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Research Collection School Of Computing and Information Systems

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Full-Text Articles in Computer Sciences

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 Feb 2014

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 …


Los And Nlos Classification For Underwater Acoustic Localization, Roee Diamant, Hwee-Pink Tan, Lutz Lampe Feb 2014

Los And Nlos Classification For Underwater Acoustic Localization, Roee Diamant, Hwee-Pink Tan, Lutz Lampe

Research Collection School Of Computing and Information Systems

The low sound speed in water makes propagation delay (PD)-based range estimation attractive for underwater acoustic localization (UWAL). However, due to the long channel impulse response and the existence of reflectors, PD-based UWAL suffers from significant degradation when PD measurements of nonline-of-sight (NLOS) communication links are falsely identified as line-of-sight (LOS). In this paper, we utilize expected variation of PD measurements due to mobility of nodes and present an algorithm to classify the former into LOS and NLOS links. First, by comparing signal strength-based and PD-based range measurements, we identify object-related NLOS (ONLOS) links, where signals are reflected from objects …


Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong Jan 2014

Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Modeling and verifying complex real-time systems, involving timing delays, are notoriously difficult problems. Checking the correctness of a system for one particular value for each delay does not give any information for other values. It is thus interesting to reason parametrically, by considering that the delays are parameters (unknown constants) and synthesizing a constraint guaranteeing a correct behavior. We present here Parametric Stateful Timed Communicating Sequential Processes, a language capable of specifying and verifying parametric hierarchical real-time systems with complex data structures. Although we prove that the synthesis is undecidable in general, we present several semi-algorithms for efficient parameter synthesis, …


Towards Verification Of Computation Orchestration, Jin Song Dong, Yang Liu, Jun Sun, Xian Zhang Jan 2014

Towards Verification Of Computation Orchestration, Jin Song Dong, Yang Liu, Jun Sun, Xian Zhang

Research Collection School Of Computing and Information Systems

Recently, a promising programming model called Orc has been proposed to support a structured way of orchestrating distributed Web Services. Orc is intuitive because it offers concise constructors to manage concurrent communication, time-outs, priorities, failure of Web Services or communication and so forth. The semantics of Orc is precisely defined. However, there is no automatic verification tool available to verify critical properties against Orc programs. Our goal is to verify the orchestration programs (written in Orc language) which invoke web services to achieve certain goals. To investigate this problem and build useful tools, we explore in two directions. Firstly, we …


Model Checking Approach To Automated Planning, Yi Li, Jin Song Dong, Jing Sun, Yang Liu, Jun Sun Jan 2014

Model Checking Approach To Automated Planning, Yi Li, Jin Song Dong, Jing Sun, Yang Liu, Jun Sun

Research Collection School Of Computing and Information Systems

Model checking provides a way to automatically explore the state space of a finite state system based on desired properties, whereas planning is to produce a sequence of actions that leads from the initial state to the target goal states. Previous research in this field proposed a number of approaches for connecting model checking with planning problem solving. In this paper, we investigate the feasibility of using an established model checking framework, Process Analysis Toolkit (PAT), as a planning solution provider for upper layer applications. To achieve this, we first carry out a number of experiments on different model checking …


Towards Formal Modelling And Verification Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Yang Liu, Jin Song Dong, Jun Sun, Jit Biswas, Mounir Mokhtari Jan 2014

Towards Formal Modelling And Verification Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Yang Liu, Jin Song Dong, Jun Sun, Jit Biswas, Mounir Mokhtari

Research Collection School Of Computing and Information Systems

Smart systems equipped with emerging pervasive computing technologies enable people with limitations to live in their homes independently. However, lack of guarantees for correctness prevent such system to be widely used. Analysing the system with regard to correctness requirements is a challenging task due to the complexity of the system and its various unpredictable faults. In this work, we propose to use formal methods to analyse pervasive computing (PvC) systems. Firstly, a formal modelling framework is proposed to cover the main characteristics of such systems (e.g., context-awareness, concurrent communications, layered architectures). Secondly, we identify the safety requirements (e.g., free of …


Learning Assumptions For Compositional Verification Of Timed Systems, Shang-Wei Lin Lin, Yang Liu, Jun Sun, Jun Sun Jan 2014

Learning Assumptions For Compositional Verification Of Timed Systems, Shang-Wei Lin Lin, Yang Liu, Jun Sun, Jun Sun

Research Collection School Of Computing and Information Systems

Compositional techniques such as assume-guarantee reasoning (AGR) can help to alleviate the state space explosion problem associated with model checking. However, compositional verification is difficult to be automated, especially for timed systems, because constructing appropriate assumptions for AGR usually requires human creativity and experience. To automate compositional verification of timed systems, we propose a compositional verification framework using a learning algorithm for automatic construction of timed assumptions for AGR. We prove the correctness and termination of the proposed learning-based framework, and experimental results show that our method performs significantly better than traditional monolithic timed model checking.


