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Articles 5671 - 5700 of 9024

Full-Text Articles in Computer Sciences

Accurate Online Video Tagging Via Probabilistic Hybrid Modeling, Jialie Shen, Meng Wang, Tat-Seng Chua Feb 2016

Accurate Online Video Tagging Via Probabilistic Hybrid Modeling, Jialie Shen, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Accurate video tagging has been becoming increasingly crucial for online video management and search. This article documents a novel framework called comprehensive video tagger (CVTagger) to facilitate accurate tag-based video annotation. The system applies both multimodal and temporal properties combined with a novel classification framework with hierarchical structure based on multilayer concept model and regression analysis. The advanced architecture enables effective incorporation of both video concept dependency and temporal dynamics. Using a large-scale test collection containing 50,000 YouTube videos, a set of empirical studies have been carried out and experimental results demonstrate various advantages of CVTagger over the state-of-the-art techniques.

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Ibed: Combining Ibea And De For Optimal Feature Selection In Software Product Line Engineering, Yinxing Xue, Jinghui Zhong, Tian Huat Tan, Yang Liu, Wentong Cai, Manman Chen, Jun Sun Jan 2016

Ibed: Combining Ibea And De For Optimal Feature Selection In Software Product Line Engineering, Yinxing Xue, Jinghui Zhong, Tian Huat Tan, Yang Liu, Wentong Cai, Manman Chen, Jun Sun

Research Collection School Of Computing and Information Systems

Software configuration, which aims to customize the software for different users (e.g., Linux kernel configuration), is an important and complicated task. In software product line engineering (SPLE), feature oriented domain analysis is adopted and feature model is used to guide the configuration of new product variants. In SPLE, product configuration is an optimal feature selection problem, which needs to find a set of features that have no conflicts and meanwhile achieve multiple design objectives (e.g., minimizing cost and maximizing the number of features). In previous studies, several multi-objective evolutionary algorithms (MOEAs) were used for the optimal feature selection problem and …

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Formalizing And Verifying Stochastic System Architectures Using Monterey Phoenix, Songzheng Song, Jiexin Zhang, Yang Liu, Mikhail Auguston, Jun Sun, Jin Song Dong, Tieming Chen Jan 2016

Formalizing And Verifying Stochastic System Architectures Using Monterey Phoenix, Songzheng Song, Jiexin Zhang, Yang Liu, Mikhail Auguston, Jun Sun, Jin Song Dong, Tieming Chen

Research Collection School Of Computing and Information Systems

The analysis of software architecture plays an important role in understanding the system structures and facilitate proper implementation of user requirements. Despite its importance in the software engineering practice, the lack of formal description and verification support in this domain hinders the development of quality architectural models. To tackle this problem, in this work, we develop an approach for modeling and verifying software architectures specified using Monterey Phoenix (MP) architecture description language. MP is capable of modeling system and environment behaviors based on event traces, as well as supporting different architecture composition operations and views. First, we formalize the syntax …

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Improved Egt-Based Robustness Analysis Of Negotiation Strategies In Multiagent Systems Via Model Checking, Songzheng Song, Jianye Hao, Yang Liu, Jun Sun, Ho-Fung Leung, Jie Zhang Jan 2016

Improved Egt-Based Robustness Analysis Of Negotiation Strategies In Multiagent Systems Via Model Checking, Songzheng Song, Jianye Hao, Yang Liu, Jun Sun, Ho-Fung Leung, Jie Zhang

Research Collection School Of Computing and Information Systems

Automated negotiations play an important role in various domains modeled as multiagent systems, where agents represent human users and adopt different negotiation strategies. Generally, given a multiagent system, a negotiation strategy should be robust in the sense that most agents in the system have the incentive to choose it rather than other strategies. Empirical game-theoretic (EGT) analysis is a game-theoretic analysis approach to investigate the robustness of different strategies based on a set of empirical results. In this study, we propose that model-checking techniques can be adopted to improve EGT analysis for negotiation strategies. The dynamics of strategy profiles can …

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Object Pooling For Multimedia Event Detection And Evidence Localization, Ho Zhang, Chong-Wah Ngo, Chong-Wah Ngo Jan 2016

Object Pooling For Multimedia Event Detection And Evidence Localization, Ho Zhang, Chong-Wah Ngo, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimedia event detection (MED) and evidence hunting are two primary topics in the area of multimedia event search. The former serves to retrieve a list of relevant videos given an event query, whereas, the latter reasons why and how much the degree a retrieved video answers that query. Common practices deal with these two topics in separate methods, however, in this paper, we combine MED and evidence hunting into a joint framework. We propose a refined semantical representation named object pooling which can dynamically extract visual snippets corresponding to the location of when and where evidences might appear. The main …

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Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp Jan 2016

Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp

Research Collection School Of Computing and Information Systems

To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider “quantified self“ movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the …

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A Study On Singapore Haze, Bingtian Dai, Kasthuri Jayarajah, Ee-Peng Lim, Archan Misra, Shriguru Nayak Jan 2016

A Study On Singapore Haze, Bingtian Dai, Kasthuri Jayarajah, Ee-Peng Lim, Archan Misra, Shriguru Nayak

Research Collection School Of Computing and Information Systems

In 2015, Singaporean have experienced one of the worse air pollution crises in history. With datasets from a well-known photo sharing social network, we analyze how this haze affects Singaporean's daily life. We will share our preliminary results in this paper.

