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Weakly-Supervised Hashing In Kernel Space, Yadong Mu, Jialie Shen, Shuicheng Yan
Weakly-Supervised Hashing In Kernel Space, Yadong Mu, Jialie Shen, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform hashing in an unsupervised way. In this paper we move one step forward and propose a supervised hashing method, i.e., the LAbel-regularized Max-margin Partition (LAMP) algorithm. The proposed method generates hash functions in weakly-supervised setting, where a small portion of sample pairs are manually labeled to be “similar” or “dissimilar”. We formulate the task as a Constrained Convex-Concave Procedure (CCCP), which can be relaxed into a series of convex sub-problems solvable with efficient Quadratic-Program (QP). …
Stevent: Spatio-Temporal Event Model For Social Network Discovery, Hady W. Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan
Stevent: Spatio-Temporal Event Model For Social Network Discovery, Hady W. Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan
Research Collection School Of Computing and Information Systems
Spatio-temporal data concerning the movement of individuals over space and time contains latent information on the associations among these individuals. Sources of spatio-temporal data include usage logs of mobile and Internet technologies. This article defines a spatio-temporal event by the co-occurrences among individuals that indicate potential associations among them. Each spatio-temporal event is assigned a weight based on the precision and uniqueness of the event. By aggregating the weights of events relating two individuals, we can determine the strength of association between them. We conduct extensive experimentation to investigate both the efficacy of the proposed model as well as the …
Efficient Processing Of Exact Top-K Queries Over Disk-Resident Sorted Lists, Hwee Hwa Pang, Xuhua Ding, Baihua Zheng
Efficient Processing Of Exact Top-K Queries Over Disk-Resident Sorted Lists, Hwee Hwa Pang, Xuhua Ding, Baihua Zheng
Research Collection School Of Computing and Information Systems
The top-k query is employed in a wide range of applications to generate a ranked list of data that have the highest aggregate scores over certain attributes. As the pool of attributes for selection by individual queries may be large, the data are indexed with per-attribute sorted lists, and a threshold algorithm (TA) is applied on the lists involved in each query. The TA executes in two phases--find a cut-off threshold for the top-k result scores, then evaluate all the records that could score above the threshold. In this paper, we focus on exact top-k queries that involve monotonic linear …
Mining Antagonistic Communities From Social Networks, Kuan Zhang, David Lo, Ee Peng Lim
Mining Antagonistic Communities From Social Networks, Kuan Zhang, David Lo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
During social interactions in a community, there are often sub-communities that behave in opposite manner. These antagonistic sub-communities could represent groups of people with opposite tastes, factions within a community distrusting one another, etc. Taking as input a set of interactions within a community, we develop a novel pattern mining approach that extracts for a set of antagonistic sub-communities. In particular, based on a set of user specified thresholds, we extract a set of pairs of sub-communities that behave in opposite ways with one another. To prevent a blow up in these set of pairs, we focus on extracting a …
A Hybrid Method To Detect Deflation Fraud In Cost-Per-Action Online Advertising, Xuhua Ding
A Hybrid Method To Detect Deflation Fraud In Cost-Per-Action Online Advertising, Xuhua Ding
Research Collection School Of Computing and Information Systems
Web advertisers prefer the cost-per-action (CPA) advertisement model whereby an advertiser pays a web publisher according to the actual amount of transactions, rather than the volume of advertisement clicks. The main obstacle for a wide deployment of this model is the deflation fraud. Namely, a dishonest advertiser under-reports the transaction count in order to discharge less. In this paper, we present a mechanism to detect such a fraud using a hybrid of cryptography and probability tools. With the assistance from a small number of users, the publisher can detect deflation fraud with a success probability growing exponentially with the fraud …
Player Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Richa Sharan, Jaideep Srivastava
Player Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Richa Sharan, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
In this study, we propose a comprehensive performance management tool for measuring and reporting operational activities of game players. This study uses performance data of game players in EverQuest II, a popular MMORPG developed by Sony Online Entertainment, to build performance prediction models forgame players. The prediction models provide a projection of player’s future performance based on his past performance, which is expected to be a useful addition to existing player performance monitoring tools. First, we show that variations of PECOTA [2] and MARCEL [3], two most popular baseball home run prediction methods, can be used for game player performance …
Semantic Context Modeling With Maximal Margin Conditional Random Fields For Automatic Image Annotation, Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-Seng Chua, Chong-Wah Ngo
