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Articles 7861 - 7890 of 9003
Full-Text Articles in Computer Sciences
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Research Collection School Of Computing and Information Systems
While mobile computing provides organizations with many information systems implementation alternatives, it is often difficult to predict the potential benefits, limitations, and problems with mobile applications. Given the inherent portability of mobile devices, many design and use issues can arise which do not exist with desktop systems. While many existing rules of thumb for design of stationary systems apply to mobile systems, many new ones emerge. Issues such as the security and privacy of information take on new dimensions, and potential conflicts can develop when a single mobile device serves both personal and business needs. This paper identifies potential issues …
H-Dpop: Using Hard Constraints For Search Space Pruning In Dcop, Akshat Kumar, Adrian Petcu, Boi Faltings
H-Dpop: Using Hard Constraints For Search Space Pruning In Dcop, Akshat Kumar, Adrian Petcu, Boi Faltings
Research Collection School Of Computing and Information Systems
In distributed constraint optimization problems, dynamic programming methods have been recently proposed (e.g. DPOP). In dynamic programming many valuations are grouped together in fewer messages, which produce much less networking overhead than search. Nevertheless, these messages are exponential in size. The basic DPOP always communicates all possible assignments, even when some of them may be inconsistent due to hard constraints. Many real problems contain hard constraints that significantly reduce the space of feasible assignments. This paper introduces H-DPOP, a hybrid algorithm that is based on DPOP, which uses Constraint Decision Diagrams (CDD) to rule out infeasible assignments, and thus compactly …
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance by combining the outputs from multiple ranking algorithms. Many ensemble ranking approaches employ supervised learning techniques to learn appropriate weights for combining multiple rankers. The main shortcoming with these approaches is that the learned weights for ranking algorithms are query independent. This is suboptimal since a ranking algorithm could perform well for certain queries but poorly for others. In this paper, we propose a novel semi-supervised ensemble ranking (SSER) algorithm that learns query-dependent weights when combining …
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Comments left by readers on Web documents contain valuable information that can be utilized in different information retrieval tasks including document search, visualization, and summarization. In this paper, we study the problem of comments-oriented document summarization and aim to summarize a Web document (e.g., a blog post) by considering not only its content, but also the comments left by its readers. We identify three relations (namely, topic, quotation, and mention) by which comments can be linked to one another, and model the relations in three graphs. The importance of each comment is then scored by: (i) graph-based method, where the …
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Excel spreadsheets have been used in many classrooms to teach modeling and analysis of real business problems. This can be done with relative ease but often the modeling approach may be inappropriate and the analysis results not easily implemented. In this article, we illustrate these difficulties with the modeling of the number of equipment required in future years, given demand (historical and projected) and the amount of equipment held. We show how the desired output can be, and needs to be related to the given input. For this purpose, we apply the TREND function to predict data into future years. …
Issues And Procedures In Adopting Structural Equation Modelling Technique, Siu Loon Hoe
Issues And Procedures In Adopting Structural Equation Modelling Technique, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
When applying structural equation modeling (SEM) technique for analytical procedures, various issues are involved. These issues may concern sample size, overall fit indices and approach. Initiates of SEM may find it somewhat daunting in resolving these technical issues. The purpose of this paper is to highlight key issues in adopting SEM technique and various approaches available. This paper provides a discussion on the sample size, fit indices, standardized paths, unidimensionality test and various approaches in relation to SEM. It is hoped that having reviewed the paper, new researchers can devote more time to data analysis instead of procedural issues involved.
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Software evolution incurs difficulties in program comprehension and software verification, and hence it increases the cost of software maintenance. In this study, we propose a novel technique to mine from program execution traces a sound and complete set of statistically significant temporal rules of arbitrary lengths. The extracted temporal rules reveal invariants that the program observes, and will consequently guide developers to understand the program behaviors, and facilitate all downstream applications such as verification and debugging. Different from previous studies that were restricted to mining two-event rules (e.g., (lock) →(unlock)), our algorithm discovers rules of arbitrary lengths. In order to …
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
Research Collection School Of Computing and Information Systems
This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of ervicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and …
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A number of kernel learning algorithms have been proposed to learn kernel functions or matrices from side information (e.g., either labeled examples or pairwise constraints). However, most previous studies are limited to “passive” kernel learning in which side information is provided beforehand. In this paper we present a framework of Active Kernel Learning (AKL) that actively identifies the most informative pairwise constraints for kernel learning. The key challenge of active kernel learning is how to measure the informativeness of an example pair given its …
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Research Collection School Of Computing and Information Systems
Verification techniques like SAT-based bounded model checking have been successfully applied to a variety of system models. Applying bounded model checking to compositional process algebras is, however, not a trivial task. One challenge is that the number of system states for process algebra models is not statically known, whereas exploring the full state space is computationally expensive. This paper presents a compositional encoding of hierarchical processes as SAT problems and then applies state-of-the-art SAT solvers for bounded model checking. The encoding avoids exploring the full state space for complex systems so as to deal with state space explosion. We developed …
Mapping The Multi-Tiered Impacts Of The Growth Of It Industries In India: A Combined Scale-And-Scope Externalities Perspective, Robert J. Kauffman, Ajay Kumar
Mapping The Multi-Tiered Impacts Of The Growth Of It Industries In India: A Combined Scale-And-Scope Externalities Perspective, Robert J. Kauffman, Ajay Kumar
Research Collection School Of Computing and Information Systems
Externalities occur among agglomerated firms. Scale externalities occur between firms in the same industry. Scope externalities occur when heterogeneous industries are collocated. Combined scale-and-scope externalities exist when the scale of one industry is beneficial to the growth of another collocated industry. In the Sein and Haridranath (2004) framework of information technology (IT) impacts on development, scale externalities correspond to second-order impacts, while combined scale and scope eternalities correspond to third-order impacts. We use an agglomeration perspective to explain the growth of IT industries in India. We study growth patterns of four specific IT industries: computer and peripheral equipment manufacturing, semiconductor …