Inferring The Untold: Mining Software Engineering Research Publication Networks, Santonu Sarkar, Subhajit Datta Jan 2014

Inferring The Untold: Mining Software Engineering Research Publication Networks, Santonu Sarkar, Subhajit Datta

Research Collection School Of Computing and Information Systems

Since the inception of organized research publication in software engineering in 1975, the discipline has gained maturity. This journey has been guided by the synergy of ideas and interactions of individuals. In this paper, we discuss a method for aggregating the corpus of 19,000+ papers and 21,000+ authors across 16 specialized software engineering venues. We focus on the approach of data collection, processing and storage. It can be used to address questions by the software engineering research community. We evaluate three questions: patterns of research topics with time, factors influencing the contribution of individual researchers, and the interaction among the …


Coupling Graphs, Efficient Algorithms And B-Cell Epitope Prediction, Liang Zhao, Steven C. H. Hoi, Zhenhua Li, Limsoon Wong, Hung Nguyen Jan 2014

Coupling Graphs, Efficient Algorithms And B-Cell Epitope Prediction, Liang Zhao, Steven C. H. Hoi, Zhenhua Li, Limsoon Wong, Hung Nguyen

Research Collection School Of Computing and Information Systems

Coupling graphs are newly introduced in this paper to meet many application needs particularly in the field of bioinformatics. A coupling graph is a two-layer graph complex, in which each node from one layer of the graph complex has at least one connection with the nodes in the other layer, and vice versa. The coupling graph model is sufficiently powerful to capture strong and inherent associations between subgraph pairs in complicated applications. The focus of this paper is on mining algorithms of frequent coupling subgraphs and bioinformatics application. Although existing frequent subgraph mining algorithms are competent to identify frequent subgraphs …


Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li Jan 2014

Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li

Research Collection School Of Computing and Information Systems

Off-the-shelf smartphones have boosted large scale participatory sensing applications as they are equipped with various functional sensors, possess powerful computation and communication capabilities, and proliferate at a breathtaking pace. Yet the low participation level of smartphone users due to various resource consumptions, such as time and power, remains a hurdle that prevents the enjoyment brought by sensing applications. Recently, some researchers have done pioneer works in motivating users to contribute their resources by designing incentive mechanisms, which are able to provide certain rewards for participation. However, none of these works considered smartphone users’ nature of opportunistically occurring in the area …


Sherlock: Microenvironment Sensing For Smartphones, Zheng Yang, Longfei Shangguan, Weixi Gu, Zimu Zhou, Chenshu Wu, Yunhao Liu Jan 2014

Sherlock: Microenvironment Sensing For Smartphones, Zheng Yang, Longfei Shangguan, Weixi Gu, Zimu Zhou, Chenshu Wu, Yunhao Liu

Research Collection School Of Computing and Information Systems

Context-awareness is getting increasingly important for a range of mobile and pervasive applications on nowadays smartphones. Whereas human-centric contexts (e.g., indoor/ outdoor, at home/in office, driving/walking) have been extensively researched, few attempts have studied from phones’ perspective (e.g., on table/sofa, in pocket/bag/hand). We refer to such immediate surroundings as micro-environment, usually several to a dozen of centimeters, around a phone. In this study, we design and implement Sherlock, a micro-environment sensing platform that automatically records sensor hints and characterizes the micro-environment of smartphones. The platform runs as a daemon process on a smartphone and provides finer-grained environment information to upper …


Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li Jan 2014

Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li

Research Collection School Of Computing and Information Systems

Off-the-shelf smartphones have boosted large scale participatory sensing applications as they are equipped with various functional sensors, possess powerful computation and communication capabilities, and proliferate at a breathtaking pace. Yet the low participation level of smartphone users due to various resource consumptions, such as time and power, remains a hurdle that prevents the enjoyment brought by sensing applications. Recently, some researchers have done pioneer works in motivating users to contribute their resources by designing incentive mechanisms, which are able to provide certain rewards for participation. However, none of these works considered smartphone users’ nature of opportunistically occurring in the area …


Complexity Of The Soundness Problem Of Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong Jan 2014

