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Articles 4981 - 5010 of 8481
Full-Text Articles in Computer Sciences
Probabilistic Robust Route Recovery With Spatio-Temporal Dynamics, Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang
Probabilistic Robust Route Recovery With Spatio-Temporal Dynamics, Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang
Research Collection School Of Computing and Information Systems
Vehicle trajectories are one of the most important data in location-based services. The quality of trajectories directly affects the services. However, in the real applications, trajectory data are not always sampled densely. In this paper, we study the problem of recovering the entire route between two distant consecutive locations in a trajectory. Most existing works solve the problem without using those informative historical data or solve it in an empirical way. We claim that a data-driven and probabilistic approach is actually more suitable as long as data sparsity can be well handled. We propose a novel route recovery system in …
Revocable And Decentralized Attribute-Based Encryption, Hui Cui, Deng, Robert H.
Revocable And Decentralized Attribute-Based Encryption, Hui Cui, Deng, Robert H.
Research Collection School Of Computing and Information Systems
In this paper, we propose a revocable and decentralized attribute-based encryption (ABE) system that splits the task of decryption key generation across multiple attribute authorities (AAs) without requiring any central party such that it achieves attribute revocation by simply stopping updating of the corresponding private key. In our system, a party can easily behave as an AA by creating a public and private key pair without any global communication except the creation for the common system parameters, under which it can periodically issue/update private key components for users that reflect their attributes, and an AA can freely leave the system …
New Developments In Metaheuristics And Their Applications: Selected Extended Contributions From The 10th Metaheuristics International Conference (Mic 2013), Hoong Chuin Lau, Günther R. Raidl, Pascal Van Hentenryck
New Developments In Metaheuristics And Their Applications: Selected Extended Contributions From The 10th Metaheuristics International Conference (Mic 2013), Hoong Chuin Lau, Günther R. Raidl, Pascal Van Hentenryck
Research Collection School Of Computing and Information Systems
No abstract provided.
Tafloc: Time-Adaptive And Fine-Grained Device-Free Localization With Little Cost, Liqiong Chang, Jie Xiong, Xiaojiang Chen, Ju Wang, Junhao Hu, Wei Wang
Tafloc: Time-Adaptive And Fine-Grained Device-Free Localization With Little Cost, Liqiong Chang, Jie Xiong, Xiaojiang Chen, Ju Wang, Junhao Hu, Wei Wang
Research Collection School Of Computing and Information Systems
Many emerging applications drive the needs of device-free localization (DfL), in which the target can be localized without any device attached. Because of the ubiquitousness of WiFi infrastructures nowadays, the widely available Received Signal Strength (RSS) information at the WiFi Access points are commonly employed for localization purposes. However, current RSS based DfL systems have one main drawback hindering their real-life applications. That is, the RSS measurements (fingerprints) vary slowly in time even without any change in the environment and frequent updates of RSS at each location lead to a high human labor cost. In this paper, we propose an …
A Fast Algorithm For Personalized Travel Planning Recommendation, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
A Fast Algorithm For Personalized Travel Planning Recommendation, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
Research Collection School Of Computing and Information Systems
With the pervasive use of recommender systems and web/mobile applications such as TripAdvisor and Booking.com, an emerging interest is to generate personalized tourist routes based on a tourist’s preferences and time budget constraints, often in real-time. The problem is generally known as the Tourist Trip Design Problem (TTDP) which is a route-planning problem on multiple Points of Interest (POIs). TTDP can be considered as an extension of the classical problem of Team Orienteering Problem with Time Windows (TOPTW). The objective of the TOPTW is to determine a fixed number of routes that maximize the total collected score. The TOPTW also …
Social Sentiment And Stock Trading Via Mobile Phones, Kwansoo Kim, Sang Yong Lee, Robert John Kauffman
Social Sentiment And Stock Trading Via Mobile Phones, Kwansoo Kim, Sang Yong Lee, Robert John Kauffman
Research Collection School Of Computing and Information Systems
What happens when uninformed investors trade stocks via mobile phones? Do they react to social sentiment differently than more informed traders in traditional trading? Based on 16,817 data observations and econometric analysis for the trading of 251 equities in Korea over 39 days, we present evidence of herding behavior among uninformed traders in the mobile channel. The results indicate that mobile traders seem more easily swayed by changing social sentiment. In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. Mobile traders follow signals in social media suggesting that they engage in less beneficial …
Detecting Communities Using Coordination Games: A Short Paper, Radhika Arava, Pradeep Varakantham
