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Full-Text Articles in Entire DC Network
A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo
A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo
Research Collection School Of Computing and Information Systems
In this article, we propose a novel Hamming embedding kernel with informative bag-of-visual words to address two main problems existing in traditional BoW approaches for video semantic indexing. First, Hamming embedding is employed to alleviate the information loss caused by SIFT quantization. The Hamming distances between keypoints in the same cell are calculated and integrated into the SVM kernel to better discriminate different image samples. Second, to highlight the concept-specific visual information, we propose to weight the visual words according to their informativeness for detecting specific concepts. We show that our proposed kernels can significantly improve the performance of concept …
Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui
Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui
Research Collection School Of Computing and Information Systems
In this demonstration, we demonstrate a mobile-based celebrity video browsing system called CeleBrowser. Using this system, users can interactively switch among four views: people-centric, timeline-centric, month-centric and topic-centric, for browsing celebrity-related hot videos. A peculiarity of the demonstration is to highlight the advantage of multiperspective information organization and presentation in engaging users for exploratory browsing of large number of Web videos on a device with small screen. Technology-wise the demonstration shows how query logs collected for six months from two vertical search engines are leveraged for mining hot events and videos of celebrities.
Community Discovery In Social Networks Via Heterogeneous Link Association And Fusion, Lei Meng, Ah-Hwee Tan
Community Discovery In Social Networks Via Heterogeneous Link Association And Fusion, Lei Meng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a prior, do not address the weighting problem for fusing heterogeneous types of links and have a heavy computational cost. In this paper, we explore the feasibility of a newly proposed heterogeneous data clustering algorithm, called Generalized Heterogeneous Fusion Adaptive Resonance Theory (GHF-ART), for discovering communities in heterogeneous social networks. Different from existing algorithms, GHF-ART performs real-time matching of patterns and one-pass learning which guarantee its low computational cost. With a vigilance parameter to …
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
A scalable video coding (SVC) codestream consists of one base layer and possibly several enhancement layers. The base layer, which contains the lowest quality and resolution images, is the foundation of the SVC codestream and must be delivered to recipients, whereas enhancement layers contain richer contour/texture of images in order to supplement the base layer in resolution, quality, and temporal scalabilities. This paper presents a novel hybrid authentication (HAU) scheme. The HAU employs both cryptographic authentication and content-based authentication techniques to ensure integrity and authenticity of the SVC codestreams. Our analysis and experimental results indicate that the HAU is able …
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Research Collection School Of Computing and Information Systems
Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …
Where Am I? : Studying Users’ Indoor Navigation Location Needs, Kartik Muralidharan, Archan Misra, Rajesh Krishna Balan
Where Am I? : Studying Users’ Indoor Navigation Location Needs, Kartik Muralidharan, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Location has emerged as the single-most important context whilst building pervasive mobile applications. Several mobile applications have appeared that use location to provide a host of services such as location-specific advertising as well as navigation. As a result, the key challenge of positioning techniques has been to provide the most precise location of the user (device) and much effort has been put in computing this fine grained location in indoor environments. This is under the assumption that highly accurate location is crucial for all indoor services. To understand the location accuracy, that should prove sufficient, for users to navigate to …
Clonepedia: Summarizing Code Clones By Common Syntactic Context For Software Maintenance, Yun Lin, Zhenchang Xing, Xin Peng, Yang Liu, Jun Sun, Wenyun Zhao, Jin Song Dong
Clonepedia: Summarizing Code Clones By Common Syntactic Context For Software Maintenance, Yun Lin, Zhenchang Xing, Xin Peng, Yang Liu, Jun Sun, Wenyun Zhao, Jin Song Dong
Research Collection School Of Computing and Information Systems