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Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding Jan 2016

Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding

Research Collection School Of Computing and Information Systems

Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point (STIP) based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words (BoVW) model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, …

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We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni Jan 2016

We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni

Research Collection School Of Computing and Information Systems

Recent literature advances Wi-Fi signals to “see” people’s motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people’s talks leveraging MIMO technology. We …

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Towards A Science Of Security Games, Thanh Hong Nguyen, Debarun Kar, Matthew Brown, Arunesh Sinha, Albert Xin Jiang, Milind Tambe Jan 2016

Towards A Science Of Security Games, Thanh Hong Nguyen, Debarun Kar, Matthew Brown, Arunesh Sinha, Albert Xin Jiang, Milind Tambe

Research Collection School Of Computing and Information Systems

Security is a critical concern around the world. In many domains from counter-terrorism to sustainability, limited security resources prevent full security coverage at all times; instead, these limited resources must be scheduled, while simultaneously taking into account different target priorities, the responses of the adversaries to the security posture and potential uncertainty over adversary types.Computational game theory can help design such security schedules. Indeed, casting the problem as a Bayesian Stackelberg game, we have developed new algorithms that are now deployed over multiple years in multiple applications for security scheduling. These applications are leading to real-world use-inspired research in the …

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Regular Symmetry Patterns, Anthony W. Lin, Truong Khanh Nguyen, Philipp Rümmer, Jun Sun Jan 2016

Regular Symmetry Patterns, Anthony W. Lin, Truong Khanh Nguyen, Philipp Rümmer, Jun Sun

Research Collection School Of Computing and Information Systems

Symmetry reduction is a well-known approach for alleviating the state explosion problem in model checking. Automatically identifying symmetries in concurrent systems, however, is computationally expensive. We propose a symbolic framework for capturing symmetry patterns in parameterised systems (i.e. an infinite family of finite-state systems): two regular word transducers to represent, respectively, parameterised systems and symmetry patterns. The framework subsumes various types of “symmetry relations” ranging from weaker notions (e.g. simulation preorders) to the strongest notion (i.e. isomorphisms). Our framework enjoys two algorithmic properties: (1) symmetry verification: given a transducer, we can automatically check whether it is a symmetry pattern of …

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Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin Jan 2016

Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin

Research Collection School Of Computing and Information Systems

Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attention to these potentially problematic areas present in the drawing. this paper presents a technique that highlights common types of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge …

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Hidden Ciphertext Policy Attribute-Based Encryption Under Standard Assumptions, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo Jan 2016

Hidden Ciphertext Policy Attribute-Based Encryption Under Standard Assumptions, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

We propose two new ciphertext policy attributebased encryption (CP-ABE) schemes where the access policy is defined by AND-gate with wildcard. In the first scheme, we present a new technique that uses only one group element to represent an attribute, while the existing ABE schemes of the same type need to use three different group elements to represent an attribute for the three possible values (namely, positive, negative, and wildcard). Our new technique leads to a new CP-ABE scheme with constant ciphertext size, which, however, cannot hide the access policy used for encryption. The main contribution of this paper is to …

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A Tool-Free Calibration Method For Turntable-Based 3d Scanning Systems, Xufang Pang, Rynson W.H. Lau, Zhan Song, Shengfeng He, Shengfeng He Jan 2016

A Tool-Free Calibration Method For Turntable-Based 3d Scanning Systems, Xufang Pang, Rynson W.H. Lau, Zhan Song, Shengfeng He, Shengfeng He

Research Collection School Of Computing and Information Systems

Turntable-based 3D scanners are popular but require calibration of the turntable axis. Existing methods for turntable calibration typically make use of specially designed tools, such as a chessboard or criterion sphere, which users must manually install and dismount. In this article, the authors propose an automatic method to calibrate the turntable axis without any calibration tools. Given a scan sequence of the input object, they first recover the initial rotation axis from an automatic registration step. Then they apply an iterative procedure to obtain the optimized turntable axis. This iterative procedure alternates between two steps: refining the initial pose of …

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Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau Jan 2016

Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

A recent exploratory study on the collaborative urban logistics in Singapore suggests that cost reduction and privacy preservation are two main drivers that would motivate the participation of carriers in consolidating their last mile deliveries. With Singapore's mild restrictions on the vehicle types or the time windows for the last-mile delivery, we believe that with proper technology in place, an Urban Consolidation Center like the Tenjin Joint Distribution System in Fukuoka Japan may be implemented to achieve cost reduction with some degree of privacy preservation. Participating carriers keep their respective private orders and have the option to get their remaining …

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Smart Ambient Sound Analysis Via Structured Statistical Modeling, Jialie Shen, Liqiang Nie, Tat Seng Chua Jan 2016

Smart Ambient Sound Analysis Via Structured Statistical Modeling, Jialie Shen, Liqiang Nie, Tat Seng Chua

Research Collection School Of Computing and Information Systems

In this paper, we introduce a novel framework called SASA (Smart Ambient Sound Analyser) to support different ambient audio mining tasks (e.g., audio classification and location estimation). To gain comprehensive ambient sound modelling, SASA extracts a variety of acoustic features from different sound components (e.g., music, voice and background), and translates them into structured information. This significantly enhances quality of audio content representation. Further, distinguished from existing approaches, SASA’s multilayered architecture seamlessly integrates mixture models and aPEGASOS (adaptive PEGASOS) SVM algorithm into a unified classification framework. The approach can leverage complimentary strengths of both models. Experimental results based on three …

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On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim Jan 2016

On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Geotagged social media is becoming highly popular as social media access is now made very easy through a wide range of mobile apps which automatically detect and augment social media posts with geo-locations. In this paper, we analyze two kinds of location-based patterns. The first is the association between location attributes and the locations of user tweets. The second is location association pattern which comprises a pair of locations that are co-visited by users. We demonstrate that through tracking the Twitter data of Singapore-based users, we are able to reveal association between users tweeting from school locations and the school …

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Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan Jan 2016

Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan

Research Collection School Of Computing and Information Systems

We espouse a vision of small data-based immersive retail analytics, where a combination of sensor data, from personal wearable-devices and store-deployed sensors & IoT devices, is used to create real-time, individualized services for in-store shoppers. Key challenges include (a) appropriate joint mining of sensor & wearable data to capture a shopper’s product level interactions, and (b) judicious triggering of power-hungry wearable sensors (e.g., camera) to capture only relevant portions of a shopper’s in-store activities. To explore the feasibility of our vision, we conducted experiments with 5 smartwatch-wearing users who interacted with objects placed on cupboard racks in our lab (to …

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Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang Jan 2016

Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. …

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Press: Personalized Event Scheduling Recommender System (Demonstration), Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang Jan 2016

Press: Personalized Event Scheduling Recommender System (Demonstration), Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang

Research Collection School Of Computing and Information Systems

This paper presents a personalized event scheduling recom-mender system, PRESS, for a large conference setting with multiple parallel tracks. PRESS is a mobile application that gathers personalized information from a user and recommends talks/demos to be attend. The input from a user include a list of keyword preferences and (optionally) preferred talks. We use the MALLET topic model package to analyze the set of conference papers and classify them based on automatically identified topics. We propose an algorithm to generate a list of recommended papers based on the user keywords and the MALLET topics. An optimization model is then applied …

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Data Analytics On Consumer Behavior In Omni-Channel Retail Banking, Card And Payment Services, Geng Dan Jan 2016

Data Analytics On Consumer Behavior In Omni-Channel Retail Banking, Card And Payment Services, Geng Dan

Research Collection School Of Computing and Information Systems

Innovations in financial services have created challenges for banks that Information Systems (IS) research can address. My interests involve transaction cost theory, substitution and complementarity theory, and consumer informedness theory to understand consumer behavior and firm performance in the omni-channel world of digital banking. At a high level, my research inquiry asks: How can financial institutions take advantage of the deep insights that data analytics and management science modeling create on consumer behavior and channel management decision-making? And how can changes in payments and services in retail banking be understood in spatial and temporal terms? I am working on three …

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Online Arima Algorithms For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun Jan 2016

Online Arima Algorithms For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun

Research Collection School Of Computing and Information Systems

Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, which restricts its applications and makes it inefficient for handling large-scale real data. In this paper, we propose online learning algorithms for estimating ARIMA models under relaxed assumptions on the noise terms, which is suitable to a wider range of applications and enjoys high computational efficiency. The idea of our ARIMA method is to …

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Elderly Medication Adherence With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Hwee-Pink Tan, Hwee-Pink Tan Jan 2016

Elderly Medication Adherence With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Hwee-Pink Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