Detecting Communities Using Coordination Games: A Short Paper, Radhika Arava, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Communities typically capture homophily as people of the same community share many common features. This paper is motivated by the problem of community detection in social networks, as it can help improve our understanding of the network topology. Given the selfish nature of humans to align with like-minded people, we employ game theoretic models and algorithms to detect communities in this paper. Specifically, we employ coordination games to represent interactions between individuals in a social network. We provide a novel and scalable two phased algorithm NashOverlap to compute an accurate overlapping community structure in the given network. We evaluate our …
Fine-Grained Appliance Usage And Energy Monitoring Through Mobile And Power-Line Sensing, Nirmalya Roy, Nilavra Pathak, Archan Misra
Fine-Grained Appliance Usage And Energy Monitoring Through Mobile And Power-Line Sensing, Nirmalya Roy, Nilavra Pathak, Archan Misra
Research Collection School Of Computing and Information Systems
To promote energy-efficient operations in residential and office buildings, non-intrusive load monitoring (NILM) techniques have been proposed to infer the fine-grained power consumption and usage patterns of appliances from power-line measurement data. Fine-grained monitoring of everyday appliances (such as toasters and coffee makers) can not only promote energy-efficient building operations, but also provide unique insights into the context and activities of individuals. Current building-level NILM techniques are unable to identify the consumption characteristics of relatively low-load appliances, whereas smart-plug based solutions incur significant deployment and maintenance costs. In this paper, we investigate an intermediate architecture, where smart circuit breakers provide …
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen
Research Collection School Of Computing and Information Systems
With the advance of internet and multimedia technologies, large-scale multi-modal representation techniques such as cross-modal hashing, are increasingly demanded for multimedia retrieval. In cross-modal hashing, three essential problems should be seriously considered. The first is that effective cross-modal relationship should be learned from training data with scarce label information. The second is that appropriate weights should be assigned for different modalities to reflect their importance. The last is the scalability of training process which is usually ignored by previous methods. In this paper, we propose Multi-graph Cross-modal Hashing (MGCMH) by comprehensively considering these three points. MGCMH is unsupervised method which …
Design And Evaluation Of Advanced Collusion Attacks On Collaborative Intrusion Detection Networks In Practice, Weizhi Meng, Xiapu Luo, Wenjuan Li, Yan Li
Design And Evaluation Of Advanced Collusion Attacks On Collaborative Intrusion Detection Networks In Practice, Weizhi Meng, Xiapu Luo, Wenjuan Li, Yan Li
Research Collection School Of Computing and Information Systems
To encourage collaboration among single intrusion detection systems (IDSs), collaborative intrusion detection networks (CIDNs) have been developed that enable different IDS nodes to communicate information with each other. This distributed network infrastructure aims to improve the detection performance of a single IDS, but may suffer from various insider attacks like collusion attacks, where several malicious nodes can collaborate to perform adversary actions. To defend against insider threats, challenge-based trust mechanisms have been proposed in the literature and proven to be robust against collusion attacks. However, we identify that such mechanisms depend heavily on an assumption of malicious nodes, which is …
Understanding Patient Portal Use Intentions: Enablers And Inhibitors Of It Use, M. Moqbel, Fiona Fui-Hoon Nah, V. Bartelt, R. O’Dell
Understanding Patient Portal Use Intentions: Enablers And Inhibitors Of It Use, M. Moqbel, Fiona Fui-Hoon Nah, V. Bartelt, R. O’Dell
Research Collection School Of Computing and Information Systems
This research explores factors that influence patient’s intentions to use a hospital’s patient portal. Specifically, we investigate patient portal use intentions using two different perspectives: enablers of IT use (patient need for healthcare empowerment and healthcare professional encouragement) and inhibitors of IT use (privacy and security concerns). Drawing on theories of privacy calculus and protection motivation, we propose a research model to assess the relationships between the enablers and inhibitors of IT use as well as their effects on patient portal adoption. We will administer a survey questionnaire to existing patients of a major hospital in the Midwest and employ …
Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien
Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien
Research Collection School Of Computing and Information Systems
In this paper, we present a real-time salient object detection system based on the minimum spanning tree. Due to the fact that background regions are typically connected to the image boundaries, salient objects can be extracted by computing the distances to the boundaries. However, measuring the image boundary connectivity efficiently is a challenging problem. Existing methods either rely on superpixel representation to reduce the processing units or approximate the distance transform. Instead, we propose an exact and iteration free solution on a minimum spanning tree. The minimum spanning tree representation of an image inherently reveals the object geometry information in …
Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H.
Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H.
