level reputation by selling cheap products and then deceives buyers by inducing them to purchase …

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Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng Jan 2015

Software Puzzle: A Countermeasure To Resource-Inflated Denial-Of-Service Attacks, Yongdong Wu, Zhigang Zhao, Bao Feng, Robert H. Deng

Research Collection School Of Computing and Information Systems

Denial-of-service (DoS) and distributed DoS (DDoS) are among the major threats to cyber-security, and client puzzle, which demands a client to perform computationally expensive operations before being granted services from a server, is a well-known countermeasure to them. However, an attacker can inflate its capability of DoS/DDoS attacks with fast puzzle-solving software and/or built-in graphics processing unit (GPU) hardware to significantly weaken the effectiveness of client puzzles. In this paper, we study how to prevent DoS/DDoS attackers from inflating their puzzle-solving capabilities. To this end, we introduce a new client puzzle referred to as software puzzle. Unlike the existing client …

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Recovering Household Preferences For Digital Entertainment, Jin Li, Zhiling Guo, Robert J. Kauffman Jan 2015

Recovering Household Preferences For Digital Entertainment, Jin Li, Zhiling Guo, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Cable TV return path data made possible by current generation set-top boxes present a new opportunity to analyze household viewing behavior and recover household viewing preferences from it. This research develops a model of household viewing preference that supports quantifying a household's valuation for different categories of digital content within the constraints of the programs to which it subscribes. This study uses a data set of more than 1 million observations on households from a digital entertainment firm that offers basic and premium services. Our estimation is via a Bayesian hierarchical model that employs the Gibbs sampler. The results show …

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Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu Jan 2015

Multidimensional Context Awareness In Mobile Devices, Zhuo Wei, Robert H. Deng, Jialie Shen, Jixiang Zhu, Kun Ouyang, Yongdong Wu

Research Collection School Of Computing and Information Systems

With the increase of mobile computation ability and the development of wireless network transmission technology, mobile devices not only are the important tools of personal life (e.g., education and entertainment), but also emerge as indispensable "secretary" of business activities (e.g., email and phone call). However, since mobile devices could work under complex and dynamic local and network conditions, they are vulnerable to local and remote security attacks. In real applications, different kinds of data protection are required by various local contexts. To provide appropriate protection, we propose a multidimensional context (MContext) scheme to comprehensively model and characterize the scene and …

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Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei Jan 2015

Travel Recommendation Via Author Topic Model Based Collaborative Filtering, Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei

Research Collection School Of Computing and Information Systems

While automatic travel recommendation has attracted a lot of attentions, the existing approaches generally suffer from different kinds of weaknesses. For example, sparsity problem can significantly degrade the performance of traditional collaborative filtering (CF). If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information. Motivated by this concern, we propose an Author Topic Collaborative Filtering (ATCF) method to facilitate comprehensive Points of Interest (POIs) recommendation for social media users. In our approach, the topics about user preference (e.g., cultural, cityscape, or landmark) are extracted from the textual description of …

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Improving Internet Security Through Mandatory Information Disclosure, Qian Tang, Andrew B. Whinston Jan 2015

Improving Internet Security Through Mandatory Information Disclosure, Qian Tang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

Although disclosure has long been considered as a solution to internalize externalities, mandatory security information disclosure is still in debate. We propose a mandatory disclosure mechanism based on existing data. The information is disclosed as straightforward rankings of organizations for users to understand, interpret, and make comparisons. As a result, the disclosure can influence organizations through reputational effects. We created a public website to disclose information regularly and conducted a quasi-experiment on outgoing spam to test the effectiveness of our mechanism on four matched country groups. For each treated country, we released the ranking list of top 10 most spamming …

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An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong Jan 2015

An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Research Collection School Of Computing and Information Systems

Learning for maximizing AUC performance is an important research problem in machine learning. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass online learning approaches. Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple stochastic gradient descent approaches, which fail to exploit the geometry knowledge of the data observed in the online learning process, and thus could suffer from relatively slow convergence. To overcome the limitation of the existing studies, in this paper, we propose a …

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The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang Jan 2015

The Knowledge Accumulation And Transfer In Open-Source Software (Oss) Development, Youngsoo Kim, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

We examine the learning curves of individual software developers in Open-Source Software (OSS) Development. We collected the dataset of multi-year code change histories from the repositories for 20 open source software projects involving more than 200 developers. We build and estimate regression models to assess individual developers' learning progress (in reducing the likelihood they make a bug). Our estimation results show that developer's coding and indirect bug-fixing experiences do not decrease bug ratios while bug-fixing experience can lead to the decrease of bug ratio of learning progress. We also find that developer's coding and bug-fixing experiences in other projects do …

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Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong Jan 2015

Multi-User Multiple Input Multiple Output (Mimo) Communication With Distributed Antenna Systems In Wireless Networks, Karthikeyan Sundaresan, Mohammad Khojastepour, Sampath Rangarajan, Jie Xiong

Research Collection School Of Computing and Information Systems

A system and a method are provided. The method includes deploying a plurality of antennas of an access point or a base station as a distributed antenna system. The method further includes configuring the distributed antenna system for multi-user wireless transmissions by applying medium access techniques and power-balanced pre-coding at the access point or the base station. The method also includes providing device localization for devices communicating with the distributed antenna system by applying time-difference-of-arrival techniques to antenna pairs from among the plurality of antennas at the access point or the base station.

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