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Singapore Management University

2008

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Articles 1 - 30 of 161

Full-Text Articles in Physical Sciences and Mathematics

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 Dec 2008

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 …

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Text Cube: Computing Ir Measures For Multidimensional Text Database Analysis, Cindy Xinde Lin, Bolin Ding, Jiawei Han, Feida Zhu, Bo Zhao Dec 2008

Text Cube: Computing Ir Measures For Multidimensional Text Database Analysis, Cindy Xinde Lin, Bolin Ding, Jiawei Han, Feida Zhu, Bo Zhao

Research Collection School Of Computing and Information Systems

Since Jim Gray introduced the concept of ”data cube” in 1997, data cube, associated with online analytical processing (OLAP), has become a driving engine in data warehouse industry. Because the boom of Internet has given rise to an ever increasing amount of text data associated with other multidimensional information, it is natural to propose a data cube model that integrates the power of traditional OLAP and IR techniques for text. In this paper, we propose a Text-Cube model on multidimensional text database and study effective OLAP over such data. Two kinds of hierarchies are distinguishable inside: dimensional hierarchy and term …

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Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau Dec 2008

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 …

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Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan Dec 2008

Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents iFALCON, a model of BDI (beliefdesire-intention) agents that is fully realized as a selforganizing neural network architecture. Based on multichannel network model called fusion ART, iFALCON is developed to bridge the gap between a self-organizing neural network that autonomously adapts its knowledge and the BDI agent model that follows explicit descriptions. Novel techniques called gradient encoding are introduced for representing sequences and hierarchical structures to realize plans and the intention structure. This paper shows that a simplified plan representation can be encoded as weighted connections in the neural network through a process of supervised learning. A case …

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Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan Dec 2008

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 …

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Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo Dec 2008

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 …

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Chosen-Ciphertext Secure Proxy Re-Encryption Without Pairing, Robert H. Deng, Jian Weng, Shengli Liu, Kefei Chen Dec 2008

Chosen-Ciphertext Secure Proxy Re-Encryption Without Pairing, Robert H. Deng, Jian Weng, Shengli Liu, Kefei Chen

Research Collection School Of Computing and Information Systems

In a proxy re-encryption system, a semi-trusted proxy can convert a ciphertext originally intended for Alice into a ciphertext intended for Bob, without learning the underlying plaintext. Proxy re-encryption has found many practical applications, such as encrypted email forwarding, secure distributed file systems, and outsourced filtering of encrypted spam. In ACM CCS'07, Canetti and Hohenberger presented a proxy re-encryption scheme with chosen-ciphertext security, and left an important open problem to construct a chosen-ciphertext secure proxy re-encryption scheme without pairings. In this paper, we solve this open problem by proposing a new proxy re-encryption scheme without resort to bilinear pairings. Based …

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Mobitop: Accessing Hierarchically Organized Georeferenced Multimedia Annotations, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Quang Minh Nguyen, Ee Peng Lim Dec 2008

Mobitop: Accessing Hierarchically Organized Georeferenced Multimedia Annotations, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Quang Minh Nguyen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a map-based interface for accessing hierarchically organized georeferenced annotations. Each annotation contains multimedia content associated with a location, and users are able to annotate existing annotations, in effect creating a hierarchy.

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Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng Dec 2008

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.

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Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra Dec 2008

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 …

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On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang Dec 2008

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 …

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Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman Dec 2008

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 …

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Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Dec 2008

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 …

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Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Dec 2008

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 …

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Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu Dec 2008

Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu

Research Collection School Of Computing and Information Systems

This paper investigates the structure and dynamics of the Web 2.0 software ecosystem by analyzing empirical data on web service APIs and mashups. Using network analysis tools to visualize the growth of the ecosystem from December 2005 to 2007, we find that the APIs are organized into three tiers, and that mashups are often formed by combining APIs across tiers. Plotting the cumulative distribution of mashups to APIs reveals a power-law relationship, although the tail is short compared to previously reported distributions of book and movie sales. While this finding highlights the dominant role played by the most popular APIs …

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Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan Dec 2008

Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (TD) methods for real-time reinforcement learning. In this paper, we present two strategies, i.e. policy sharing and neighboring-agent mechanism, to further improve the learning efficiency of TD-FALCON in complex multi-agent domains. Through experiments on a traffic control problem domain and the herding task, we demonstrate that those strategies enable TD-FALCON to remain functional and adaptable in complex multi-agent domains

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A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu Dec 2008

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 …

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Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang Nov 2008

Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

Evaluation is prevalent in real life. With the advent of Web 2.0, online evaluation has become an important feature in many applications that involve information (e.g., video, photo, and audio) sharing and social networking (e.g., blogging). In these evaluation settings, a set of reviewers assign scores to a set of objects. As part of the evaluation analysis, we want to obtain fair reviews for all the given objects. However, the reality is that reviewers may deviate in their scores assigned to the same object, due to the potential bias of reviewers or controversy of objects. The statistical approach of averaging …

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Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan Nov 2008

Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

This paper presents our approaches and results of the four TRECVID 2008 tasks we participated in: high-level feature extraction, automatic video search, video copy detection, and rushes summarization

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A New Framework For The Design And Analysis Of Identity-Based Identification Schemes, Guomin Yang, Jing Chen, Duncan S. Wong, Xiaotie Deng, Dongsheng Wang Nov 2008

A New Framework For The Design And Analysis Of Identity-Based Identification Schemes, Guomin Yang, Jing Chen, Duncan S. Wong, Xiaotie Deng, Dongsheng Wang

Research Collection School Of Computing and Information Systems

Constructing an identification scheme is one of the fundamental problems in cryptography, and is very useful in practice. An identity-based identification (IBI) scheme allows a prover to identify himself to a public verifier who knows only the claimed identity of the prover and some public information. In this paper, we propose a new framework for both the design and analysis of IBI schemes. Our approach works in an engineering way. We first identify an IBI scheme as the composition of two building blocks, and then show that, with different security properties of these building blocks, the corresponding IBI schemes can …

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Two-Factor Mutual Authentication Based On Smart Cards And Passwords, Guomin Yang, Duncan S. Wong, Huaxiong Wang, Xiaotie Deng Nov 2008

Two-Factor Mutual Authentication Based On Smart Cards And Passwords, Guomin Yang, Duncan S. Wong, Huaxiong Wang, Xiaotie Deng

Research Collection School Of Computing and Information Systems

One of the most commonly used two-factor user authentication mechanisms nowadays is based on smart-card and password. A scheme of this type is called a smart-card-based password authentication scheme. The core feature of such a scheme is to enforce two-factor authentication in the sense that the client must have the smart-card and know the password in order to gain access to the server. In this paper, we scrutinize the security requirements of this kind of schemes, and propose a new scheme and a generic construction framework for smart-card-based password authentication. We show that a secure password based key exchange protocol …

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A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow Nov 2008

A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow

Research Collection School Of Computing and Information Systems

The architecture of the human cortex is uniform and hierarchical in nature. In this paper, we build upon works on hierarchical classification systems that model the cortex to develop a neural network representation for a hierarchical spatio-temporal memory (HST-M) system. The system implements spatial and temporal processing using neural network architectures. We have tested the algorithms developed against both the MLP and the Hierarchical Temporal Memory algorithms. Our results show definite improvement over MLP and are comparable to the performance of HTM.

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Model-Driven Remote Attestation: Attesting Remote System From Behavioral Aspect, Liang Gu, Xuhua Ding, Robert H. Deng, Yanzhen Zou, Bing Xie, Weizhong Shao, Hong Mei Nov 2008

Model-Driven Remote Attestation: Attesting Remote System From Behavioral Aspect, Liang Gu, Xuhua Ding, Robert H. Deng, Yanzhen Zou, Bing Xie, Weizhong Shao, Hong Mei

Research Collection School Of Computing and Information Systems

Remote attestation was introduced in TCG specifications to determine whether a remote system is trusted to behave in a particular manner for a specific purpose; however, most of the existing approaches attest only the integrity state of a remote system and hence have a long way to go in achieving the above attestation objective. Behavior-based attestation and semantic attestation were recently introduced as solutions to approach the TCG attestation objective. In this paper, we extend behavior-based attestation to a model-driven remote attestation to prove that a remote system is trusted as defined by TCG. Our model-driven remote attestation verifies two …

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Market Liquidity Provision For On-Demand Computing, Zhiling Guo Nov 2008

Market Liquidity Provision For On-Demand Computing, Zhiling Guo

Research Collection School Of Computing and Information Systems

This paper focuses on a market intermediary’s role of liquidity provision to support on-demand computing in a dynamic market trading environment. We outline a framework in which a number of distributed agents sell and buy assets based on their changing utilities over time and a service provider acts as a market maker performing market intervention. We present benchmark models based on socially optimal liquidity provision and a brokerage framework. We then examine the benefits and the dealer’s incentives to provide market liquidity.

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Profile-Guided Program Simplification For Effective Testing And Analysis, Lingxiao Jiang, Zhendong Su Nov 2008

Profile-Guided Program Simplification For Effective Testing And Analysis, Lingxiao Jiang, Zhendong Su

Research Collection School Of Computing and Information Systems

Many testing and analysis techniques have been developed for inhouse use. Although they are effective at discovering defects before a program is deployed, these techniques are often limited due to the complexity of real-world code and thus miss program faults. It will be the users of the program who eventually experience failures caused by the undetected faults. To take advantage of the large number of program runs carried by the users, recent work has proposed techniques to collect execution profiles from the users for developers to perform post-deployment failure analysis. However, in order to protect users' privacy and to reduce …

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Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li Nov 2008

Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li

Research Collection School Of Computing and Information Systems

Event detection is one of the most fundamental components for various kinds of domain applications of video information system. In recent years, it has gained a considerable interest of practitioners and academics from different areas. While detecting video event has been the subject of extensive research efforts recently, much less existing approach has considered multimodal information and related efficiency issues. In this paper, we use a subspace selection technique to achieve fast and accurate video event detection using a subspace selection technique. The approach is capable of discriminating different classes and preserving the intramodal geometry of samples within an identical …

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Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard Oct 2008

Spatio-Temporal Efficiency In A Taxi Dispatch System, Darshan Santani, Rajesh Krishna Balan, C. Jason Woodard

Research Collection School Of Computing and Information Systems

In this paper, we present an empirical analysis of the GPS-enabled taxi dispatch system used by the world’s second largest land transportation company. We first summarize the collective dynamics of the more than 6,000 taxicabs in this fleet. Next, we propose a simple method for evaluating the efficiency of the system over a given period of time and geographic zone. Our method yields valuable insights into system performance—in particular, revealing significant inefficiencies that should command the attention of the fleet operator. For example, despite the state of the art dispatching system employed by the company, we find imbalances in supply …

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Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan Oct 2008

Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

We propose, theorize and implement the Recursive Pattern-based Hybrid Supervised (RPHS) learning algorithm. The algorithm makes use of the concept of pseudo global optimal solutions to evolve a set of neural networks, each of which can solve correctly a subset of patterns. The pattern-based algorithm uses the topology of training and validation data patterns to find a set of pseudo-optima, each learning a subset of patterns. It is therefore well adapted to the pattern set provided. We begin by showing that finding a set of local optimal solutions is theoretically equivalent, and more efficient, to finding a single global optimum …

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Model Checking Csp Revisited: Introducing A Process Analysis Toolkit, Jun Sun, Yang Liu, Jin Song Dong Oct 2008

Model Checking Csp Revisited: Introducing A Process Analysis Toolkit, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

FDR, initially introduced decades ago, is the de facto analyzer for Communicating Sequential Processes (CSP). Model checking techniques have been evolved rapidly since then. This paper describes PAT, i.e., a process analysis toolkit which complements FDR in several aspects. PAT is designed to analyze event-based compositional system models specified using CSP as well as shared variables and asynchronous message passing. It supports automated refinement checking, model checking of LTL extended with events, etc. In this paper, we highlight how partial order reduction is applied to improve refinement checking in PAT. Experiment results show that PAT outperforms FDR in some cases.

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Remote Attestation On Program Execution, Liang Gu, Xuhua Ding, Robert H. Deng, Bing Xie, Hong Mei Oct 2008

Remote Attestation On Program Execution, Liang Gu, Xuhua Ding, Robert H. Deng, Bing Xie, Hong Mei

Research Collection School Of Computing and Information Systems

Remote attestation provides the basis for one platform to establish trusts on another. In this paper, we consider the problem of attesting the correctness of program executions. We propose to measure the target program and all the objects it depends on, with an assumption that the Secure Kernel and the Trusted Platform Module provide a secure execution environment through process separation. The attestation of the target program begins with a program analysis on the source code or the binary code in order to find out the relevant executables and data objects. Whenever such a data object is accessed or a …

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