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Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Integrated Cognitive Architectures: A Survey, Hui-Qing Chong, Ah-Hwee Tan, Gee-Wah Ng
Research Collection School Of Computing and Information Systems
This article aims to present an account of the state of the art research in the field of integrated cognitive architectures by providing a review of six cognitive architectures, namely Soar, ACT-R, ICARUS, BDI, the subsumption architecture and CLARION. We conduct a detailed functional comparison by looking at a wide range of cognitive components, including perception, memory, goal representation, planning, problem solving, reasoning, learning, and relevance to neurobiology. In addition, we study the range of benchmarks and applications that these architectures have been applied to. Although no single cognitive architecture has provided a full solution with the level of human …
Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan
Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Web information fusion can be defined as the problem of collating and tracking information related to specific topics on the World Wide Web. Whereas most existing work on Web information fusion has focused on text-based multidocument summarization, this paper concerns the topic of image and text association, a cornerstone of cross-media Web information fusion. Specifically, we present two learning methods for discovering the underlying associations between images and texts based on small training data sets. The first method based on vague transformation measures the information similarity between the visual features and the textual features through a set of predefined domain-specific …
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Situation awareness modelling is popularly used in the command and control domain for situation assessment and decision support. However, situation models in real-world applications are typically complex and not easy to use. This paper presents a Context-aware Decision Support (CaDS) system, which consists of a situation model for shared situation awareness modelling and a group of entity agents, one for each individual user, for focused and customized decision support. By incorporating a rule-based inference engine, the entity agents provide functions including event classification, action recommendation, and proactive decision making. The implementation and the performance of the proposed system are demonstrated …
Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li
Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li
Research Collection School Of Computing and Information Systems
In this paper, we introduce a novel indexing scheme-query context tree (QUC-tree) to facilitate efficient query sensitive music search under different query contexts. Distinguished from the previous approaches, QUC-tree is a balanced multiway tree structure, where each level represents the data space at different dimensionality. Before the tree structure construction, principle component analysis (PCA) is applied for data analysis and transforming the raw composite features into a new feature space sorted by the importance of acoustic features. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an …
Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Wireless sensor networks have been widely used in civilian and military applications. Primarily designed for monitoring purposes, many sensor applications require continuous collection and processing of sensed data. Due to the limited power supply for sensor nodes, energy efficiency is a major performance concern in query processing. In this paper, we focus on continuous kNN query processing in object tracking sensor networks. We propose a localized scheme to monitor nearest neighbors to a query point. The key idea is to establish a monitoring area for each query so that only the updates relevant to the query are collected. The monitoring …
Tuning On-Air Signatures For Balancing Performance And Confidentiality, Baihua Zheng, Wang-Chien Lee, Peng Liu, Dik Lun Lee, Xuhua Ding
Tuning On-Air Signatures For Balancing Performance And Confidentiality, Baihua Zheng, Wang-Chien Lee, Peng Liu, Dik Lun Lee, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, we investigate the trade off between performance and confidentiality in signature-based air indexing schemes for wireless data broadcast. Two metrics, namely, false drop probability and false guess probability, are defined to quantify the filtering efficiency and confidentiality loss of a signature scheme. Our analysis reveals that false drop probability and false guess probability share a similar trend as the tuning parameters of a signature scheme change and it is impossible to achieve a low false drop probability and a high false guess probability simultaneously. In order to balance the performance and confidentiality, we perform an analysis to …
Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen
Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen
Research Collection School Of Computing and Information Systems
This paper studies the dynamic web service selection problem in a failure-prone environment, which aims to determine a subset of Web services to be invoked at run-time so as to successfully orchestrate a composite web service. We observe that both the composite and constituent web services often constrain the sequences of invoking their operations and therefore propose to use finite state machine to model the permitted invocation sequences of Web service operations. We assign each state of execution an aggregated reliability to measure the probability that the given state will lead to successful execution in the context where each web …
The Architecture Of Platforms: A Unified View, Carliss Y. Baldwin, C. Jason Woodard
The Architecture Of Platforms: A Unified View, Carliss Y. Baldwin, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Product and system designers have long exploited opportunities to create families of complex artifacts by developing and recombining modular components. An especially common design pattern has come to be associated with the concept of a ‘platform’, which we define as a set of stable components that supports variety and evolvability in a system by constraining the linkages among the other components. Our goal in this chapter is to shed light on the relationships between platforms and the systems in which they are embedded, in order to better understand firms and industries where platforms play an important role. We begin by …
A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian
A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian
Research Collection School Of Computing and Information Systems
Unified modeling language (UML) is the standard modeling language for object-oriented system development. Despite its status as a standard, UML has a fuzzy formal specification and a weak theoretical foundation. Semiotics, the study of signs, provides a good theoretical foundation for UML research because graphical notations (or visual signs) of UML are subjected to the principles of signs. In our research, we use semiotics to study the effectiveness of graphical notations in UML. We hypothesized that the use of iconic signs as UML graphical notations leads to representation that is more accurately interpreted and that arouses fewer connotations than the …
Integrated Resource Allocation And Scheduling In Bidirectional Flow Shop With Multi-Machine And Cos Constraints, Hoong Chuin Lau, Zhengyi Zhao, Shuzhi Sam Ge
Integrated Resource Allocation And Scheduling In Bidirectional Flow Shop With Multi-Machine And Cos Constraints, Hoong Chuin Lau, Zhengyi Zhao, Shuzhi Sam Ge
Research Collection School Of Computing and Information Systems
An integer programming (IP) model is proposed for integrated resource allocation and operation scheduling for a multiple job-agents system. Each agent handles a specific job-list in a bidirectional flowshop. For the individual agent scheduling problem, a formulation is proposed in continuous time domain and compared with an IP formulation in discrete time domain. Of particular interest is the formulation of the machine utilization function-- both in continuous time and discrete time. Fast heuristic methods are proposed with the relaxation of the machine capacity. For the integrated resource allocation and scheduling problem, a linear programming relaxation approach is applied to solve …
Multiuser Private Queries Over Encrypted Databases, Yanjiang Yang, Feng Bao, Xuhua Ding, Robert H. Deng
Multiuser Private Queries Over Encrypted Databases, Yanjiang Yang, Feng Bao, Xuhua Ding, Robert H. Deng
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 multiuser setting. Our results include a set of security notions for multiuser searchable encryption as well as a construction which is provably secure under the newly introduced security notions. We also discuss how …
The Price Of Stability In Selfish Scheduling Games, Lucas Agussurja, Hoong Chuin Lau
The Price Of Stability In Selfish Scheduling Games, Lucas Agussurja, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Game theory has gained popularity as an approach to analysing and understanding distributed systems with self-interested agents. Central to game theory is the concept of Nash equilibrium as a stable state (solution) of the system, which comes with a price − the loss in efficiency. The quantification of the efficiency loss is one of the main research concerns. In this paper, we study the quality and computational characteristics of the best Nash equilibrium in two selfish scheduling models: the congestion model and the sequencing model. In particular, we present the following results: (1) In the congestion model: first, the best …
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Ontology-Based Business Process Customization For Composite Web Services, Qianhui (Althea) Liang, Xindong Wu, E. K. Park, T. Khoshgoftaar, C. Chi
Research Collection School Of Computing and Information Systems
A key goal of the Semantic Web is to shift social interaction patterns from a producer-centric paradigm to a consumer-centric one. Treating customers as the most valuable assets and making the business models work better for them are at the core of building successful consumer-centric business models. It follows that customizing business processes constitutes a major concern in the realm of a knowledge-pull-based human semantic Web. This paper conceptualizes the customization of service-based business processes leveraging the existing knowledge of Web services and business processes. We represent this conceptualization as a new Extensible Markup Language (XML) markup language Web Ontology …
Web Social Mining, Hady W. Lauw, Ee Peng Lim
Web Social Mining, Hady W. Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
No abstract provided.
Offering Rss Feeds: Does It Help To Gain Competitive Advantage?, Dan Ma
Offering Rss Feeds: Does It Help To Gain Competitive Advantage?, Dan Ma
Research Collection School Of Computing and Information Systems
Nowadays, many Websites have adopted the really simple syndication (RSS) technology to deliver online content to visitors. In this paper, I build an analytical model to examine how the offering of RSS feeds impact the number of visitors, total traffic load, and profit of Websites in a competitive setting. I show that although RSS can always attract more visitors, it may reduce the Website's profit. Interestingly, in a competitive market there are cases that the RSS feeds hurt the offering Website but benefit the competing Website instead. The conditions under which these will happen are derived. I also study the …
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Research Collection School Of Computing and Information Systems
Community Question Answering (QA) portals contain questions and answers contributed by hundreds of millions of users. These databases of questions and answers are of great value if they can be used directly to answer questions from any user. In this research, we address this collaborative QA task by drawing knowledge from the crowds in community QA portals such as Yahoo! Answers. Despite their popularity, it is well known that answers in community QA portals have unequal quality. We therefore propose a quality-aware framework to design methods that select answers from a community QA portal considering answer quality in addition to …
Distributed Utility-Based Rate Adaptation Protocols For Prioritized, Quasi-Elastic Flows, Sharanya Eswaran, Matthew P. Johnson, Archan Misra, Thomas La Porta
Distributed Utility-Based Rate Adaptation Protocols For Prioritized, Quasi-Elastic Flows, Sharanya Eswaran, Matthew P. Johnson, Archan Misra, Thomas La Porta
Research Collection School Of Computing and Information Systems
This paper considers rate adaptation for streaming multimedia data in a wireless sensor network (WSN) consisting of multiple missions, where each mission subscribes to data streams from multiple sensors, and each sensor's data is utilized by multiple heterogenous missions. We specifically consider the application of the distributed network utility maximization (NUM) framework to a previously unconsidered scenario where the different missions have different priorities, as well as minimum utility demands. When all the utility demands are feasible, we first show that the addition of a penalty for failing to reach the minimum utility demand to the base NUM protocol leads …
Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang
Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
In the outsourced database model, a data owner publishes her database through a third-party server; i.e., the server hosts the data and answers user queries on behalf of the owner. Since the server may not be trusted, or may be compromised, users need a means to verify that answers received are both authentic and complete, i.e., that the returned data have not been tampered with, and that no qualifying results have been omitted. We propose a result verification approach for one-dimensional queries, called Partially Materialized Digest scheme (PMD), that applies to both static and dynamic databases. PMD uses separate indexes …
