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Articles 5131 - 5160 of 5707
Full-Text Articles in Entire DC Network
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
Research Collection School Of Computing and Information Systems
Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by …
Social Network Dynamics For Open Source Software Projects, Y. Long, Keng Siau
Social Network Dynamics For Open Source Software Projects, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
Drawing on social network theories and previous studies, this research is an initial effort to explore the dynamics of the social network structure in Open Source Software (OSS) teams. Three projects were selected from SourceForge.net in term of their similarities as well as their differences. Monthly data were extracted from the bug tracking system in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of network structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a …
Understanding Intrinsic Factors Influencing Benefit Maximization Of Is Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Intrinsic Factors Influencing Benefit Maximization Of Is Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This research uses the Repertory Grid technique to understand intrinsic factors influencing benefit maximization of IS usage. The results show that domain-relevant skills, task motivation, cognitive/work style attributes, individual characteristics (identified as creativity traits) and personal characteristics (identified as innovativeness traits) influence benefit maximization of IS usage. The findings not only provide insights on ways to increase quality of IS usage in organizations but are also helpful for identifying approaches that foster attributes leading to increased benefit realization from IS usage.
A Hybrid Architecture Combining Reactive Plan Execution And Reactive Learning, Samin Karim, Liz Sonenberg, Ah-Hwee Tan
A Hybrid Architecture Combining Reactive Plan Execution And Reactive Learning, Samin Karim, Liz Sonenberg, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Developing software agents has been complicated by the problem of how knowledge should be represented and used. Many researchers have identified that agents need not require the use of complex representations, but in many cases suffice to use “the world” as their representation. However, the problem of introspection, both by the agents themselves and by (human) domain experts, requires a knowledge representation with a higher level of abstraction that is more ‘understandable’. Learning and adaptation in agents has traditionally required knowledge to be represented at an arbitrary, low-level of abstraction. We seek to create an agent that has the capability …
Bias And Controversy: Beyond The Statistical Deviation, Hady W. Lauw, Ee Peng Lim, Ke Wang
Bias And Controversy: Beyond The Statistical Deviation, Hady W. Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a 'data-centric approach' where the evaluation data is assumed to represent the ground truth'. The standard statistical approaches take evaluation and deviation at face value. We argue that attention should be paid to the subjectivity of evaluation, judging the evaluation score not just on 'what is being said' (deviation), but also on 'who says it' (reviewer) as well as on 'whom it is said about' (object). Furthermore, we observe that bias …
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
OntoSearch, a full-text search engine that exploits ontological knowledge for document retrieval, is presented in this paper. Different from other ontology based search engines, OntoSearch does not require a user to specify the associated concepts of his/her queries. Domain ontology in OntoSearch is in the form of a semantic network. Given a keyword based query, OntoSearch infers the related concepts through a spreading activation process in the domain ontology. To provide personalized information access, we further develop algorithms to learn and exploit user ontology model based on a customized view of the domain ontology. The proposed system has been applied …
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when point-to-point (P2P) constraint is imposed on the bag-of-words. We conduct investigation on two tasks: near-duplicate keyframe (NDK) retrieval, and high-level concept classification, covering parts of TRECVID 2003 and 2005 datasets. In P2P matching, we propose a one-to-one symmetric keypoint matching strategy to diminish the noise effect during keyframe comparison. In addition, a new multi-dimensional index structure is proposed to speed up the matching process with keypoint filtering. Through experiments, we demonstrate that P2P constraint can …
A Novel Privacy Preserving Authentication And Access Control Scheme For Pervasive Computing Environments, K. Ren, Wenjing Lou, K. Kim, Robert H. Deng
A Novel Privacy Preserving Authentication And Access Control Scheme For Pervasive Computing Environments, K. Ren, Wenjing Lou, K. Kim, Robert H. Deng
Research Collection School Of Computing and Information Systems
Privacy and security are two important but seemingly contradictory objectives in a pervasive computing environment (PCE). On one hand, service providers want to authenticate legitimate users and make sure they are accessing their authorized services in a legal way. On the other hand, users want to maintain the necessary privacy without being tracked down for wherever they are and whatever they are doing. In this paper, a novel privacy preserving authentication and access control scheme to secure the interactions between mobile users and services in PCEs is proposed. The proposed scheme seamlessly integrates two underlying cryptographic primitives, namely blind signature …
Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai
Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai
Research Collection School Of Computing and Information Systems
In information retrieval, retrieving relevant passages, as opposed to whole documents, not only directly benefits the end user by filtering out the irrelevant information within a long relevant document, but also improves retrieval accuracy in general. A critical problem in passage retrieval is to extract coherent relevant passages accurately from a document, which we refer to as passage extraction. While much work has been done on passage retrieval, the passage extraction problem has not been seriously studied. Most existing work tends to rely on presegmenting documents into fixed-length passages which are unlikely optimal because the length of a relevant passage …
Autonomic Management Of Stream Processing Applications Via Adaptive Bandwidth Control, Dimitrios Pendarakis, Jeremy Silber, Laura Wynter
Autonomic Management Of Stream Processing Applications Via Adaptive Bandwidth Control, Dimitrios Pendarakis, Jeremy Silber, Laura Wynter
Research Collection School Of Computing and Information Systems
We present a novel autonomic control system for high performance stream processing systems. The system uses bandwidth controls on incoming or outgoing streams to achieve a desired resource utilization balance among a set of concurrently executing stream processing tasks. We show that CPU prioritization and allocation mechanisms in schedulers and virtual machine managers are not sufficient to control such I/O-centric applications, and present an autonomic bandwidth control system that adaptively adjusts incoming and outgoing traffic rates to achieve system management goals. The system dynamically learns the bandwidth rate necessary to meet the system management goals using stochastic nonlinear optimization, and …
Mobile Healthcare Informatics, Keng Siau, Zixing Shen
Mobile Healthcare Informatics, Keng Siau, Zixing Shen
Research Collection School Of Computing and Information Systems
Advances in wireless technology give pace to the rapid development of mobile applications. The coming mobile revolution will bring dramatic and fundamental changes to our daily life. It will influence the way we live, the way we do things, and the way we take care of our health. For the healthcare industry, mobile applications provide a new frontier in offering better care and services to patients, and a more flexible and mobile way of communicating with suppliers and patients. Mobile applications will provide important real time data for patients, physicians, insurers, and suppliers. In addition, it will revolutionalize the way …
Cognitive Mapping Techniques For User-Database Interaction, Keng Siau, X. Tan
Cognitive Mapping Techniques For User-Database Interaction, Keng Siau, X. Tan
Research Collection School Of Computing and Information Systems
In this paper, we first develop a framework of user-database interaction. Based on this framework, we then provide a discussion on how notable human factors influence various dimensions of user-database interaction. Following that, we propose using cognitive mapping techniques to overcome some cognitive and behavioral biases during user-database interaction. Three popular cognitive mapping techniques-causal mapping, semantic mapping, and concept mapping-are introduced as techniques to elicit an individual's belief systems regarding a problem domain. Through an example database application, we demonstrate how to use these cognitive mapping techniques to improve user-database interaction. Finally, we discuss the implications of this research for …
Security Analysis On A Conference Scheme For Mobile Communications, Zhiguo Wan, Feng Bao, Robert H. Deng, A. L. Ananda
Security Analysis On A Conference Scheme For Mobile Communications, Zhiguo Wan, Feng Bao, Robert H. Deng, A. L. Ananda
Research Collection School Of Computing and Information Systems
The conference key distribution scheme (CKDS) enables three or more parties to derive a common conference key to protect the conversation content in their conference. Designing a conference key distribution scheme for mobile communications is a difficult task because wireless networks are more susceptible to attacks and mobile devices usually obtain low power and limited computing capability. In this paper we study a conference scheme for mobile communications and find that the scheme is insecure against the replay attack. With our replay attack, an attacker with a compromised conference key can cause the conferees to reuse the compromised conference key, …
Can Online Reviews Reveal A Product's True Quality? Empirical Findings Analytical Modeling Of Online Word-Of-Mouth Communication, Nan Hu, Paul Pavlou, Jennifer Zhang
Can Online Reviews Reveal A Product's True Quality? Empirical Findings Analytical Modeling Of Online Word-Of-Mouth Communication, Nan Hu, Paul Pavlou, Jennifer Zhang
Research Collection School Of Computing and Information Systems