Research Collection School Of Computing and Information Systems
In a broadcast encryption system, a broadcaster can encrypt a message to a group of authorized receivers S and each authorized receiver can use his/her own private key to correctly decrypt the broadcast ciphertext, while the users outside S cannot. Identity-based broadcast encryption (IBBE) system is a variant of broadcast encryption system where any string representing the user’s identity (e.g., email address) can be used as his/her public key. IBBE has found many applications in real life, such as pay-TV systems, distribution of copyrighted materials, satellite radio communications. When employing an IBBE system, it is very important to protect the …
A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng
A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.
On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi
On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of personalized text based music retrieval which takes users' music preferences on songs into account via the analysis of online listening behaviours and social tags. Towards the goal, a novel Dual-Layer Music Preference Topic Model (DL-MPTM) is proposed to construct latent music interest space and characterize the correlations among (user, song, term). Based on the DL-MPTM, we further develop an effective personalized music retrieval system. To evaluate the system's performance, extensive experimental studies have been conducted over two test collections to compare the proposed method with the state-of-the-art music retrieval methods. The results …
Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu
Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu
Research Collection School Of Computing and Information Systems
Nowadays an increasing amount of data stored in the public cloud need to be searched remotely for fast accessing. For the sake of privacy, the remote files are usually encrypted, which makes them difficult to be searched by remote servers. It is also harder to efficiently share encrypted data in the cloud than those in plaintext. In this paper, we develop a searchable encryption framework called Linear Encryption with Keyword Search (LEKS) that can semi-generically convert some existing encryption schemes meeting our Linear Encryption Template (LET) to be searchable without re-encrypting all the data. For allowing easy data sharing, we …
Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics, Jovian Lin, Richard Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, Agus Kwee
Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics, Jovian Lin, Richard Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, Agus Kwee
Research Collection School Of Computing and Information Systems
If you were to open your own cafe, would you not want to effortlessly identify the most suitable location to set up your shop? Choosing an optimal physical location is a critical decision for numerous businesses, as many factors contribute to the final choice of the location. In this paper, we seek to address the issue by investigating the use of publicly available Facebook Pages data-which include user "check-ins", types of business, and business locations-to evaluate a user-selected physical location with respect to a type of business. Using a dataset of 20,877 food businesses in Singapore, we conduct analysis of …
A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske
A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske
Research Collection School Of Computing and Information Systems
Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program elements that are likely to be the root cause of the failures (i.e., failing test cases). In this work, we propose Savant, a new fault localization approach that employs a learning-to-rank strategy, using likely invariant diffs and suspiciousness scores as features, to rank methods based on their likelihood to be a root cause …
Detecting Rumors From Microblogs With Recurrent Neural Networks, Jing Ma, Wei Gao, Prasenjit Mitra, Sejeong Kwon, Bernard J. Jansen, Kam-Fai Wong, Meeyoung Cha
Detecting Rumors From Microblogs With Recurrent Neural Networks, Jing Ma, Wei Gao, Prasenjit Mitra, Sejeong Kwon, Bernard J. Jansen, Kam-Fai Wong, Meeyoung Cha
Research Collection School Of Computing and Information Systems
Microblogging platforms are an ideal place for spreading rumors and automatically debunking rumors is a crucial problem. To detect rumors, existing approaches have relied on hand-crafted features for employing machine learning algorithms that require daunting manual effort. Upon facing a dubious claim, people dispute its truthfulness by posting various cues over time, which generates long-distance dependencies of evidence. This paper presents a novel method that learns continuous representations of microblog events for identifying rumors. The proposed model is based on recurrent neural networks (RNN) for learning the hidden representations that capture the variation of contextual information of relevant posts over …
Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li
Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …
Fine-Grained Detection Of Programming Students’ Frustration Using Keystrokes, Mouse Clicks And Interaction Logs, Hua Leong Fwa
Fine-Grained Detection Of Programming Students’ Frustration Using Keystrokes, Mouse Clicks And Interaction Logs, Hua Leong Fwa
Research Collection School Of Computing and Information Systems
Prolonged frustration leads to loss of confidence and eventual disinterest in the learning itself. The modelling of frustration in learning is thus important as it informs on the appropriate time to intervene to sustain the interest and motivation of students. To automatically detect learner’s frustration in a naturalistic learning environment, the novel use of keystrokes, mouse clicks and interaction patterns of students captured within the context of a tutoring system was proposed. The modelling approach was described and a comparison was made between the proposed model using Bayesian Network and the baseline Naïve Bayes model. With the formulation of an …
Three Strategies To Success: Learning Adversary Models In Security Games, Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe
Three Strategies To Success: Learning Adversary Models In Security Games, Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe
Research Collection School Of Computing and Information Systems
State-of-the-art applications of Stackelberg security games -- including wildlife protection -- offer a wealth of data, which can be used to learn the behavior of the adversary. But existing approaches either make strong assumptions about the structure of the data, or gather new data through online algorithms that are likely to play severely suboptimal strategies. We develop a new approach to learning the parameters of the behavioral model of a bounded rational attacker (thereby pinpointing a near optimal strategy), by observing how the attacker responds to only three defender strategies. We also validate our approach using experiments on real and …
Stpp: Spatial-Temporal Phase Profiling Based Method For Relative Rfid Tag Localization, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Stpp: Spatial-Temporal Phase Profiling Based Method For Relative Rfid Tag Localization, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using radio frequency identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called spatial-temporal phase profiling (STPP) to RFID-based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously interrogating …
Satisfiability Modulo Heap-Based Programs, Quang Loc Le, Jun Sun, Wei-Ngan Chin
Satisfiability Modulo Heap-Based Programs, Quang Loc Le, Jun Sun, Wei-Ngan Chin
Research Collection School Of Computing and Information Systems
In this work, we present a semi-decision procedure for a fragment of separation logic with user-defined predicates and Presburger arithmetic. To check the satisfiability of a formula, our procedure iteratively unfolds the formula and examines the derived disjuncts. In each iteration, it searches for a proof of either satisfiability or unsatisfiability. Our procedure is further enhanced with automatically inferred invariants as well as detection of cyclic proof. We also identify a syntactically restricted fragment of the logic for which our procedure is terminating and thus complete. This decidable fragment is relatively expressive as it can capture a range of sophisticated …
Proxy Signature With Revocation, Shengmin Xu, Guomin Yang, Yi Mu, Shu Ma
Proxy Signature With Revocation, Shengmin Xu, Guomin Yang, Yi Mu, Shu Ma
Research Collection School Of Computing and Information Systems
Proxy signature is a useful cryptographic primitive that allows signing right delegation. In a proxy signature scheme, an original signer can delegate his/her signing right to a proxy signer (or a group of proxy signers) who can then sign documents on behalf of the original signer. In this paper, we investigate the problem of proxy signature with revocation. The revocation of delegated signing right is necessary for a proxy signature scheme when the proxy signer’s key is compromised and/or any misuse of the delegated right is noticed. Although a proxy signature scheme usually specifies a delegation time period, it may …
From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang
From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang
Research Collection School Of Computing and Information Systems
Online healthcare service has gradually become a significant part of healthcare services, especially in emerging economy with shortage in medical resources and wide coverage in the Internet usage. This paper studies how health insurance policies affect the demand for online healthcare consultation by using longitudinal online healthcare and offline medical services datasets of a major city in China. The two policies we study are the integration of health insurance systems in urban and rural regions and the integration of health insurance systems between pairwise-cities. The empirical results show that both policies significantly affected the demand for online consultation. Our study …
Response To Sbp-Brims Data Challenge: Agent-Based Approach To Human Migration Movement, Lin Junjie, Larry, Kathleen M. Carley
Response To Sbp-Brims Data Challenge: Agent-Based Approach To Human Migration Movement, Lin Junjie, Larry, Kathleen M. Carley
Research Collection School Of Computing and Information Systems
In this work, we attempt to address the social question of international migration, and the resulting shifts in country populations. This is achieved through the development of a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which inuences overall population change.
Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw
Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Word cloud is a visualization form for text that is recognized for its aesthetic, social, and analytical values. Here, we are concerned with deepening its analytical value for visual comparison of documents. To aid comparative analysis of two or more documents, users need to be able to perceive similarities and differences among documents through their word clouds. However, as we are dealing with text, approaches that treat words independently may impede accurate discernment of similarities among word clouds containing different words of related meanings. We therefore motivate the principle of displaying related words in a coherent manner, and propose to …
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
Research Collection School Of Computing and Information Systems
On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based …
Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham
Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Bike Sharing Systems (BSSs) experience a significant loss in customer demand due to starvation (empty base stations precluding bike pickup) or congestion (full base stations precluding bike return). Therefore, BSSs operators reposition bikes between stations with the help of carrier vehicles. Due to unpredictable and dynamically changing nature of the demand, myopic reasoning typically provides a below par performance. We propose an online and robust repositioning approach to minimise the loss in customer demand while considering the possible uncertainty in future demand. Specifically, we develop a scenario generation approach based on an iterative two player game to compute a strategy …