Text Mining In Radiology Reports, Tianxia Gong, Chew Lim Tan, Tze-Yun Leong, Cheng Kiang Lee, Boon Chuan Pang, C. C. Tchoyoson Lim, Qi Tian, Suisheng Tang, Zhuo Zhang
Text Mining In Radiology Reports, Tianxia Gong, Chew Lim Tan, Tze-Yun Leong, Cheng Kiang Lee, Boon Chuan Pang, C. C. Tchoyoson Lim, Qi Tian, Suisheng Tang, Zhuo Zhang
Research Collection School Of Computing and Information Systems
Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologist's observations on the patient's medical conditions in the associated medical images. However as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. In this paper we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: a medical finding extractor a report and image retriever and a text-assisted image feature extractor In evaluation, the …
Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng
Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng
Research Collection School Of Computing and Information Systems
With the rapid proliferation of client-to-client applications, PAKE (password authenticated key exchange) protocols in the client-to-client setting become increasingly important. In this paper, we propose an efficient client-to client PAKE protocol, which has much better performance than existing generic constructions. We also show that the proposed protocol is secure under a formal security model.
Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
As an emerging phenomenon, virtual world education is rarely researched in MIS literature. With stiff competition among institutions using virtual worlds for education, a legitimate research question is: What factors influence students’ intention to adopt 3-D virtual world environment for their education needs? Drawing on existing technology acceptance models and studies in other IS contexts, we developed a model to predict students’ acceptance of a 3-D virtual world education environment and plan to empirically test the model using survey data collected from college students. From the academic research perspective, studies on the use of the new technology for education will …
Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
A major problem for firms making information technology investment decisions is predicting and understanding the effects of future technological developments on the value of present technologies. Failure to adequately address this problem can result in wasted organization resources in acquiring, developing, managing, and training employees in the use of technologies that are short-lived and fail to produce adequate return on investment. The sheer number of available technologies and the complex set of relationships among them make IT landscape analysis extremely challenging. Most IT-consuming firms rely on third parties and suppliers for strategic recommendations on IT investments, which can lead to …
Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formulation for robust regularized kernel regression under the theoretical framework of regularization networks and then tackle the optimization problem directly in the primal. We show that the primal and dual approaches are equivalent to achieving similar regression performance, but the primal formulation is more efficient and easier to be implemented than the dual one. Different from …
Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …
Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan
Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant development efforts. To ease the knowledge acquisition bottleneck, this paper presents a class of cognitive agents based on self-organizing neural model known as TD-FALCON that integrates rules and learning for supporting context-aware decision making. Besides the ability to incorporate a priori knowledge in the form of symbolic propositional rules, TD-FALCON performs reinforcement learning (RL), enabling knowledge refinement and expansion through the interaction with its environment. The efficacy of the developed Context-Aware Decision Support (CaDS) system is …
Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall short because they do not exploit variable interactions and cannot account for compensations during inferences. This paper proposes the Explaining BN Inferences (EBI) procedure for explaining how variables interact to reach conclusions. EBI explains the value of a target node in terms of the influential nodes in the target's Markov blanket under specific contexts, where the Markov nodes include the target's parents, children, and the children's other parents. Working back from the target node, EBI shows the …
Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time …
Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra
Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra
Research Collection School Of Computing and Information Systems
Satisfying the varied privacy preferences of individuals, while exposing context data to authorized applications and individuals, remains a major challenge for context-aware computing. This paper describes our experiences in building a middleware component, the context privacy engine (CPE), that enforces a role-based, context-dependent privacy model for enterprise domains. While fundamentally an ACL-based access control scheme, CPE extends the traditional ACL mechanism with usage control and context constraints. This paper focuses on discussing issues related to managing and evaluating context-dependent privacy policies. Extensive experimental studies with a production-grade implementation and real-life context sources demonstrate that the CPE can support a large …
A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu
A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu
Research Collection School Of Computing and Information Systems
Extreme learning machine (ELM) represents one of the recent successful approaches in machine learning, particularly for performing pattern classification. One key strength of ELM is the significantly low computational time required for training new classifiers since the weights of the hidden and output nodes are randomly chosen and analytically determined, respectively. In this paper, we address the architectural design of the ELM classifier network, since too few/many hidden nodes employed would lead to underfitting/overfitting issues in pattern classification. In particular, we describe the proposed pruned-ELM (P-ELM) algorithm as a systematic and automated approach for designing ELM classifier network. P-ELM uses …
On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang
On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang
Research Collection School Of Computing and Information Systems
In this paper, we focus on the visualization of heterogeneous semantic networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social …