Digital Commons Network^™

Generating Templates Of Entity Summaries With An Entity-Aspect Model And Pattern Mining, Peng Li, Jing Jiang, Yinglin Wang

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel approach to automatic generation of summary templates from given collections of summary articles. This kind of summary templates can be useful in various applications. We first develop an entity-aspect LDA model to simultaneously cluster both sentences and words into aspects. We then apply frequent subtree pattern mining on the dependency parse trees of the clustered and labeled sentences to discover sentence patterns that well represent the aspects. Key features of our method include automatic grouping of semantically related sentence patterns and automatic identification of template slots that need to be filled in. We …

Non-Parametric Kernel Ranking Approach For Social Image Retrieval, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Social image retrieval has become an emerging research challenge in web rich media search. In this paper, we address the research problem of text-based social image retrieval, which aims to identify and return a set of relevant social images that are related to a text-based query from a corpus of social images. Regular approaches for social image retrieval simply adopt typical text-based image retrieval techniques to search for the relevant social images based on the associated tags, which may suffer from noisy tags. In this paper, we present a novel framework for social image re-ranking based on a non-parametric kernel …

Tan Ah Choon: The Singapore ‘King Of Spirit Mediums’ (1928-2010), Margaret Chan, Victor Yue

Research Collection School of Social Sciences

On 27 January 2010 Tan Ah CHOON died at the age of 82. Born in the year of the dragon (1928), Tan was the most respected spirit-medium among his peers. He became a tangki (童乩 tongji ‘child diviner’ or Chinese spirit-medium) just before the 1950s, and by the 1960s was regarded as the wisest, most powerful spirit-medium in the Singapore tangki community so that he was nicknamed “Tangki Ong” (童乩王), the “Tangki King”.Mr Tan was “caught” by deities to become a spirit medium when he was aged about 21 years. This was just after the Second World War, but Tan’s …

Learning To Rank Only Using Training Data From Related Domain, Wei Gao, Peng Cai, Kam-Fai Wong, Aoying Zhou

Research Collection School Of Computing and Information Systems

Like traditional supervised and semi-supervised algorithms, learning to rank for information retrieval requires document annotations provided by domain experts. It is costly to annotate training data for different search domains and tasks. We propose to exploit training data annotated for a related domain to learn to rank retrieved documents in the target domain, in which no labeled data is available. We present a simple yet effective approach based on instance-weighting scheme. Our method first estimates the importance of each related-domain document relative to the target domain. Then heuristics are studied to transform the importance of individual documents to the pairwise …

Auditing The Defense Against Cross Site Scripting In Web Applications, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Majority attacks to web applications today are mainly carried out through input manipulation in order to cause unintended actions of these applications. These attacks exploit the weaknesses of web applications in preventing the manipulation of inputs. Among these attacks, cross site scripting attack -- malicious input is submitted to perform unintended actions on a HTML response page -- is a common type of attacks. This paper proposes an approach for thorough auditing of code to defend against cross site scripting attack. Based on the possible methods of implementing defenses against cross site scripting attack, the approach extracts all such defenses …

Extracting Common Emotions From Blogs Based On Fine-Grained Sentiment Clustering, Shi Feng, Daling Wang, Ge Yu, Wei Gao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Recently, blogs have emerged as the major platform for people to express their feelings and sentiments in the age of Web 2.0. The common emotions, which reflect people’s collective and overall sentiments, are becoming the major concern for governments, business companies and individual users. Different from previous literatures on sentiment classification and summarization, the major issue of common emotion extraction is to find out people’s collective sentiments and their corresponding distributions on the Web. Most existing blog clustering methods take into account keywords, stories or timelines but neglect the embedded sentiments, which are considered very important features of blogs. In …

Evaluation Of Protein Backbone Alphabets: Using Predicted Local Structure For Fold Recognition, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Optimally combining available information is one of the key challenges in knowledge-driven prediction techniques. In this study, we evaluate six Phi and Psi-based backbone alphabets. We show that the addition of predicted backbone conformations to SVM classifiers can improve fold recognition. Our experimental results show that the inclusion of predicted backbone conformations in our feature representation leads to higher overall accuracy compared to when using amino acid residues alone.

Analytics-Modulated Coding Of Surveillance Video, Lai-Tee Cheok, Nikhil Gagvani

Research Collection School Of Computing and Information Systems

Video surveillance systems increasingly use H.264 coding to achieve 24x7 recording and streaming. However, with the proliferation of security cameras, and the need to store several months of video, bandwidth and storage costs can be significant. We propose a new compression technique to significantly improve the coding efficiency of H.264 for surveillance video. Video content is analyzed and video semantics are extracted using video analytics algorithms such as segmentation, classification and tracking. In contrast to existing approaches, our Analytics-Modulated Compression (AMC) scheme does not require coding of object shape information and produces bitstreams that are standards-compliant and not limited to …

Exploiting Metaheuristics To Strategize On Performance-Based Logistics Contracts For Mro Services, Arnd Schirrmann, Elaine Wong, Zhichao Zheng

Research Collection Lee Kong Chian School Of Business

An inherent challenge of using Performance-Based Logistics (PBL) contracts for aircraftmaintenance, repair and overhaul (MRO) services is pricing. As with traditional bricks andmortar services, under-priced contracts cannot cover costs, while overpriced contracts loseout to competition. Furthermore MRO services have an additional element of uncertainty.Performance uncertainties arise due to the inability to accurately forecast demand of spareparts, while cost uncertainties are a result of globally distributed operations subjected tofluctuating economic conditions. Previous work to solve this contracting problem adoptedthe principal-agent model, obtaining an optimal solution from the perspective of both riskaverseparties (i.e., a price-sensitive customer and a profit-driven service provider). Thiswork …

A Self-Organizing Approach To Episodic Memory Modeling, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents a neural model that learns episodic traces in response to a continual stream of sensory input and feedback received from the environment. The proposed model, based on fusion Adaptive Resonance Theory (fusion ART) network, extracts key events and encodes spatiotemporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs parallel search of stored episodic traces continuously. Comparing with prior systems, the proposed episodic memory model presents a robust approach to encoding key events and episodes and recalling them using partial and erroneous cues. We present experimental studies, …

Coherent Bag-Of Audio Words Model For Efficient Large-Scale Video Copy Detection, Yang Liu, Wan-Lei Zhao, Chong-Wah Ngo, Chang-Sheng Xu, Han-Qing Lu

Research Collection School Of Computing and Information Systems

Current content-based video copy detection approaches mostly concentrate on the visual cues and neglect the audio information. In this paper, we attempt to tackle the video copy detection task resorting to audio information, which is equivalently important as well as visual information in multimedia processing. Firstly, inspired by bag-of visual words model, a bag-of audio words (BoA) representation is proposed to characterize each audio frame. Different from naive singlebased modeling audio retrieval approaches, BoA is a highlevel model due to its perceptual and semantical property. Within the BoA model, a coherency vocabulary indexing structure is adopted to achieve more efficient …

Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current so stator current based fault detection techniques become less reliable. This paper presents a hybrid algorithm, which combines time and frequency domain analysis, for broken rotor bar and bearing fault detection. Cluster information obtained by using Independent Component Analysis (ICA) …

Self-Organizing Agents For Reinforcement Learning In Virtual Worlds, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

We present a self-organizing neural model for creating intelligent learning agents in virtual worlds. As agents in a virtual world roam, interact and socialize with users and other agents as in real world without explicit goals and teachers, learning in virtual world presents many challenges not found in typical machine learning benchmarks. In this paper, we highlight the unique issues and challenges of building learning agents in virtual world using reinforcement learning. Specifically, a self-organizing neural model, named TD-FALCON (Temporal Difference - Fusion Architecture for Learning and Cognition), is deployed, which enables an autonomous agent to adapt and function in …

Towards Probabilistic Memetic Algorithm: An Initial Study On Capacitated Arc Routing Problem, Liang Feng, Yew-Soon Ong, Quang Huy Nguyen, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Capacitated arc routing problem (CARP) has attracted much attention due to its generality to many real world problems. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving CARP ranging from small to medium size. In this paper we propose a formal probabilistic memetic algorithm for CARP that is equipped with an adaptation mechanism to control the degree of global exploration against local exploitation while the search progresses. Experimental study on benchmark instances of CARP showed that the proposed probabilistic scheme led to improved search performances when introduced into a recently proposed state-of-the-art …

Faceted Topic Retrieval Of News Video Using Joint Topic Modeling Of Visual Features And Speech Transcripts, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia

Research Collection School Of Computing and Information Systems

Because of the inherent ambiguity in user queries, an important task of modern retrieval systems is faceted topic retrieval (FTR), which relates to the goal of returning diverse or novel information elucidating the wide range of topics or facets of the query need. We introduce a generative model for hypothesizing facets in the (news) video domain by combining the complementary information in the visual keyframes and the speech transcripts. We evaluate the efficacy of our multimodal model on the standard TRECVID-2005 video corpus annotated with facets. We find that: (1) the joint modeling of the visual and text (speech transcripts) …

Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current so stator current based fault detection techniques become less reliable. This paper presents a hybrid algorithm, which combines time and frequency domain analysis, for broken rotor bar and bearing fault detection. Cluster information obtained by using Independent Component Analysis (ICA) …

Effective Heuristic Methods For Finding Non-Optimal Solutions Of Interest In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper introduces the SoI problem, that of finding nonoptimal solutions of interest for constrained optimization models. SoI problems subsume finding FoIs (feasible solutions of interest), and IoIs (infeasible solutions of interest). In all cases, the interest addressed is post-solution analysis in one form or another. Post-solution analysis of a constrained optimization model occurs after the model has been solved and a good or optimal solution for it has been found. At this point, sensitivity analysis and other questions of import for decision making (discussed in the paper) come into play and for this purpose the SoIs can be of …

A Heuristic Algorithm For Trust-Oriented Service Provider Selection In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In a service-oriented online social network consisting of service providers and consumers, a service consumer can search trustworthy service providers via the social network. This requires the evaluation of the trustworthiness of a service provider along a certain social trust path from the service consumer to the service provider. However, there are usually many social trust paths between participants in social networks. Thus, a challenging problem is which social trust path is the optimal one that can yield the most trustworthy evaluation result. In this paper, we first present a novel complex social network structure and a new concept, Quality …

Oral History Interview With Roberto Mariano: Conceptualising Smu, Roberto S. Mariano

Oral History Collection

The interview covered: first involvement with SMU, founding dean for School of Economics, vision, curriculum, faculty development, faculty recruitment, research, pioneer students, postgraduate programmes, challenges.

Biography:

Dean, SMU School of Economics, 2007–2010
Founding Dean, School of Economics and Social Science, SMU, 2002–2007

Professor Roberto S Mariano was appointed as dean of the new School of Economics and Social Sciences in 2002. He oversaw the intake of the inaugural classes of the economics and social science bachelors programmes in 2002 and 2004 respectively, and also served as the vice provost of research and deputy director of the Wharton-SMU Research Centre. His …

Pro-Creativity Leadership: An Exploratory Study On The Mediating Role Of Intrinsic Motivation, Gilbert Tan, Wei Nurn Chong

Research Collection Lee Kong Chian School Of Business

Many scholars believe in the critical role leaders play in fostering creativity at the workplace (e.g. Amabile, 1998; Amabile, Conti, Coon, Lazenby, & Herron, 1996; Jung, 2000-2001; Mumford & Gustafson, 1988). Leaders have been described to occupy a boundary role position in organizations (Katz & Kahn, 1978) where they are tasked with influencing subordinate behavior in order to attain organizational goals (Fleishman, 1973; Mumford, 1986). As such, they are in the position to influence subordinate behavior considerably, including subordinates’ creative behavior. Yet to date, not much research has been done on the effect of leadership on employee creativity (Jung, 2000-2001; …

Competition, Competitiveness And 'Created' Competitive Advantages: Re-Positioning The Singapore 'Advantage' In China, India, Vietnam And Indonesia, Caroline Yeoh

Research Collection Lee Kong Chian School Of Business

No abstract provided.

Otl: A Framework Of Online Transfer Learning, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning task on a target domain. We do not assume the target data follows the same class or generative distribution as the source data, and our key motivation is to improve a supervised online learning task in a target domain by exploiting the knowledge that had been learned from large amount of training data in source domains. OTL is in general challenging since data in both domains not only can be different in …

An Analysis Of Extreme Price Shocks And Illiquidity Among Systematic Trend Followers, Bernard Lee, Shih-Fen Cheng, Annie Koh

Research Collection Lee Kong Chian School Of Business

We construct an agent-based model to study the interplay between extreme price shocks and illiquidity in the presence of systematic traders known as trend followers. The agent-based approach is particularly attractive in modeling commodity markets because the approach allows for the explicit modeling of production, capacities, and storage constraints. Our study begins by using the price stream from a market simulation involving human participants and studies the behavior of various trend-following strategies, assuming initially that their participation will not impact the market. We notice an incremental deterioration in strategy performance as and when strategies deviate further and further from the …

Tort Law, Kumaralingam Amirthalingam, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

The three cases on conversion relate to the following issues: the distinction between the tort of conversion and the choice of remedy for purposes of determining the appropriate limitation period, the underlying rationale for conversion that is based essentially on possession of a chattel and finally, the question of whether a temporary certificate of entitlement for the purchase of a car in Singapore may be converted.

Do Wikipedians Follow Domain Experts? A Domain-Specific Study On Wikipedia Contribution, Yi Zhang, Aixin Sun, Anwitaman Datta, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Wikipedia is one of the most successful online knowledge bases, attracting millions of visits daily. Not surprisingly, its huge success has in turn led to immense research interest for a better understanding of the collaborative knowledge building process. In this paper, we performed a (terrorism) domain-specific case study, comparing and contrasting the knowledge evolution in Wikipedia with a knowledge base created by domain experts. Specifically, we used the Terrorism Knowledge Base (TKB) developed by experts at MIPT. We identified 409 Wikipedia articles matching TKB records, and went ahead to study them from three aspects: creation, revision, and link evolution. We …

Revisiting Unpredictability-Based Rfid Privacy Models, Junzuo Lai, Robert Huijie Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

Recently, there have been several attempts in establishing formal RFID privacy models in the literature. These models mainly fall into two categories: one based on the notion of indistinguishability of two RFID tags, denoted as ind-privacy, and the other based on the unpredictability of the output of an RFID protocol, denoted as unp-privacy. Very recently, at CCS’09, Ma et al. proposed a modified unp-privacy model, referred to as unp ^′-privacy. In this paper, we first revisit the existing RFID privacy models and point out their limitations. We then propose a new RFID privacy model, denoted as …

Z-Sky: An Efficient Skyline Query Processing Framework Based On Z-Order, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Huajing Li, Yuan Tian

Research Collection School Of Computing and Information Systems

Given a set of data points in a multidimensional space, a skyline query retrieves those data points that are not dominated by any other point in the same dataset. Observing that the properties of Z-order space filling curves (or Z-order curves) perfectly match with the dominance relationships among data points in a geometrical data space, we, in this paper, develop and present a novel and efficient processing framework to evaluate skyline queries and their variants, and to support skyline result updates based on Z-order curves. This framework consists of ZBtree, i.e., an index structure to organize a source dataset and …

Anytime Planning For Decentralized Pomdps Using Expectation Maximization, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDPs provide an expressive framework for multi-agent sequential decision making. While finite-horizon DECPOMDPs have enjoyed signifcant success, progress remains slow for the infinite-horizon case mainly due to the inherent complexity of optimizing stochastic controllers representing agent policies. We present a promising new class of algorithms for the infinite-horizon case, which recasts the optimization problem as inference in a mixture of DBNs. An attractive feature of this approach is the straightforward adoption of existing inference techniques in DBNs for solving DEC-POMDPs and supporting richer representations such as factored or continuous states and actions. We also derive the Expectation Maximization (EM) …

Pricing Options In An Extended Black Scholes Economy With Illiquidity: Theory And Empirical Evidence, Umut Cetin, Robert Jarrow, Mitchell Protter, Mitchell Warachka

Research Collection Lee Kong Chian School Of Business

This article studies the pricing of options in an extended Black Scholes economy in which the underlying asset is not perfectly liquid. The resulting liquidity risk is modeled as a stochastic supply curve, with the transaction price being a function of the trade size. Consistent with the market microstructure literature, the supply curve is upward sloping with purchases executed at higher prices and sales at lower prices. Optimal discrete time hedging strategies are then derived. Empirical evidence reveals a significant liquidity cost intrinsic to every option. [PUBLICATION ABSTRACT]

The Interaction Of Roles, Resources, And Organizational Structures In Creative Work, Feichin, Ted Tschang

Research Collection Lee Kong Chian School Of Business

Creativity is known to be located at both the individual and group levels. We look at the case of videogame development, as an instance of project level creativity. We focus in particular on the design of the artifact. By examining the loci of creativity at the individual and group levels, we shed light on the roles and tasks of the designer, and on the organizational group structure known as the design cabal. In comparing the two extremes, we discover that the lack of organizational resources (namely, well known designers) leads in certain projects to the adoption of cabals or cabal-like …