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Full-Text Articles in Entire DC Network
Timed Automata Patterns, Jin Song Dong, Ping Hao, Shengchao Qin, Jun Sun, Wang Yi
Timed Automata Patterns, Jin Song Dong, Ping Hao, Shengchao Qin, Jun Sun, Wang Yi
Research Collection School Of Computing and Information Systems
Timed Automata have proven to be useful for specification and verification of real-time systems. System design using Timed Automata relies on explicit manipulation of clock variables. A number of automated analyzers for Timed Automata have been developed. However, Timed Automata lack composable patterns for high-level system design. Specification languages like Timed Communicating Sequential Process (CSP) and Timed Communicating Object-Z (TCOZ) are well suited for presenting compositional models of complex real-time systems. In this work, we define a set of composable Timed Automata patterns based on hierarchical constructs in time-enriched process algebras. The patterns facilitate the hierarchical design of complex systems …
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.
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural models known as fusion architecture for learning, cognition and navigation (FALCON) can incorporate a priori knowledge and perform knowledge refinement and expansion through reinforcement learning. Symbolic rules are formulated based on pre-existing know-how and inserted into FALCON as a priori knowledge. The availability of knowledge enables FALCON to start performing earlier in the initial learning trials. Through a temporal-difference (TD) learning method, the inserted rules can be refined and expanded according to the evaluative feedback signals received …
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Research Collection School Of Computing and Information Systems
Very recently, the concept of Traceable Identity-based Encryption (IBE) scheme (or Accountable Authority Identity based Encryption scheme) was introduced in Crypto 2007. This concept enables some mechanisms to reduce the trust of a private key generator (PKG) in an IBE system. The aim of this paper is threefold. First, we discuss some subtleties in the first traceable IBE scheme in the Crypto 2007 paper. Second, we present an extension to this work by having the PKG’s master secret key retrieved automatically if more than one user secret key are released. This way, the user can produce a concrete proof of …
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 …
Measuring Novelty And Redundancy With Multiple Modalities In Cross-Lingual Broadcast News, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Measuring Novelty And Redundancy With Multiple Modalities In Cross-Lingual Broadcast News, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
News videos from different channels, languages are broadcast everyday, which provide abundant information for users. To effectively search, retrieve, browse and track news stories, news story similarity plays a critical role in assessing the novelty and redundancy among news stories. In this paper, we explore different measures of novelty and redundancy detection for cross-lingual news stories. A news story is represented by multimodal features which include a sequence of keyframes in the visual track, and a set of words and named entities extracted from speech transcript in the audio track. Vector space models and language models on individual features (text, …
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Research Collection School Of Computing and Information Systems
Proactively providing services to mobile individuals is essential for emerging ubiquitous applications. The major challenge in providing users with proactive services lies in continuously monitoring their contexts based on numerous sensors. The context monitoring with rich sensors imposes heavy workloads on mobile devices 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 device can proactively understand users' contexts and react appropriately. This paper proposes …
Electric Elves: What Went Wrong And Why, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Reddy Varakantham, Paul Scerri, David V. Pynadath
Electric Elves: What Went Wrong And Why, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Reddy Varakantham, Paul Scerri, David V. Pynadath
Research Collection School Of Computing and Information Systems
Software personal assistants continue to be a topic of significant research interest. This article outlines some of the important lessons learned from a successfully-deployed team of personal assistant agents (Electric Elves) in an office environment. In the Electric Elves project, a team of almost a dozen personal assistant agents were continually active for seven months. Each elf (agent) represented one person and assisted in daily activities in an actual office environment. This project led to several important observations about privacy, adjustable autonomy, and social norms in office environments. In addition to outlining some of the key lessons learned we outline …
Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis
Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q 2 Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M Q × P such that (i) each point q 2 Q (p 2 P) appears at most k times (at most nce) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|,P q2Q q.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is …
Platform Competition In Digital Systems: Architectural Control And Value Migration, C. Jason Woodard
Platform Competition In Digital Systems: Architectural Control And Value Migration, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Digital systems give rise to complex layered architectures in which products at one layer serve as platforms for applications and services in adjacent layers. Platform owners face a difficult balancing act. On one hand, they need to make their platforms attractive to potential complementors by mitigating the threat of architectural lock-in. On the other hand, platform owners must be careful not to give away too much too soon, or risk being unable to recoup their own investments. This paper presents an agent-based model that explores this tension at both the firm and industry levels. Computational experiments show that boundedly rational …
A Verification System For Timed Interval Calculus, Chunqing Chen, Jin Song Dong, Jun Sun
A Verification System For Timed Interval Calculus, Chunqing Chen, Jin Song Dong, Jun Sun
Research Collection School Of Computing and Information Systems
Timed Interval Calculus (TIC) is a highly expressive set-based notation for specifying and reasoning about embedded real-time systems. However, it lacks mechanical proving support, as its verification usually involves infinite time intervals and continuous dynamics. In this paper, we develop a system based on a generic theorem prover, Prototype Verification System (PVS), to assist formal verification of TIC at a high grade of automation. TIC semantics has been constructed by the PVS typed higher-order logic. Based on the encoding, we have checked all TIC reasoning rules and discovered subtle flaws. A translator has been implemented in Java to automatically transform …
A Dynamic Trust Management Scheme To Mitigate Malware Proliferation In P2p Networks, Xuhua Ding, Wei Yu, Ying Pan
A Dynamic Trust Management Scheme To Mitigate Malware Proliferation In P2p Networks, Xuhua Ding, Wei Yu, Ying Pan
Research Collection School Of Computing and Information Systems
The surge of peer-to-peer (P2P) networks consisting of thousands of of hosts makes them a breeding ground for malware proliferation. Although some existing studies have shown that malware proliferation can pose significant threats to P2P networks, defending against such an attack is largely an open problem. This paper aims to develop the countermeasure that can effectively mitigate the malware proliferation while preserving P2P networks' performance. To this end, we propose a dynamic trust management scheme based upon localized trust evaluation and alert propagation which prevents innocent peers from downloading files from infected peers. Our analysis and experimental results show that …
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 …
A Scalable Approach To Multi-Style Architectural Modeling And Verification, Stephen Wong, Jing Sun, Ian Warren, Jun Sun
A Scalable Approach To Multi-Style Architectural Modeling And Verification, Stephen Wong, Jing Sun, Ian Warren, Jun Sun
Research Collection School Of Computing and Information Systems
Software Architecture represents the high level description of a system in terms of components, external properties and communication. Despite its importance in the software engineering process, the lack of formal description and verification support limits the value of developing architectural models. Automated formal engineering methods can provide an effective means to precisely describe and rigorously verify intended structures and behaviors of software systems. In this paper, we present an approach to support the design and verification of software architectural models using the Alloy analyzer. Based on our earlier work, we propose a fundamental library for specifying system structures in terms …
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 …
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 …
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 …
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 …
Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava
Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
A satisfactory and robust trust model is gaining importance in addressing information overload, and helping users collect reliable information in online communities. Current research on trust prediction strongly relies on a web of trust, which is directly collected from users based on previous experience. However, the web of trust is not always available in online communities and even though it is available, it is often too sparse to predict the trust value between two unacquainted people with high accuracy. In this paper, we propose a framework to derive degree of trust based on users' expertise and users' affinity for certain …
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 …
Harmoni: Context-Aware Filtering Of Sensor Data For Continuous Remote Health Monitoring, Iqbal Mohomed, Archan Misra, Maria Ebling, William Jerome
Harmoni: Context-Aware Filtering Of Sensor Data For Continuous Remote Health Monitoring, Iqbal Mohomed, Archan Misra, Maria Ebling, William Jerome
Research Collection School Of Computing and Information Systems
A promising architecture for remote healthcare monitoring involves the use of a pervasive device (such as a cellular phone), which aggregates data from multiple body-worn medical sensors and transmits the data to the backend. Unfortunately, the volume of data generated by increasingly sophisticated continuouslyactive sensors can overwhelm the resources on the mobile device. We propose imbuing the mobile device with the intelligence to perform context-aware filtering of sensor data streams in order to reduce transmissions in cases where the observed data corresponds to the norm expected by the system in a given context. To investigate the efficacy of this technique, …
Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng
Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng
Research Collection School Of Computing and Information Systems
Wireless broadcast is an efficient way for information dissemination due to its good scalability [10]. Existing works typically assume mobile devices, such as cell phones and PDAs, can access only one channel at a time. In this paper, we consider a scenario of near future where a mobile device has the ability to process queries using information simultaneously received from multiple channels. We focus on the query processing of the transitive nearest neighbor (TNN) search [19]. Two TNN algorithms developed for a single broadcast channel environment are adapted to our new broadcast enviroment. Based on the obtained insights, we propose …
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 …
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 …
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 …
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 …
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.
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 …
Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan
Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
The use of a team of weak learners to learn a dataset has been shown better than the use of one single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be one of the best off-the-shelf classifiers. However, some problems still remain, including determining the optimal number of weak learners and the overfitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of genetic algorithm, weak learner and pattern distributor. In this paper, …
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 …