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Research Collection School Of Computing and Information Systems
Sequence, widely appearing in various applications (e.g. event logs, text documents, etc) is an ordered list of objects. Exploring correlated objects in a sequence can provide useful knowledge among the objects, e.g., event causality in event log and word phrases in documents. In this paper, we introduce correlation query that finds correlated pairs of objects often appearing closely to each other in a given sequence. A correlation query is specified by two control parameters, distance bound, the requirement of object closeness, and correlation threshold, the minimum requirement of correlation strength of result pairs. Instead of processing the query by scanning …
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Specification mining is a process of extracting specifications, often from program execution traces. These specifications can in turn be used to aid program understanding, monitoring and verification. There are a number of dynamic-analysis-based specification mining tools in the literature, however none so far extract past time temporal expressions in the form of rules stating: whenever a series of events occurs, previously another series of events has happened. Rules of this format are commonly found in practice and useful for various purposes. Most rule-based specification mining tools only mine future-time temporal expression. Many past-time temporal rules like whenever a resource is …
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Blog/news search engines are very important channels to reach information about the real-time happenings. In this paper, we study the popular queries collected over one year period and compare their search results returned by a blog search engine (i.e., Technorati) and a news search engine (i.e., Google News). We observed that the numbers of hits returned by the two search engines for the same set of queries were highly correlated, suggesting that blogs often provide commentary to current events reported in news. As many popular queries are related to some events, we further observed a high cohesiveness among the returned …
Empirical Analysis Of Certificate Revocation Lists, Daryl Walleck, Yingjiu Li, Shouhuai Xu
Empirical Analysis Of Certificate Revocation Lists, Daryl Walleck, Yingjiu Li, Shouhuai Xu
Research Collection School Of Computing and Information Systems
Managing public key certificates revocation has long been a central issue in public key infrastructures. Though various certificate revocation mechanisms have been proposed to address this issue, little effort has been devoted to the empirical analysis of real-world certificate revocation data. In this paper, we conduct such an empirical analysis based on a large amount of data collected from VeriSign. Our study enables us to understand how long a revoked certificate lives and what the difference is in the lifetime of revoked certificates by certificate types, geographic locations, and organizations. Our study also provides a solid foundation for future research …
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Research Collection School Of Computing and Information Systems
Even today, software projects still suffer from delays and budget overspending. The causes for this problem are compounded when the project team is distributed across different locations and generally attributed to the decreasing ability to communicate well (due to cultural, linguistic, and physical distance). Many projects, especially those with off-shoring component, consist of small iterations with changes, deletions and additions, yet there is no formal model of the flow of iterations available. A number of commercially available project prediction tools for projects as a whole exist, but the model adaptation process by iteration, if it exists, is unclear. Furthermore, no …
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Research Collection School Of Computing and Information Systems
A significant portion of the services industry is focused on providing services (medical, legal, financial, personal, and travel) to individuals. However, studies have shown that a less visible but rapidly growing segment of the service sector comprises firms that provide business functions to other businesses. The sector covers tasks such as payroll processing, procurement, and information systems management, as well as business consulting, technical support, call center operations, and software development. Firms may choose to purchase, rather than perform, these business functions to reduce costs, to mitigate risk, or simply to focus on their processes that provide marketplace differentiation. Transferring …
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Given a set of data points P and a query point q in a multidimensional space, Reverse Nearest Neighbor (RNN) query finds data points in P whose nearest neighbors are q. Reverse k-Nearest Neighbor (RkNN) query (where k ≥ 1) generalizes RNN query to find data points whose kNNs include q. For RkNN query semantics, q is said to have influence to all those answer data points. The degree of q's influence on a data point p (∈ P) is denoted by κp where q is the κp-th NN of p. We introduce a new variant of RNN query, namely, …
Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith
Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith
Research Collection School Of Computing and Information Systems
In this paper, we consider the problem of assisting a busy user in managing her workload of pending tasks. We assume that our user is typically oversubscribed, and is invariably juggling multiple concurrent streams of tasks (or work flows) of varying importance and urgency. There is uncertainty with respect to the duration of a pending task as well as the amount of follow-on work that may be generated as a result of executing the task. The user’s goal is to be as productive as possible; i.e., to execute tasks that realize the maximum cumulative payoff. This is achieved by enabling …
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 …
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 …
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.
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 …
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 …
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 …
Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Trust between a pair of users is an important piece of information for users in an online community (such as electronic commerce websites and product review websites) where users may rely on trust information to make decisions. In this paper, we address the problem of predicting whether a user trusts another user. Most prior work infers unknown trust ratings from known trust ratings. The effectiveness of this approach depends on the connectivity of the known web of trust and can be quite poor when the connectivity is very sparse which is often the case in an online community. In this …
Use Of Cognitive Mapping Techniques In Information Systems Development, Keng Siau, X. Tan
Use Of Cognitive Mapping Techniques In Information Systems Development, Keng Siau, X. Tan
Research Collection School Of Computing and Information Systems
Cognitive mapping techniques as a communication tool can be used in various information systems (IS) development and implementation activities. The three major cognitive mapping techniques include causal mapping, semantic mapping, and concept mapping. A causal map represents a set of causal relationships among constructs within a belief system. Semantic mapping, also known as idea mapping, is used to explore an idea without the constraints of a superimposed structure. The result of concept mapping is a graphical representation in which nodes represent concepts and links represent the relationships between concepts. Cognitive mapping techniques have been proposed to be applied in requirements …