Semantic Context Modeling With Maximal Margin Conditional Random Fields For Automatic Image Annotation, Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-Seng Chua, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources, semantic context has been exploited in AIA and brings promising results. However, previous works either casted the problem into structural classification or adopted multi-layer modeling, which suffer from the problems of scalability or model efficiency. In this paper, we propose a novel discriminative Conditional Random Field (CRF) model for semantic context modeling in AIA, which is built over semantic concepts and treats an image as a whole observation without segmentation. Our model captures the interactions between semantic …
Structural And Informal Knowledge Acquisition And Dissemination In Organisational Learning: An Exploratory Analysis, Siu Loon Hoe
Structural And Informal Knowledge Acquisition And Dissemination In Organisational Learning: An Exploratory Analysis, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
PurposeThe topic of organizational learning is populated with many theories and models; many relate to the enduring organizational learning framework consisting of knowledge acquisition, knowledge dissemination, and knowledge use. However, most of the research either emphasizes structural knowledge acquisition and dissemination as a composite construct, or focuses solely on the structural aspect of knowledge acquisition and dissemination. The primary objective of this study is to develop and test a model of organizational learning that incorporates both structural and informal knowledge acquisition and dissemination and as separate processes. The predictors of these processes are also proposedDesign/methodology/approachA model of organizational learning that …
Understanding The Values Of Mobile Technology In Education: A Value-Focused Thinking Approach, Hong Sheng, Keng Siau, Fiona Nah
Understanding The Values Of Mobile Technology In Education: A Value-Focused Thinking Approach, Hong Sheng, Keng Siau, Fiona Nah
Research Collection School Of Computing and Information Systems
Mobile technology has mobilized the human interaction in all dimensions by supporting mobile collaboration. As collaboration is key to learning in today's educational environment, mobile technology has tremendous potential in supporting and improving education and its delivery. Given that mobile technology for education is a new phenomenon that is gaining popularity, the values of using mobile technology to support education need to be further researched and better understood. In this research, we used the Value-Focused Thinking approach to interview students and instructors to identify the values of education that are enabled by mobile technology. These values are represented in the …
Global Project Management: Pedagogy For Distributed Teams, Benjamin Kok Siew Gan, Randy Weinberg, Selma Limam Mansar
Global Project Management: Pedagogy For Distributed Teams, Benjamin Kok Siew Gan, Randy Weinberg, Selma Limam Mansar
Research Collection School Of Computing and Information Systems
This paper reflects on pedagogy for teaching collaborative global projects across universities in different countries. Over a period of four years, students at three universities - one in the United States, one in Singapore and one in the Middle East - enrolled in a course called "Global Project Management". In this course, coordinated across locations, students experience a global project with distant team members. We describe the course experience and student perceptions of the requisite skills, collaboration tools and challenges bearing on effective global project work.
Exploiting Query Logs For Cross-Lingual Query Suggestions., Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Kam-Fai Wong, Hsiao-Wuen Hon
Exploiting Query Logs For Cross-Lingual Query Suggestions., Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Kam-Fai Wong, Hsiao-Wuen Hon
Research Collection School Of Computing and Information Systems
Query suggestion aims to suggest relevant queries for a given query, which helps users better specify their information needs. Previous work on query suggestion has been limited to the same language. In this article, we extend it to cross-lingual query suggestion (CLQS): for a query in one language, we suggest similar or relevant queries in other languages. This is very important to the scenarios of cross-language information retrieval (CLIR) and other related cross-lingual applications. Instead of relying on existing query translation technologies for CLQS, we present an effective means to map the input query of one language to queries of …
Time-Bound Hierarchical Key Assignment: An Overview, Wen Tao Zhu, Robert H. Deng, Jianying Zhou, Feng Bao
Time-Bound Hierarchical Key Assignment: An Overview, Wen Tao Zhu, Robert H. Deng, Jianying Zhou, Feng Bao
Research Collection School Of Computing and Information Systems
The access privileges in distributed systems can be effectively organized as a partial-order hierarchy that consists of distinct security classes, and the access rights are often designated with certain temporal restrictions. The time-bound hierarchical key assignment problem is to assign distinct cryptographic keys to distinct security classes according to their privileges so that users from a higher class can use their class key to derive the keys of lower classes, and these keys are time-variant with respect to sequentially allocated temporal units called time slots. In this paper, we present the involved principle, survey the state of the art, and …