With the growth in elderly population in Singapore, healthcare expenditure and prevalence of age-related illnesses are expected to increase. Non-adherence among the elderly is a common issue that leads to adverse health complications, particularly among those with chronic conditions. However, existing studies typically focus on identifying predictors of medication adherence, and provide neither user-friendly nor actionable solutions that can be easily adopted by the elderly. In this paper, we use the Internet of Things to monitor medication adherence and detect changes in medication consumption patterns among the elderly, thus enabling timely interventions by caregivers to take place. Sensor-enabled medication boxes …

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Experience Me! The Impact Of Content Sampling Strategies On The Marketing Of Digital Entertainment Goods, Ai Phuong Hoang, Robert J. Kauffman Jan 2016

Experience Me! The Impact Of Content Sampling Strategies On The Marketing Of Digital Entertainment Goods, Ai Phuong Hoang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Product sampling allows consumers to try out a small portion of a product for free. Uncertainty associated with consumption of information goods makes sampling useful for digital entertainment providers. Firms offer some programming for free to attract consumers to purchase a series of programs. We explore the effectiveness of content sampling for information goods using a dataset containing more than 17 million free previews and purchase observations on households from a digital entertainment firm that offers video-on-demand (VoD). Based on theories related to product sampling and information goods, we analyze the relationship between free previews and VoD purchases for series …

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On Detecting Maximal Quasi Antagonistic Communities In Signed Graphs, Ming Gao, Ee-Peng Lim, David Lo, Philips Kokoh Prasetyo Jan 2016

On Detecting Maximal Quasi Antagonistic Communities In Signed Graphs, Ming Gao, Ee-Peng Lim, David Lo, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Many networks can be modeled as signed graphs. These include social networks, and relationships/interactions networks. Detecting sub-structures in such networks helps us understand user behavior, predict links, and recommend products. In this paper, we detect dense sub-structures from a signed graph, called quasi antagonistic communities (QACs). An antagonistic community consists of two groups of users expressing positive relationships within each group but negative relationships across groups. Instead of requiring complete set of negative links across its groups, a QAC allows a small number of inter-group negative links to be missing. We propose an algorithm, Mascot, to find all maximal quasi …

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Top-K Dominating Queries On Incomplete Data, Xiaoye Miao, Yunjun Gao, Baihua Zheng, Gang Chen, Huiyong Cui Jan 2016

Top-K Dominating Queries On Incomplete Data, Xiaoye Miao, Yunjun Gao, Baihua Zheng, Gang Chen, Huiyong Cui

Research Collection School Of Computing and Information Systems

The top-k dominating (TKD) query returns the k objects that dominate the maximum number of objects in a given dataset. It combines the advantages of skyline and top-k queries, and plays an important role in many decision support applications. Incomplete data exists in a wide spectrum of real datasets, due to device failure, privacy preservation, data loss, and so on. In this paper, for the first time, we carry out a systematic study of TKD queries on incomplete data, which involves the data having some missing dimensional value(s). We formalize this problem, and propose a suite of efficient algorithms for …

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An Extended Study On Addressing Defender Teamwork While Accounting For Uncertainty In Attacker Defender Games Using Iterative Dec-Mdps, Eric Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe Jan 2016

An Extended Study On Addressing Defender Teamwork While Accounting For Uncertainty In Attacker Defender Games Using Iterative Dec-Mdps, Eric Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

Multi-agent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multi-agent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork research in security games. The problem that this paper seeks to solve is the coordination of decentralized defender agents in the presence of uncertainty while securing targets against an observing adversary. To address this problem, we offer the following novel contributions in this paper: (i) New model of security games with defender teams that coordinate under uncertainty; (ii) New algorithm based on column …

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Synergizing Specification Miners Through Model Fissions And Fusions, Le Bui Tien Duy, Le Dinh Xuan Bach, David Lo, Ivan Beschastnikh Jan 2016

Synergizing Specification Miners Through Model Fissions And Fusions, Le Bui Tien Duy, Le Dinh Xuan Bach, David Lo, Ivan Beschastnikh

Research Collection School Of Computing and Information Systems

Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed techniques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification …

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Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim Jan 2016

Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We investigate the influence of offline friendship in three specific areas of Twitter networking behaviors: (a) network structure, (b) Twitter content and (c) interaction on Twitter. We observe some interesting findings through the empirical analysis of 2193 pairs of users who are online friends. When these pairs of users know each other offline, they are more likely to (1) respond to the online gesture of friendship from their friend, (2) share mutual online friends, (3) distribute and gather information in their friend’s Twitter network, (4) pay attention to their friend’s tweets, (5) post tweets that might be of interest to …

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Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu Jan 2016

Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Social media users make decisions about what content to post and read. As posted content is often visible to others, users are likely to impose self-censorship when deciding what content to post. On the other hand, such a concern may not apply to reading social media content. As a result, the topics of content that a user posted and read can be different and this has major implications to the applications that require personalization. To better determine and profile social media users’ topic interests, we conduct a user survey in Twitter. In this survey, participants chose the topics they like …

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