Code clones have to be made explicit and be managed in software maintenance. Researchers have developed many clone detection tools to detect and analyze code clones in software systems. These tools report code clones as similar code fragments in source files. However, clone-related maintenance tasks (e.g., refactorings) often involve a group of code clones appearing in larger syntactic context (e.g., code clones in sibling classes or code clones calling similar methods). Given a list of low-level code-fragment clones, developers have to manually summarize from bottom up low-level code clones that are relevant to the syntactic context of a maintenance task. …
A Comparative Study On The Effectiveness Of Part-Of-Speech Tagging Techniques On Bug Reports, Yuan Tian, David Lo
A Comparative Study On The Effectiveness Of Part-Of-Speech Tagging Techniques On Bug Reports, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Many software artifacts are written in natural language or contain substantial amount of natural language contents. Thus these artifacts could be analyzed using text analysis techniques from the natural language processing (NLP) community, e.g., the part-of-speech (POS) tagging technique that assigns POS tags (e.g., verb, noun, etc.) to words in a sentence. In the literature, several studies have already applied POS tagging technique on software artifacts to recover important words in them, which are then used for automating various tasks, e.g., locating buggy files for a given bug report, etc. There are many POS tagging techniques proposed and they are …
Information-Theoretic Multi-View Domain Adaptation: A Theoretical And Empirical Study, Pei Yang, Wei Gao
Information-Theoretic Multi-View Domain Adaptation: A Theoretical And Empirical Study, Pei Yang, Wei Gao
Research Collection School Of Computing and Information Systems
Multi-view learning aims to improve classification performance by leveraging the consistency among different views of data. The incorporation of multiple views was paid little attention in the studies of domain adaptation, where the view consistency based on source data is largely violated in the target domain due to the distribution gap between different domain data. In this paper, we leverage multiple views for cross-domain document classification. The central idea is to strengthen the views' consistency on target data by identifying the associations of domain-specific features from different domains. We present an Information-theoretic Multi-view Adaptation Model (IMAM) using a multi-way clustering …
An Active Resource Orchestration Framework For Pan-Scale Sensor-Rich Environments, Youngki Lee, Chulhong Min, Younghyun Ju, Seungwoo Kang, Yunseok Rhee, Junehwa Song
An Active Resource Orchestration Framework For Pan-Scale Sensor-Rich Environments, Youngki Lee, Chulhong Min, Younghyun Ju, Seungwoo Kang, Yunseok Rhee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this paper, we present Orchestrator, an active resource orchestration framework for a PAN-scale sensor-rich mobile computing platform. Incorporating diverse sensing devices connected to a mobile phone, the platform will serve as a common base to accommodate personal context-aware applications. A major challenge for the platform is to simultaneously support concurrent applications requiring continuous and complex context processing, with highly scarce and dynamic resources. To address the challenge, we build Orchestrator, which actively coordinates applications' resource uses over the distributed mobile and sensor devices. As a key approach, it adopts an active resource use orchestration, which prepares multiple alternative plans …
Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin
Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in …
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu, Mei Tao, Jiebo Luo
Research Collection School Of Computing and Information Systems
Auto face annotation, which aims to detect human faces from a facial image and assign them proper human names, is a fundamental research problem and beneficial to many real-world applications. In this work, we address this problem by investigating a retrieval-based annotation scheme of mining massive web facial images that are freely available over the Internet. In particular, given a facial image, we first retrieve the top n similar instances from a large-scale web facial image database using content-based image retrieval techniques, and then use their labels for auto annotation. Such a scheme has two major challenges: 1) how to …
Teaching Tip: The Flipped Classroom, Heng Ngee Mok
Teaching Tip: The Flipped Classroom, Heng Ngee Mok
Research Collection School Of Computing and Information Systems