Complexity Of The Soundness Problem Of Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Classical workflow nets (WF-nets for short) are an important subclass of Petri nets that are widely used to model and analyze workflow systems. Soundness is a crucial property of workflow systems and guarantees that these systems are deadlock-free and bounded. Aalst et al. proved that the soundness problem is decidable for WF-nets and can be polynomially solvable for free-choice WF-nets. This paper proves that the soundness problem is PSPACE-hard for WF-nets. Furthermore, it is proven that the soundness problem is PSPACE-complete for bounded WF-nets. Based on the above conclusion, it is derived that the soundness problem is also PSPACE-complete for …


Loki: A Privacy-Conscious Platform For Crowdsourced Surveys, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Boreli Jan 2014

Loki: A Privacy-Conscious Platform For Crowdsourced Surveys, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Boreli

Research Collection School Of Computing and Information Systems

Emerging platforms such as Amazon Mechanical Turk and Google Consumer Surveys are increasingly being used by researchers and market analysts to crowdsource large-scale survey data from on-line populations at extremely low-cost. However, by participating in successive surveys, users risk being profiled and targeted, both by surveyors and by the platform itself. In this paper we propose, develop, and evaluate the design of a crowdsourcing platform, called Loki, that is privacy conscious. Our contributions are three-fold: (a) We propose Loki, a system that allows users to obfuscate their (ratings-based or multiple-choice) responses at-source based on their chosen privacy level, and gives …


A Robust Smart Card-Based Anonymous User Authentication Protocol For Wireless Communications, Fengton Wen, Willy Susilo, Guomin Yang Jan 2014

A Robust Smart Card-Based Anonymous User Authentication Protocol For Wireless Communications, Fengton Wen, Willy Susilo, Guomin Yang

Research Collection School Of Computing and Information Systems

Anonymous user authentication is an important but challenging task for wireless communications. In a recent paper, Das proposed a smart cardï based anonymous user authentication protocol for wireless communications. The scheme can protect user privacy and is believed to be secure against a range of network attacks even if the secret information stored in the smart card is compromised. In this paper, we reanalyze the security of Das' scheme, and show that the scheme is in fact insecure against impersonation attacks. We then propose a new smart cardï based anonymous user authentication protocol for wireless communications. Compared with the existing …


Cross-Domain Password-Based Authenticated Key Exchange Revisited, Liqun Chen, Hoon Wei Lim, Guomin Yang Jan 2014

Cross-Domain Password-Based Authenticated Key Exchange Revisited, Liqun Chen, Hoon Wei Lim, Guomin Yang

Research Collection School Of Computing and Information Systems

We revisit the problem of secure cross-domain communication between two users belonging to different security domains within an open and distributed environment. Existing approaches presuppose that either the users are in possession of public key certificates issued by a trusted certificate authority (CA), or the associated domain authentication servers share a long-term secret key. In this article, we propose a generic framework for designing four-party password-based authenticated key exchange (4PAKE) protocols. Our framework takes a different approach from previous work. The users are not required to have public key certificates, but they simply reuse their login passwords, which they share …


On The Security Of Auditing Mechanisms For Secure Cloud Storage, Yong Yu, Lei Niu, Guomin Yang, Yi Mu, Willy Susilo Jan 2014

On The Security Of Auditing Mechanisms For Secure Cloud Storage, Yong Yu, Lei Niu, Guomin Yang, Yi Mu, Willy Susilo

Research Collection School Of Computing and Information Systems

Cloud computing is a novel computing model that enables convenient and on-demand access to a shared pool of configurable computing resources. Auditing services are highly essential to make sure that the data is correctly hosted in the cloud. In this paper, we investigate the active adversary attacks in three auditing mechanisms for shared data in the cloud, including two identity privacy-preserving auditing mechanisms called Oruta and Knox, and a distributed storage integrity auditing mechanism.We show that these schemes become insecure when active adversaries are involved in the cloud storage. Specifically, an active adversary can arbitrarily alter the cloud data without …


Risk Minimization Of Disjunctive Temporal Problem With Uncertainty, Hoong Chuin Lau, Tuan Anh Hoang Jan 2014

Risk Minimization Of Disjunctive Temporal Problem With Uncertainty, Hoong Chuin Lau, Tuan Anh Hoang