As a digital version of word-of-mouth, online review has become a major information source for consumers and has very important implications for a wide range of management activities. While some researchers focus their studies on the impact of online product review on sales, an important assumption remains unexamined, that is, can online product review reveal the true quality of the product? To test the validity of this key assumption, this paper first empirically tests the underlying distribution of online reviews with data from Amazon. The results show that 53% of the products have a bimodal and non-normal distribution. For these …
Multilearner Based Recursive Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan, Laxmi R. Iyer
Multilearner Based Recursive Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan, Laxmi R. Iyer
Research Collection School Of Computing and Information Systems
In supervised learning, most single solution neural networks such as constructive backpropagation give good results when used with some datasets but not with others. Others such as probabilistic neural networks (PNN) fit a curve to perfection but need to be manually tuned in the case of noisy data. Recursive percentage based hybrid pattern training (RPHP) overcomes this problem by recursively training subsets of the data, thereby using several neural networks. MultiLearner based recursive training (MLRT) is an extension of this approach, where a combination of existing and new learners are used and subsets are trained using the weak learner which …
Large-Scale Text Categorization By Batch Mode Active Learning, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Large-Scale Text Categorization By Batch Mode Active Learning, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the human efforts in labeling text documents for building reliable classification models. In the past, there have been many studies on applying active learning methods to automatic text categorization, which try to select the most informative documents for labeling manually. Most of these studies focused on selecting a single unlabeled document in each iteration. As a result, the text categorization model has to be retrained after each labeled document is solicited. In this paper, we present …
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Research Collection School Of Computing and Information Systems
Motivated by the studies in Gestalt principle, this paper describes a novel approach on the adaptive selection of visual features for trademark retrieval. We consider five kinds of visual saliencies: symmetry, continuity, proximity, parallelism and closure property. The first saliency is based on Zernike moments, while the others are modeled by geometric elements extracted illusively as a whole from a trademark. Given a query trademark, we adaptively determine the features appropriate for retrieval by investigating its visual saliencies. We show that in most cases, either geometric or symmetric features can give us good enough accuracy. To measure the similarity of …
Clip-Based Similarity Measure For Query-Dependent Clip Retrieval And Video Summarization, Yuxin Peng, Chong-Wah Ngo
Clip-Based Similarity Measure For Query-Dependent Clip Retrieval And Video Summarization, Yuxin Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to visual and granularity factors. We apply the similarity measure for two tasks: retrieval and summarization. In video retrieval, a hierarchical retrieval framework is constructed based on MM and OM. The validity of the framework is theoretically proved and empirically verified on a video database of 21 …
Guest Editorial: Mobile Technology In Education, Keng Siau, Fiona Fui-Hoon Nah
Guest Editorial: Mobile Technology In Education, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
No abstract provided.
Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical need, while the uncertainty inherent to the mobile environment makes missing context values a major concern. This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive experiments on a restaurant recommender system showed that our mechanism can accurately discover causal dependencies among context, thereby enabling the effective identification of the minimal set of important context for a specific user and task, as well as providing highly accurate recommendations even …
Time-Dependent Semantic Similarity Measure Of Queries Using Historical Click-Through Data, Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma
Time-Dependent Semantic Similarity Measure Of Queries Using Historical Click-Through Data, Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma
Research Collection School Of Computing and Information Systems
It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of click-through data logged by Web search engines, which record the interactions between users and the search engines. Most existing approaches employ the click-through data for similarity measure of queries with little consideration of the temporal factor, while the click-through data is often dynamic and contains rich temporal information. In this paper we present a new framework of time-dependent query semantic similarity model on exploiting the temporal characteristics of historical click-through data. The intuition is that more accurate semantic similarity values between …
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Research Collection School Of Computing and Information Systems
The popular models for repairable item inventory, both in the literature as well as practical applications, assume that the demands for items are independent of the number of working systems. However this assumption can introduce a serious underestimation of availability when the number of working systems is small, the failure rate is high or the repair time is long. In this paper, we study a multi-echelon repairable item inventory system under the phenomenon of passivation, i.e. serviceable items are passivated (“switched off”) upon system failure. This work is motivated by corrective maintenance of high-cost technical equipment in the miltary. We …