The flipped classroom has been gaining popularity in recent years. In theory, flipping the classroom appears sound: passive learning activities such as unidirectional lectures are pushed to outside class hours in the form of videos, and precious class time is spent on active learning activities. Yet the courses for information systems (IS) undergraduates at the university that the author is teaching at are still conducted in the traditional lecture-in-class, homework-after-class style. In order to increase students’ engagement with the course content and to improve their experience with the course, the author implemented a trial of the flipped classroom model for …
Keystroke Biometrics: The User Perspective, Chee Meng Tey, Payas Gupta, Kartik Muralidaran, Debin Gao
Keystroke Biometrics: The User Perspective, Chee Meng Tey, Payas Gupta, Kartik Muralidaran, Debin Gao
Research Collection School Of Computing and Information Systems
Usability is an important aspect of security, because poor usability motivates users to find shortcuts that bypass the system. Existing studies on keystroke biometrics evaluate the usability issue in terms of the average false rejection rate (FRR). We show in this paper that such an approach underestimates the user impact in two ways. First, the FRR of keystroke biometrics changes for the worse under a range of common conditions such as background music, exercise and even game playing. In a user study involving 111 participants, the average penalties (increases) in FRR are 0.0360 and 0.0498, respectively, for two different classifiers. …
Ropsteg: Program Steganography With Return Oriented Programming, Kangjie Lu, Siyang Xiong, Debin Gao
Ropsteg: Program Steganography With Return Oriented Programming, Kangjie Lu, Siyang Xiong, Debin Gao
Research Collection School Of Computing and Information Systems
Many software obfuscation techniques have been proposed to hide program instructions or logic and to make reverse engineering hard. In this paper, we introduce a new property in software obfuscation, namely program steganography, where certain instructions are "diffused" in others in such a way that they are non-existent until program execution. Program steganography does not raise suspicion in program analysis, and conforms to the W⊕X and mandatory code signing security mechanisms. We further implement RopSteg, a novel software obfuscation system, to provide (to a certain degree) program steganography using return-oriented programming. We apply RopSteg to eight Windows executables and evaluate …
Theorems About Quadrilaterals And Conics, Dorde Baralic, Branko Grbic, Dorde Zikelic
Theorems About Quadrilaterals And Conics, Dorde Baralic, Branko Grbic, Dorde Zikelic
Research Collection School Of Computing and Information Systems
We study quadrilaterals inscribed and circumscribed about conics and prove interesting theorems. Theorems are discovered by experimenting with dynamical geometry software. The Poncelet theorem for quadrilaterals is proved by elementary means together with Poncelet's grid property.
L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan
L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan
Research Collection School Of Computing and Information Systems
The wealth of information contained in online social networks has created a demand for the publication of such data as graphs. Yet, publication, even after identities have been removed, poses a privacy threat. Past research has suggested ways to publish graph data in a way that prevents the re-identification of nodes. However, even when identities are effectively hidden, an adversary may still be able to infer linkage between individuals with sufficiently high confidence. In this paper, we focus on the privacy threat arising from such link disclosure. We suggest L-opacity, a sufficiently strong privacy model that aims to control an …
Sampled Fictitious Play For Multi-Action Stochastic Dynamic Programs, Archis Ghate, Shih-Fen Cheng, Stephen Baumert, Daniel Reaume, Dushyant Sharma, Robert L. Smith
Sampled Fictitious Play For Multi-Action Stochastic Dynamic Programs, Archis Ghate, Shih-Fen Cheng, Stephen Baumert, Daniel Reaume, Dushyant Sharma, Robert L. Smith
Research Collection School Of Computing and Information Systems
We introduce a class of finite-horizon dynamic optimization problems that we call multi-action stochastic dynamic programs (DPs). Their distinguishing feature is that the decision in each state is a multi-dimensional vector. These problems can in principle be solved using Bellman's backward recursion. However, complexity of this procedure grows exponentially in the dimension of the decision vectors. This is called the curse of action-space dimensionality. To overcome this computational challenge, we propose an approximation algorithm rooted in the game theoretic paradigm of Sampled Fictitious Play (SFP). SFP solves a sequence of DPs with a one-dimensional action-space, which are exponentially smaller than …
Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Tin Seong Kam, Roy Ka Wei Lee
Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Tin Seong Kam, Roy Ka Wei Lee
Research Collection School Of Computing and Information Systems
The adoption of smart cards technologies and automated data collection systems (ADCS) in transportation domain had provided public transport planners opportunities to amass a huge and continuously increasing amount of time-series data about the behaviors and travel patterns of commuters. However the explosive growth of temporal related databases has far outpaced the transport planners’ ability to interpret these data using conventional statistical techniques, creating an urgent need for new techniques to support the analyst in transforming the data into actionable information and knowledge. This research study thus explores and discusses the potential use of time-series data mining, a relatively new …
Digital Certificate Management: Optimal Pricing And Crl Releasing Strategies, Jie Zhang, Nan Hu, M. K. Raka
Digital Certificate Management: Optimal Pricing And Crl Releasing Strategies, Jie Zhang, Nan Hu, M. K. Raka
Research Collection School Of Computing and Information Systems
The fast growth of e-commerce and online activities places increasing needs for authentication and secure communication to enable information exchange and online transactions. The public key infrastructure (PKI) provides a promising foundation for meeting such demand, in which certificate authorities (CAs) provide digital certificates. In practice, it is critical to understand consumer purchasing and revocation behaviors so that CAs can better manage the digital certificates and its CRL releasing process. To address this problem, we analytically model a CA's pricing and revocation releasing strategies taking into consideration the users' rational decisions. The model provides solutions two main research questions: (1) …
Examining The Growth Of Digital Wireless Phone Technology: A Take-Off Theory Analysis, Angsana A. Techatassanasoontorn, Robert J. Kauffman
Examining The Growth Of Digital Wireless Phone Technology: A Take-Off Theory Analysis, Angsana A. Techatassanasoontorn, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
The early phase of diffusion plays a critical role in determining information technology (IT) success in a market. Takeoff, the transition point from the introduction to the growth phase in the IT life cycle, is viewed as an acid test for whether a technology will succeed. We develop a theory to understand global takeoff for digital wireless phones that can be extended to other technologies with related characteristics. Drawing on technology dominance and product life cycle theories, we build a model that consists of standards, market competition, technology costs, and technology substitution to explain takeoff and subsequent market penetration growth. …
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …
Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji
Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji
Research Collection School Of Computing and Information Systems
Weakly-supervised image segmentation is a challenging problem with multidisciplinary applications in multimedia content analysis and beyond. It aims to segment an image by leveraging its imagelevel semantics (i.e., tags). This paper presents a weakly-supervised image segmentation algorithm that learns the distribution of spatially structural superpixel sets from image-level labels. More specifically, we first extract graphlets from a given image, which are small-sized graphs consisting of superpixels and encapsulating their spatial structure. Then, an ecient manifold embedding algorithm is proposed to transfer labels from training images into graphlets. It is further observed that there are numerous redundant graphlets that are not …
Livelabs: Building An In-Situ Real-Time Mobile Experimentation Testbed, Rajesh Krishna Balan, Archan Misra, Youngki Lee
Livelabs: Building An In-Situ Real-Time Mobile Experimentation Testbed, Rajesh Krishna Balan, Archan Misra, Youngki Lee
Research Collection School Of Computing and Information Systems
We present LiveLabs, a mobile experimentation testbed that is currently deployed across our university campus with further deployments at a large shopping mall, a commercial airport, and a resort island soon to follow. The key goal of LiveLabs is to allow in-situ real-time experimentation of mobile applications and services that require context-specific triggers with real participants on their actual smart phones. We describe how LiveLabs works, and then explain the novel R&D required to realise it. We end with a descriptionof the current LiveLabs status (> 700 active participants to date) as well as present some key lessons learned.
Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage, Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jiangying Zhou, Robert H. Deng
Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage, Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jiangying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set …
Ropecker: A Generic And Practical Approach For Defending Against Rop Attack, Yueqiang Cheng, Zongwei Zhou, Yu Miao, Xuhua Ding, Robert H. Deng
Ropecker: A Generic And Practical Approach For Defending Against Rop Attack, Yueqiang Cheng, Zongwei Zhou, Yu Miao, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
Return-Oriented Programming (ROP) is a sophisticated exploitation technique that is able to drive target applications to perform arbitrary unintended operations by constructing a gadget chain reusing existing small code sequences (gadgets). Existing defense mechanisms either only handle specific types of gadgets, require access to source code and/or a customized compiler, break the integrity of application binary, or suffer from high performance overhead. In this paper, we present a novel system, ROPecker, to efficiently and effectively defend against ROP attacks without relying on any other side information (e.g., source code and compiler support) or binary rewriting. ROPecker detects an ROP attack …
Sketch: Pen And Touch Recognition [Workshop Summary], Richard C. Davis, Aaron Adler
Sketch: Pen And Touch Recognition [Workshop Summary], Richard C. Davis, Aaron Adler
Research Collection School Of Computing and Information Systems
Sketch recognition has technically been around for 40 years, but it has come and gone several times due to the difficulty of the problem. With the rise of touch and pen enabled phones and tablets, sketch recognition is regaining popularity and public presence, and more people are becoming aware of and interested in this difficult, but valuable, problem. It is important to harness the Sketch Recognition community at this time to encourage the flourishing of this topic.
Democracy Is Good For Ranking: Towards Multi-View Rank Learning And Adaptation In Web Search, Wei Gao, Pei Yang
Democracy Is Good For Ranking: Towards Multi-View Rank Learning And Adaptation In Web Search, Wei Gao, Pei Yang
Research Collection School Of Computing and Information Systems
No abstract provided.
Sinabro: Opportunistic And Unobtrusive Mobile Ecg Monitoring System, Seungwoo Kang, Sungjun Kwon, Sangwon Seo, Chungkuk Yoo, Kwangsuk Park, Junehwa Song, Youngki Lee
Sinabro: Opportunistic And Unobtrusive Mobile Ecg Monitoring System, Seungwoo Kang, Sungjun Kwon, Sangwon Seo, Chungkuk Yoo, Kwangsuk Park, Junehwa Song, Youngki Lee
Research Collection School Of Computing and Information Systems
In this paper, we propose Sinabro, an opportunistic and unobtrusive mobile electrocardiogram (ECG) monitoring system that monitors the user’s ECG opportunistically during daily smartphone use. Daily ECG monitoring will open up an unprecedented opportunity for pervasive healthcare applications. It will enable the daily detection and prevention of heart problems and also allow inferences about stress, emotion, and even sleep quality. Despite its huge potential, daily ECG monitoring still has not become reality due to its obtrusiveness. In this paper, we first study the potential opportunity to capture ECGs from daily use of smartphones, without requiring the user’s explicit attention. Based …
Building Thinc: User Incentivization And Meeting Rescheduling For Energy Savings, Jun Young Kwak, Debarun Kar, William Haskell, Pradeep Reddy Varakantham, Milind Tambe
Building Thinc: User Incentivization And Meeting Rescheduling For Energy Savings, Jun Young Kwak, Debarun Kar, William Haskell, Pradeep Reddy Varakantham, Milind Tambe
Research Collection School Of Computing and Information Systems
This paper presents THINC, an agent developed for saving energy in real-world commercial buildings. While previous work has presented techniques for computing energy-efficient schedules, it fails to address two issues, centered on human users, that are essential in real-world agent deployments: (i) incentivizing users for their energy saving activities and (ii) interacting with users to reschedule key “energy-consuming” meetings in a timely fashion, while handling the uncertainty in such interactions. THINC addresses these shortcomings by providing four new major contributions. First, THINC computes fair division of credits from energy savings. For this fair division, THINC provides novel algorithmic advances for …