Research Collection School Of Computing and Information Systems

The Disjunctive Temporal Problem with Uncertainty (DTPU) is a fundamental problem that expresses temporal reasoning with both disjunctive constraints and contingency. A recent work (Peintner et al, 2007) develops a complete algorithm for determining Strong Controlla- bility of a DTPU. Such a notion that guarantees 100% confidence of execution may be too conservative in practice. In this paper, following the idea of (Tsamardinos 2002), we are interested to find a schedule that minimizes the risk (i.e. probability of failure) of executing a DTPU. We present a problem decomposition scheme that enables us to compute the probability of failure efficiently, followed …


Learning To Recommend Descriptive Tags For Questions In Social Forums, Liqiang Nie, Yiliang Zhao, Xiangyu Wang, Jialie Shen, Tat-Seng Chua Jan 2014

Learning To Recommend Descriptive Tags For Questions In Social Forums, Liqiang Nie, Yiliang Zhao, Xiangyu Wang, Jialie Shen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Around 40% of the questions in the emerging social-oriented question answering forums have at most one manually labeled tag, which is caused by incomprehensive question understanding or informal tagging behaviors. The incompleteness of question tags severely hinders all the tag-based manipulations, such as feeds for topic-followers, ontological knowledge organization, and other basic statistics. This article presents a novel scheme that is able to comprehensively learn descriptive tags for each question. Extensive evaluations on a representative real-world dataset demonstrate that our scheme yields significant gains for question annotation, and more importantly, the whole process of our approach is unsupervised and can …


Detecting Click Fraud In Online Advertising: A Data Mining Approach, Richard Oentaryo, Ee Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar Jan 2014

Detecting Click Fraud In Online Advertising: A Data Mining Approach, Richard Oentaryo, Ee Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar

Research Collection School Of Computing and Information Systems

Click fraud - the deliberate clicking on advertisements with no real interest on the product or service offered - is one of the most daunting problems in online advertising. Building an elective fraud detection method is thus pivotal for online advertising businesses. We organized a Fraud Detection in Mobile Advertising (FDMA) 2012 Competition, opening the opportunity for participants to work on real-world fraud data from BuzzCity Pte. Ltd., a global mobile advertising company based in Singapore. In particular, the task is to identify fraudulent publishers who generate illegitimate clicks, and distinguish them from normal publishers. The competition was held from …


The Challenge Of Continuous Mobile Context Sensing, Rajesh Krishna Balan, Youngki Lee, Kiat Wee Tan, Archan Misra Jan 2014

The Challenge Of Continuous Mobile Context Sensing, Rajesh Krishna Balan, Youngki Lee, Kiat Wee Tan, Archan Misra

Research Collection School Of Computing and Information Systems

In this paper, we highlight the challenge of continuously sensing context data from mobile phones. In particular, we show that the energy cost of this type of continuous sensing is extremely high if a) accuracy is desired, and b) power optimisations do not work well if multiple tasks are sensing concurrently. Our results are derived from our experience in building the LiveLabs context sensing platform. We present results for different types of sensing tasks; ranging from simple sensing using just one sensor all the way to multi-sensor sensing performed by concurrent high-level tasks. We end with a discussion of the …


How Can Substitution And Complementarity Effects Be Leveraged For Broadband Internet Services Strategy?, Gwangjae Jung, Young Soo Kim, Robert J. Kauffman Jan 2014

How Can Substitution And Complementarity Effects Be Leveraged For Broadband Internet Services Strategy?, Gwangjae Jung, Young Soo Kim, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

With growth in mobile Internet services, the relationship between mobile and fixed broadband has become an issue in telecom firm strategy. Previous research focused on aggregate penetration for mobile and fixed broadband services. Our research analyzes the economic relationship between mobile and fixed broadband services at the household level, as a basis for how senior managers should rethink their strategy approach. Using data on broadband services subscriptions, we examine how changes that occur for mobile broadband services bandwidth (MBB) affect changes in fixed broadband bandwidth (FBB) services subscriptions, inclusive of new subscriptions - and vice versa. We explore the different …


Strategic Decision Support System Using Heuristic Algorithm For Practical Outlet Zones Allocation To Dealers In A Beer Supply Distribution Network, Michelle Lee Fong Cheong Jan 2014

Strategic Decision Support System Using Heuristic Algorithm For Practical Outlet Zones Allocation To Dealers In A Beer Supply Distribution Network, Michelle Lee Fong Cheong

Research Collection School Of Computing and Information Systems

We consider a two-echelon beer supply distribution network with the brewer replenishing the dealers and the dealers serving the outlet zones directly, for multiple product types. The allocation of the outlet zones to the dealers will determine the quantity of products the brewer replenishes each dealer, which will in turn impact the total warehousing and transportation costs. The non-linear optimization model formulated is difficult to solve to optimality, and the model itself does not include practical business considerations in the distribution business. A heuristics algorithm is designed and easily implemented using spreadsheets with Visual Basic programming to effectively and efficiently …


Personalizing Software Development Practice Using Mastery-Based Coaching, Chris Boesch, Sandra Boesch Jan 2014

Personalizing Software Development Practice Using Mastery-Based Coaching, Chris Boesch, Sandra Boesch

Research Collection School Of Computing and Information Systems

The authors previously developed a system to facilitate the self-directed learning and practicing of software languages in Singapore. One of the goals of this self-directed learning was to enable the development of student mentors who would then be able to assist other students during classroom sessions. Building on this work, the authors extended the platform to support personalized coaching with the goals of further enabling and preparing students to mentor their peers. This paper covers the challenges, insights, and features that were developed in order to develop and deploy this mastery-based coaching feature.


Privacy-Preserving Ad-Hoc Equi-Join On Outsourced Data, Hwee Hwa Pang, Xuhua Ding Jan 2014

Privacy-Preserving Ad-Hoc Equi-Join On Outsourced Data, Hwee Hwa Pang, Xuhua Ding

Research Collection School Of Computing and Information Systems

In IT outsourcing, a user may delegate the data storage and query processing functions to a third-party server that is not completely trusted. This gives rise to the need to safeguard the privacy of the database as well as the user queries over it. In this article, we address the problem of running ad hoc equi-join queries directly on encrypted data in such a setting. Our contribution is the first solution that achieves constant complexity per pair of records that are evaluated for the join. After formalizing the privacy requirements pertaining to the database and user queries, we introduce a …


Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi Jan 2014

Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation …


Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu Jan 2014

Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu

Research Collection School Of Computing and Information Systems

This paper investigates a framework of search-based face annotation (SBFA) by mining weakly labeled facial images that are freely available on the World Wide Web (WWW). One challenging problem for search-based face annotation scheme is how to effectively perform annotation by exploiting the list of most similar facial images and their weak labels that are often noisy and incomplete. To tackle this problem, we propose an effective unsupervised label refinement (ULR) approach for refining the labels of web facial images using machine learning techniques. We formulate the learning problem as a convex optimization and develop effective optimization algorithms to solve …


Online Multiple Kernel Similarity Learning For Visual Search, Hao Xia, Chu Hong Hoi, Rong Jin, Peilin Zhao Jan 2014

Online Multiple Kernel Similarity Learning For Visual Search, Hao Xia, Chu Hong Hoi, Rong Jin, Peilin Zhao

Research Collection School Of Computing and Information Systems

Recent years have witnessed a number of studies on distance metric learning to improve visual similarity search in content-based image retrieval (CBIR). Despite their successes, most existing methods on distance metric learning are limited in two aspects. First, they usually assume the target proximity function follows the family of Mahalanobis distances, which limits their capacity of measuring similarity of complex patterns in real applications. Second, they often cannot effectively handle the similarity measure of multimodal data that may originate from multiple resources. To overcome these limitations, this paper investigates an online kernel similarity learning framework for learning kernel-based proximity functions …


How Can Consumer Preferences Be Leveraged For Targeted Upselling In Cable Tv Services?, Bing Tian Dai Jan 2014

How Can Consumer Preferences Be Leveraged For Targeted Upselling In Cable Tv Services?, Bing Tian Dai

Research Collection School Of Computing and Information Systems

Internet TV has attracted a significant amount of attention from the conventional cable TV service providers, by providing customized TV programs at preferred time slots. The cable TV service providers are seeking to retain their customers by giving them a better experience: by understanding their customers’ preferences and upselling them the right products to cater to their interests. It is not easy to understand customer preferences though, since customers are not able to watch channels to which they have not subscribed. This makes it difficult to predict what they will like to watch, as a result. In this paper, I …


Innovative Applications And Security Of Internet Of Things, Yingjiu Li, Yingjiu Li, Nai-Wei Lo Jan 2014

Innovative Applications And Security Of Internet Of Things, Yingjiu Li, Yingjiu Li, Nai-Wei Lo

Research Collection School Of Computing and Information Systems

With the advances and falling cost of intelligent things like RFID/USN, sensor networks, NFC, ZigBee, smart phones, and other relevant technologies, the potential applications and implementations of Internet of things have been intensively studied by both the academia and the industry. One potential application is integrating social networks with IoT, which results in the social Internet of things (SIoT). This vision not only provides potential opportunities but also new challenges. Innovative application and security are two main issues toward this paradigm