A Practical Password-Based Two-Server Authentication And Key Exchange System, Yanjiang Yang, Robert H. Deng, Feng Bao
A Practical Password-Based Two-Server Authentication And Key Exchange System, Yanjiang Yang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Most password-based user authentication systems place total trust on the authentication server where cleartext passwords or easily derived password verification data are stored in a central database. Such systems are, thus, by no means resilient against offline dictionary attacks initiated at the server side. Compromise of the authentication server by either outsiders or insiders subjects all user passwords to exposure and may have serious legal and financial repercussions to an organization. Recently, several multiserver password systems were proposed to circumvent the single point of vulnerability inherent in the single-server architecture. However, these multiserver systems are difficult to deploy and operate …
Efficient Client-To-Server Assignments For Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Efficient Client-To-Server Assignments For Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Research Collection School Of Computing and Information Systems
Distributed Virtual Environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently assign …
Effect Of Changing Requirements: A Tracking Mechanism For The Analysis Workflow, Subhajit Datta, Robert Van Engelen
Effect Of Changing Requirements: A Tracking Mechanism For The Analysis Workflow, Subhajit Datta, Robert Van Engelen
Research Collection School Of Computing and Information Systems
Managing the effects of changing requirements remains one of the greatest challenges of enterprise software development. The iterative and incremental model provides an expedient framework for addressing such concerns. This paper presents a set of metrics - Mutation Index, Component Set, Dependency Index - and a methodology to measure the effects of requirement changes in the analysis workflow from one iteration to another. Results from a sample case study are included to highlight a usage scenario. Future directions of our work based on this mechanism are also discussed.
A Unified Log-Based Relevance Feedback Scheme For Image Retrieval, Steven Hoi, Michael R. Lyu, Rong Jin
A Unified Log-Based Relevance Feedback Scheme For Image Retrieval, Steven Hoi, Michael R. Lyu, Rong Jin
Research Collection School Of Computing and Information Systems
Relevance feedback has emerged as a powerful tool to boost the retrieval performance in content-based image retrieval (CBIR). In the past, most research efforts in this field have focused on designing effective algorithms for traditional relevance feedback. Given that a CBIR system can collect and store users' relevance feedback information in a history log, an image retrieval system should be able to take advantage of the log data of users' feedback to enhance its retrieval performance. In this paper, we propose a unified framework for log-based relevance feedback that integrates the log of feedback data into the traditional relevance feedback …
Experimental And Empirical Perspectives On Grid Resource Allocation For The Singapore Market, Danny Oh, Steven Miller, Nan Hu
Experimental And Empirical Perspectives On Grid Resource Allocation For The Singapore Market, Danny Oh, Steven Miller, Nan Hu
Research Collection School Of Computing and Information Systems
In this paper, we describe our work on using the Tycoon system developed by HP Labs to provide a market-based resource allocation and bidding framework for a grid. We discuss how we intend to evaluate the feasibility of the Tycoon system by measuring its economic performance using agent-based simulation experiments for a particular type of grid usage scenario, namely, the digital media market scenario. We will also discuss a related effort in collecting and using real grid data from the National Grid Pilot Platform in Singapore and how we will be using real data collected to derive actual usage patterns …
Enterprise Agility And The Enabling Role Of Information Technology, Eric Overby, Anandhi S. Bharadwaj, V. Sambamurthy
Enterprise Agility And The Enabling Role Of Information Technology, Eric Overby, Anandhi S. Bharadwaj, V. Sambamurthy
Research Collection School Of Computing and Information Systems
In turbulent environments, enterprise agility, that is, the ability of firms to sense environmental change and respond readily, is an important determinant of firm success. We define and deconstruct enterprise agility, delineate enterprise agility from similar concepts in the business research literature, explore the underlying capabilities that support enterprise agility, explicate the enabling role of information technology (IT) and digital options, and propose a method for measuring enterprise agility. The concepts in this paper are offered as foundational building blocks for the overall research program on enterprise agility and the enabling role of IT.
Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu
Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a …
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Research Collection School Of Computing and Information Systems
This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary