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Full-Text Articles in Entire DC Network
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Research Collection School Of Computing and Information Systems
To generate a believable and dynamic virtual world is a great challenge in interactive storytelling. In this paper, we propose a model, namely evolutionary fuzzy cognitive map (E-FCM), to model the dynamic causal relationships among different context variables. As an extension to conventional FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the probabilistic property of causal relationships, and asynchronous activity update of the concepts. With this model, the context variables evolve in a dynamic and uncertain manner with the according evolving time. As a result, the virtual world is presented more realistically and dynamically.
An Experimental Study On U-Commerce Adoption: Impact Of Personalization And Privacy Concerns, H. Sheng, Fiona Fui-Hoon Nah, Keng Siau
An Experimental Study On U-Commerce Adoption: Impact Of Personalization And Privacy Concerns, H. Sheng, Fiona Fui-Hoon Nah, Keng Siau
Research Collection School Of Computing and Information Systems
Ubiquitous commerce (u-commerce) represents “anytime, anywhere” commerce. U-commerce can provide a high level of personalization, which can bring significant benefits to customers. However, privacy is a major concern to customers and an obstacle to the adoption of u-commerce. This research examines how personalization and context can impact customers’ privacy concerns as well as intention to adopt u-commerce applications. As u-commerce is new and emerging, we used the scenario-based approach to operationalize personalization and context in an experimental study. The experimental results show that the effects of personalization on customers’ privacy concerns and adoption intention are situation dependent.
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Research Collection School Of Computing and Information Systems
In this paper we develop a learning-mediated model of offshore software project productivity and quality to examine whether widely adopted structured software processes are effective in mitigating the negative effects of work dispersion in offshore software development. We explicate how the key process areas of the capability maturity model (CMM) can be utilized as a platform to launch learning routines in offshore software development and thereby explain why some offshore software development process improvement initiatives are more effective than others. We validate our learning-mediated model of offshore software project performance by utilizing data collected from 42 offshore software projects of …
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Research Collection School Of Computing and Information Systems
When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed controversy rank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user …
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer …
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Research Collection School Of Computing and Information Systems
In a multisystem environment where a mobile node can utilize multiple interfaces and simultaneously connect to multiple providers, new opportunities exist for efficient location management strategies spanning heterogeneous cellular wireless networks. In this paper, an integrated framework is developed for location management in such a multi-system, fourth generation (4 G) wireless networks. This information-theoretic framework allows each individual sub-system to operate fairly independently, and does not require the knowledge of individual sub-network topologies. An efficient location management in such a loosely coupled network is designed by having a mobile node view its movement as a vector-valued sequence, and then transmit …
Advances And Challenges For Scalable Provenance In Stream Processing Systems, Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby Sow, Min Wang
Advances And Challenges For Scalable Provenance In Stream Processing Systems, Archan Misra, Marion Blount, Anastasios Kementsietsidis, Daby Sow, Min Wang
Research Collection School Of Computing and Information Systems
While data provenance is a well-studied topic in both database and workflow systems, its support within stream processing systems presents a new set of challenges. Part of the challenge is the high stream event rate and the low processing latency requirements imposed by many streaming applications. For example, emerging streaming applications in healthcare or finance call for data provenance, as illustrated in the Century stream processing infrastructure that we are building for supporting online healthcare analytics. At anytime, given an output data element (e.g., a medical alert) generated by Century, the system must be able to retrieve the input and …
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
A critical issue of large-scale multimedia retrieval is how to develop an effective framework for ranking the search results. This problem is particularly challenging for content-based video retrieval due to some issues such as short text queries, insufficient sample learning, fusion of multimodal contents, and large-scale learning with huge media data. In this paper, we propose a novel multimodal and multilevel (MMML) ranking framework to attack the challenging ranking problem of content-based video retrieval. We represent the video retrieval task by graphs and suggest a graph based semi-supervised ranking (SSR) scheme, which can learn with small samples effectively and integrate …
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, relevance feedback has been adopted as a promising approach to improve the search performance. In this paper, we propose a novel idea of learning with historical relevance feedback log data, and adopt a new paradigm called “Collaborative Image Retrieval” (CIR). To effectively explore the log data, we propose a novel semi-supervised distance metric learning technique, called “Laplacian Regularized Metric Learning” (LRML), for learning robust distance metrics for CIR. Different from previous methods, the proposed LRML method integrates both …
Multi-View Ear Recognition Based On B-Spline Pose Manifold Construction, Zhiyuan Zhang, Heng Liu
Multi-View Ear Recognition Based On B-Spline Pose Manifold Construction, Zhiyuan Zhang, Heng Liu
Research Collection School Of Computing and Information Systems
In this work, multi-view ear recognition problems are examined in detail. A new multi-view ear recognition approach based on B-Spline pose manifold construction in discriminative projection space which is formed by null kernel discriminant analysis (NKDA) feature extraction is presented. Many experiments and comparisons are provided to show the effectiveness of our multi-view ear recognition approach.
Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan
Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online servers over extended periods of time. A breached server that is not detected in time may return incorrect query answers to users. In this article, we introduce authentication schemes for users to verify that their query answers from an online server are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values are legitimate). We introduce a scheme that supports range selection, projection as well as primary key-foreign key join queries on relational databases. We also …
Architectural Control Points, C. Jason Woodard
Architectural Control Points, C. Jason Woodard
Research Collection School Of Computing and Information Systems
System designers and technology strategists have long recognized the concept of an architectural control point as a way to identify parts of a system that have particular strategic importance. Despite the vast body of work on system architecture in the engineering design literature, however, few authors have attempted to define architectural control points or study them systematically. Moreover, some industry participants have questioned whether architectural control is still a valuable or achievable goal in an era of increasingly open standards. This paper offers tentative definitions of architectural control, architectural control points, and architectural strategy. In a longer version of the …
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
Research Collection School Of Computing and Information Systems
Semantic Web services have been one of the most significant research areas within the semantic Web vision, and have been recognized as a promising technology that exhibits huge commercial potential. Current semantic Web service research focuses on defining models and languages for the semantic markup of all relevant aspects of services, which are accessible through a Web service interface. The Web service modelling ontology (WSMO) is one of the most significant semantic Web service framework proposed to date. To support the standardization and tool support of WSMO, a formal semantics of the language is highly desirable. As there are a …
Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha
Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha
Research Collection School Of Computing and Information Systems
This paper focuses on the problem of increasing the traffic capacity (volume of admissible traffic) of broadcast and multicast flows in a wireless mesh network (WMN). We study and suggest routing strategies where the process of constructing the forwarding tree considers three distinct features: (a) the ability of individual mesh nodes to perform link-layer broadcasts at multiple rates, (b) the wireless broadcast advantage, whereby a single broadcast transmission covers multiple neighboring receivers and (c) the residual transmission capacity at a WMN node, subject to intereference-based constraints from existing traffic flows in its neighborhood. Our metric of interest is the total …
Benefiting From Customer And Competitor Knowledge: A Market-Based Approach To Organisational Learning, Siu Loon Hoe
Benefiting From Customer And Competitor Knowledge: A Market-Based Approach To Organisational Learning, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
PurposeThe purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market‐based approach to organizational learning.Design/methodology/approachThe extant organizational learning and market orientation literature was reviewed, and the salient points on how adopting a market‐based approach to organizational learning promotes competitive advantage are discussed.FindingsOrganizational behavior scholars have devoted a lot attention on the factors and conditions affecting organizational learning. The end outcome, of course, is to improve organizational performance. Marketing scholars, on the other, focused on the effect of market …
K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay
K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay
Research Collection School Of Computing and Information Systems
Because most animation tools are complex and timeconsuming to learn and use, most animations today are created by experts. To help novices create a wide range of animations quickly, we have developed a general-purpos informal, 2D animation sketching system called K-Sketch. Field studies investigating the needs of animatorsnd would-be animators helped us collect a library of usage scenarios for our tool. A novel optimization technique enabled us to design an interface that is simultaneously fast, simple, and powerful. The result is a pen-based system that relies on users’ intuitive sense of space and time while still supporting a wide range …
E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan
E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan
Research Collection School Of Computing and Information Systems
This paper offers a macro perspective of the various activities involved in the implementation of e-government through an interpretive analysis of the various e-government-related initiatives undertaken by the Singapore Government. The analysis lead to the identification of four main components in the implementation of e-government, namely (i) information content, (ii) ICT infrastructure, (iii) e-government infostructure, and (iv) e-government promotion. These four components were then conceptually integrated into the e-Government Implementation Framework. This paper suggests that this framework can either be used as a descriptive tool to organize and coordinate various e-government initiatives, or be used as a prescriptive structure to …
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange is a kind of protocols to solve the problem of fair exchange between two parties. Almost all the previous work on this topic are provably secure only in the random oracle model. In PKC 2007, Dodis et al. considered optimistic fair exchange in a multi-user setting, and showed that the security of an optimistic fair exchange in a single-user setting may no longer be secure in a multi-user setting. Besides, they also proposed one and reviewed several previous construction paradigms and showed that they are secure in the multi-user setting. However, their proofs are either in the …
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Research Collection School Of Computing and Information Systems
Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …
Perceptions Becoming Reality: Bridging The Market Knowledge Gap, Siu Loon Hoe
Perceptions Becoming Reality: Bridging The Market Knowledge Gap, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
PurposeOrganizations constantly strive to learn about new market trends and ideas to stay ahead of the game. However, with an increased demand of market knowledge, how does the organization motivate employees to constantly acquire and disseminate market knowledge? The purpose of this paper is to highlight the perceived importance of market knowledge in promoting continuous employee acquisition and dissemination of customer and competitor knowledge.Design/methodology/approachThe perceived importance of market knowledge concept is highlighted and discussed.FindingsThe paper offers a view on how management could address the increased demand for market knowledge and how the development and learning team could provide further support …
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Research Collection School Of Computing and Information Systems
This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …
On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang
On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang
Research Collection School Of Computing and Information Systems
Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with controversial content. They also occur frequently among contributors who are "aggressive" or controversial in their personalities. In this paper, we aim to identify controversial articles in Wikipedia. We propose three models, namely the Basic model and two Controversy Rank (CR) models. These models draw clues from collaboration and edit history instead of interpreting the actual articles or edited content. While …
Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Face annotation in images and videos enjoys many potential applications in multimedia information retrieval. Face annotation usually requires many training data labeled by hand in order to build effective classifiers. This is particularly challenging when annotating faces on large-scale collections of media data, in which huge labeling efforts would be very expensive. As a result, traditional supervised face annotation methods often suffer from insufficient training data. To attack this challenge, in this paper, we propose a novel Transductive Kernel Fisher Discriminant (TKFD) scheme for face annotation, which outperforms traditional supervised annotation methods with few training data. The main idea of …
Benford And Your Taxes, Manoj Thulasidas
Benford And Your Taxes, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
Nothing is certain but death and taxes, they say. On the death front, we are making some inroads with all our medical marvels, at least in postponing it if not actually avoiding it. But when it comes to taxes, we have no defense other than a bit of creativity in our tax returns.
Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston
Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other …
A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang
A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang
Research Collection School Of Computing and Information Systems
The emergence of information and communication technologies infrastructure has transformed the global economy. The development of information technology infrastructure is limited to some developed countries though. This research explores the role of information technology infrastructure in B2C e-commerce growth at the country-level from the perspective of growth theory in economics. We propose a hybrid exogenous and endogenous growth model to explain e-commerce growth. We estimate a panel data model that incorporates the direct effects of e-commerce infrastructure and other key explanatory variables. We further specify a simultaneous effects model that permits the analysis of reverse causality in the association between …
Factors Affecting The Information Quality Of Personal Web Portfolios, P. Katerattanakul, Keng Siau
Factors Affecting The Information Quality Of Personal Web Portfolios, P. Katerattanakul, Keng Siau
Research Collection School Of Computing and Information Systems
Personal Web portfolios have become a popular information source and an effective method for individuals to present themselves to others in cyberspace. Thus, the quality of personal Web portfolios is critical and affects the perception that others have of the individuals. But how do we measure quality of personal Web portfolios? What are the important factors affecting quality of personal Web portfolios? This study presents the development of an instrument measuring factors affecting information quality of personal Web portfolios. The proposed instrument, based on the Information Quality framework, was refined and validated to assess its construct validity, convergent validity, and …
Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Research Collection School Of Computing and Information Systems
Classical multi-echelon repairable item inventory models are based either on steady-state analysis or infinite repair capacity, which may not work well in situations when the demand is nonstationary, or repair capacity is limited. In this paper, we propose an analytical model for evaluating system performance that works well under limited repair capacity and nonstationary demands. Following the METRIC methodology, we then develop an optimisation algorithm to solve the corrective maintenance problem in military logistics. Experimental results show that our approach yields good solutions efficiently. This work has also resulted in a software that has been field-tested by a military organisation.
The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao
The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao
Research Collection School Of Computing and Information Systems
In this work, we liken the solving of combinatorial optimization problems under a prescribed computational budget as hunting for oil in an unexplored ground. Using this generic model, we instantiate an iterative deepening genetic annealing (IDGA) algorithm, which is a variant of memetic algorithms. Computational results on the traveling salesman problem show that IDGA is more effective than standard genetic algorithms or simulated annealing algorithms or a straightforward hybrid of them. Our model is readily applicable to solve other combinatorial optimization problems.
Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang
Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang
Research Collection School Of Computing and Information Systems
Searchable encryption schemes allow users to perform keyword based searches on an encrypted database. Almost all existing such schemes only consider the scenario where a single user acts as both the data owner and the querier. However, most databases in practice do not just serve one user; instead, they support search and write operations by multiple users. In this paper, we systematically study searchable encryption in a practical multi-user setting. Our results include a set of security notions for multi-user searchable encryption as well as a construction which is provably secure under the newly introduced security notions.