A Scalable And Energy-Efficient Context Monitoring Framework For Mobile Personal Sensor Networks, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Youngki Lee, Souneil Park, Junehwa Song
A Scalable And Energy-Efficient Context Monitoring Framework For Mobile Personal Sensor Networks, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Youngki Lee, Souneil Park, Junehwa Song
Research Collection School Of Computing and Information Systems
The key feature of many emerging pervasive computing applications is to proactively provide services to mobile individuals. One major challenge in providing users with proactive services lies in continuously monitoring users’ context based on numerous sensors in their PAN/BAN environments. The context monitoring in such environments imposes heavy workloads on mobile devices and sensor nodes with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the …
Two-View Transductive Support Vector Machines, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
Two-View Transductive Support Vector Machines, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
Research Collection School Of Computing and Information Systems
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam detection, which changes at a very brisk pace. For some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such as term frequency, while a second view may contain a small but highly-informative number of domain specific features. We thus propose a novel two-view transductive SVM that takes advantage of both the abundant amount of unlabeled data …
Open Innovation In Platform Competition, Mei Lin
Open Innovation In Platform Competition, Mei Lin
Research Collection School Of Computing and Information Systems
We examine the competition between a proprietary platform and an open platform,where each platform holds a two-sided market consisted of app developers and users.The open platform cultivates an innovative environment by inviting public efforts todevelop the platform itself and permitting distribution of apps outside of its own appmarket; the proprietary platform restricts apps sales solely within its app market. Weuse a game theoretic model to capture this competitive phenomenon and analyze theimpact of growth of the open source community on the platform competition. We foundthat growth of the open community mitigates the platform rivalry, and balances the developernetwork sizes on …
Point-Based Backup For Decentralized Pompds: Complexity And New Algorithms, Akshat Kumar, Shlomo Zilberstein
Point-Based Backup For Decentralized Pompds: Complexity And New Algorithms, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Decentralized POMDPs provide an expressive framework for sequential multi-agent decision making. Despite their high complexity, there has been significant progress in scaling up existing algorithms, largely due to the use of point-based methods. Performing point-based backup is a fundamental operation in state-of-the-art algorithms. We show that even a single backup step in the multi-agent setting is NP-Complete. Despite this negative worst-case result, we present an efficient and scalable optimal algorithm as well as a principled approximation scheme. The optimal algorithm exploits recent advances in the weighted CSP literature to overcome the complexity of the backup operation. The polytime approximation scheme …
Towards Finding Robust Execution Strategies For Rcpsp/Max With Durational Uncertainty, Na Fu, Pradeep Varakantham, Hoong Chuin Lau
Towards Finding Robust Execution Strategies For Rcpsp/Max With Durational Uncertainty, Na Fu, Pradeep Varakantham, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max) have been studied extensively in the literature. However, the more realistic RCPSP/max problems — ones where durations of activities are not known with certainty – have received scant interest and hence are the main focus of the paper. Towards addressing the significant computational complexity involved in tackling RCPSP/max with durational uncertainty, we employ a local search mechanism to generate robust schedules. In this regard, we make two key contributions: (a) Introducing and studying the key properties of a new decision rule to specify start times of activities with …
Exclusive Lasso For Multi-Task Feature Selection, Yang Zhou, Rong Jin, Steven C. H. Hoi
Exclusive Lasso For Multi-Task Feature Selection, Yang Zhou, Rong Jin, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
We propose a novel group regularization which we call exclusive lasso. Unlike the group lasso regularizer that assumes co-varying variables in groups, the proposed exclusive lasso regularizer models the scenario when variables in the same group compete with each other. Analysis is presented to illustrate the properties of the proposed regularizer. We present a framework of kernel-based multi-task feature selection algorithm based on the proposed exclusive lasso regularizer. An efficient algorithm is derived to solve the related optimization problem. Experiments with document categorization show that our approach outperforms state-of-the-art algorithms for multi-task feature selection.
The Role Of Emergent Knowledge Structures In Collaborative Software Development, Christoph Treude
The Role Of Emergent Knowledge Structures In Collaborative Software Development, Christoph Treude
Research Collection School Of Computing and Information Systems
Many collaboration features in software development tools draw on lightweight technologies such as tagging and wikis. We propose to study the role of emergent knowledge structures created through these features. Using a mixed-methods approach, we investigate which processes emergent knowledge structures support and how tool support can leverage them.
Optimal Matching Between Spatial Datasets Under Capacity Constraints, Hou U Leong, Kyriakos Mouratidis, Man Lung Yiu, Nikos Mamoulis
Optimal Matching Between Spatial Datasets Under Capacity Constraints, Hou U Leong, Kyriakos Mouratidis, Man Lung Yiu, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
Consider a set of customers (e.g., WiFi receivers) and a set of service providers (e.g., wireless access points), where each provider has a capacity and the quality of service offered to its customers is anti-proportional to their distance. The capacity constrained assignment (CCA) is a matching between the two sets such that (i) each customer is assigned to at most one provider, (ii) every provider serves no more customers than its capacity, (iii) the maximum possible number of customers are served, and (iv) the sum of Euclidean distances within the assigned provider-customer pairs is minimized. Although max-flow algorithms are applicable …
Mining Diversity On Networks, Lu Liu, Feida Zhu, Chen Chen, Xifeng Yan, Jiawei Han, Philip Yu, Shiqiang Yang
Mining Diversity On Networks, Lu Liu, Feida Zhu, Chen Chen, Xifeng Yan, Jiawei Han, Philip Yu, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Despite the recent emergence of many large-scale networks in different application domains, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. We first lay out two criteria that capture the semantic meaning of diversity, and then propose a compliant definition which is simple enough to embed the idea. An efficient top-k diversity ranking algorithm is developed for computation on dynamic networks. Experiments on both synthetic and real datasets …
A Verification System For Interval-Based Specification Languages, Chunqing Chen, Jin Song Dong, Jun Sun, Andrew P. Martin
A Verification System For Interval-Based Specification Languages, Chunqing Chen, Jin Song Dong, Jun Sun, Andrew P. Martin
Research Collection School Of Computing and Information Systems
Interval-based specification languages have been used to formally model and rigorously reason about real-time computing systems. This usually involves logical reasoning and mathematical computation with respect to continuous or discrete time. When these systems are complex, analyzing their models by hand becomes error-prone and difficult. In this article, we develop a verification system to facilitate the formal analysis of interval-based specification languages with machine-assisted proof support. The verification system is developed using a generic theorem prover, Prototype Verification System (PVS). Our system elaborately encodes a highly expressive set-based notation, Timed Interval Calculus (TIC), and can rigorously carry out the verification …
Shifting Inference Control To User Side: Architecture And Protocol, Yanjiang Yang, Yingjiu Li, Robert H. Deng, Feng Bao
Shifting Inference Control To User Side: Architecture And Protocol, Yanjiang Yang, Yingjiu Li, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Inference has been a longstanding issue in database security, and inference control, aiming to curb inference, provides an extra line of defense to the confidentiality of databases by complementing access control. However, in traditional inference control architecture, database server is a crucial bottleneck, as it enforces highly computation-intensive auditing for all users who query the protected database. As a result, most auditing methods, though rigorously studied, are not practical for protecting large-scale real-world database systems. In this paper, we shift this paradigm by proposing a new inference control architecture, entrusting inference control to each user's platform that is equipped with …
Data Mining Based Predictive Models For Overall Health Indices, Ridhima Rajkumar, Kyong Jin Shim, Jaideep Srivastava
Data Mining Based Predictive Models For Overall Health Indices, Ridhima Rajkumar, Kyong Jin Shim, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
In this study, we infer health care indices of individuals using their pharmacy medical and prescription claims. Specifically, we focus on the widely used Charlson Index. We use data mining techniques to formulate the problem of classifying Charlson Index (CI) and build predictive models to predict individual health index score. First, we present comparative analyses of several classification algorithms. Second, our study shows that certain ensemble algorithms lead to higher prediction accuracy in comparison to base algorithms. Third, we introduce cost-sensitive learning to the classification algorithms and show that the inclusion of cost-sensitive learning leads to improved prediction accuracy. The …
Algorithms For Constrained K-Nearest Neighbor Queries Over Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen
Algorithms For Constrained K-Nearest Neighbor Queries Over Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen
Research Collection School Of Computing and Information Systems
An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (≥ 1) trajectories that lie closest to q and …
Managing Media Rich Geo-Spatial Annotations For A Map-Based Mobile Application Using Clustering, Khasfariyati Razikin, Dion Hoe-Lian Goh, Ee Peng Lim, Aixin Sun, Yin-Leng Theng, Thi Nhu Quynh Kim, Kalyani Chatterjea, Chew-Hung Chang
Managing Media Rich Geo-Spatial Annotations For A Map-Based Mobile Application Using Clustering, Khasfariyati Razikin, Dion Hoe-Lian Goh, Ee Peng Lim, Aixin Sun, Yin-Leng Theng, Thi Nhu Quynh Kim, Kalyani Chatterjea, Chew-Hung Chang
Research Collection School Of Computing and Information Systems
With the prevalence of mobile devices that are equipped with wireless Internet capabilities and Global Positioning System (GPS) functionality, the creation and access of user-generated content are extended to users on the go. Such content are tied to real world objects, in the form of geospatial annotations, and it is only natural that these annotations are visualized using a map-based approach. However, viewing maps that are filled with annotations could hinder the serendipitous discovery of data, especially on the small screens of mobile devices. This calls for a need to manage the annotations. In this paper, we introduce a mobile …
Practical Id-Based Encryption For Wireless Sensor Network, Cheng-Kang Chu, Joseph K. Liu, Jianying Zhou, Feng Bao, Robert H. Deng
Practical Id-Based Encryption For Wireless Sensor Network, Cheng-Kang Chu, Joseph K. Liu, Jianying Zhou, Feng Bao, Robert H. Deng
Research Collection School Of Computing and Information Systems
In this paper, we propose a new practical identity-based encryption scheme which is suitable for wireless sensor network (WSN). We call it Receiver-Bounded Online/Offline Identity-based Encryption (RB-OOIBE). It splits the encryption process into two parts -- the offline and the online part. In the offline part, all heavy computations are done without the knowledge of the receiver's identity and the plaintext message. In the online stage, only light computations such as modular operation and symmetric key encryption are required, together with the receiver's identity and the plaintext message. Moreover, since each offline ciphertext can be re-used for the same receiver, …
Continuous Spatial Assignment Of Moving Users, Hou U Leong, Kyriakos Mouratidis, Nikos Mamoulis
Continuous Spatial Assignment Of Moving Users, Hou U Leong, Kyriakos Mouratidis, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), …
Information Search Patterns In E-Commerce Product Comparison Services, Fiona Fui-Hoon Nah, Weiyin Hong, Liqiang Chen, Hong-Hee Lee
Information Search Patterns In E-Commerce Product Comparison Services, Fiona Fui-Hoon Nah, Weiyin Hong, Liqiang Chen, Hong-Hee Lee
Research Collection School Of Computing and Information Systems
To facilitate product selection and purchase decisions on e-commerce Web sites, the presentation of product information is very important. In this research, the authors study how disposition styles influence users’ search patterns in product comparison services of e-commerce Web sites. The results show that people use relatively more feature paths and less product paths in vertical disposition style than horizontal disposition style. The findings also indicate that there are relatively more feature paths and less product paths in the first half than second half of the information search paths. This is consistent with Gensch’s two-stage choice model which suggests that …
Cca-Secure Unidirectional Proxy Re-Encryption In The Adaptive Corruption Model Without Random Oracles, Jian Weng, Minrong Chen, Yanjiang Yang, Robert H. Deng, Kefei Chen
Cca-Secure Unidirectional Proxy Re-Encryption In The Adaptive Corruption Model Without Random Oracles, Jian Weng, Minrong Chen, Yanjiang Yang, Robert H. Deng, Kefei Chen
Research Collection School Of Computing and Information Systems
Proxy re-encryption (PRE), introduced by Blaze, Bleumer and Strauss in Eurocrypt’98, allows a semitrusted proxy to convert a ciphertext originally intended for Alice into an encryption of the same message intended for Bob. PRE has recently drawn great interest, and many interesting PRE schemes have been proposed. However, up to now, it is still an important question to come up with a chosen-ciphertext secure unidirectional PRE in the adaptive corruption model. To address this problem, we propose a new unidirectional PRE scheme, and prove its chosen-ciphertext security in the adaptive corruption model without random oracles. Compared with the best known …