Digital Commons Network^™

Probabilistic Value Selection For Space Efficient Model, Gunarto Sindoro Njoo, Baihua Zheng, Kuo-Wei Hsu, Wen-Chih Peng

Research Collection School Of Computing and Information Systems

An alternative to current mainstream preprocessing methods is proposed: Value Selection (VS). Unlike the existing methods such as feature selection that removes features and instance selection that eliminates instances, value selection eliminates the values (with respect to each feature) in the dataset with two purposes: reducing the model size and preserving its accuracy. Two probabilistic methods based on information theory's metric are proposed: PVS and P + VS. Extensive experiments on the benchmark datasets with various sizes are elaborated. Those results are compared with the existing preprocessing methods such as feature selection, feature transformation, and instance selection methods. Experiment results …

Graph-To-Tree Learning For Solving Math Word Problems, Jipeng Zhang, Lei Wang, Roy Ka-Wei Lee, Yi Bin, Yan Wang, Jie Shao, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

While the recent tree-based neural models have demonstrated promising results in generating solution expression for the math word problem (MWP), most of these models do not capture the relationships and order information among the quantities well. This results in poor quantity representations and incorrect solution expressions. In this paper, we propose Graph2Tree, a novel deep learning architecture that combines the merits of the graph-based encoder and tree-based decoder to generate better solution expressions. Included in our Graph2Tree framework are two graphs, namely the Quantity Cell Graph and Quantity Comparison Graph, which are designed to address limitations of existing methods by …

Lightweight And Privacy-Aware Fine-Grained Access Control For Iot-Oriented Smart Health, Jianfei Sun, Hu Xiong, Ximeng Liu, Yinghui Zhang, Xuyun Nie, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the booming of Internet of Things (IoT), smart health (s-health) is becoming an emerging and attractive paradigm. It can provide an accurate prediction of various diseases and improve the quality of healthcare. Nevertheless, data security and user privacy concerns still remain issues to be addressed. As a high potential and prospective solution to secure IoT-oriented s-health applications, ciphertext policy attribute-based encryption (CP-ABE) schemes raise challenges, such as heavy overhead and attribute privacy of the end users. To resolve these drawbacks, an optimized vector transformation approach is first proposed to efficiently transform the access policy and user attribute set into …

Spinfer: Inferring Semantic Patches For The Linux Kernel, Lucas Serrano, Van-Anh Nguyen, Ferdian Thung, Lingxiao Jiang, David Lo, Julia Lawall, Gilles Muller

Research Collection School Of Computing and Information Systems

In a large software system such as the Linux kernel, there is a continual need for large-scale changes across many source files, triggered by new needs or refined design decisions. In this paper, we propose to ease such changes by suggesting transformation rules to developers, inferred automatically from a collection of examples. Our approach can help automate large-scale changes as well as help understand existing large-scale changes, by highlighting the various cases that the developer who performed the changes has taken into account. We have implemented our approach as a tool, Spinfer. We evaluate Spinfer on a range of challenging …

Mining And Predicting Micro-Process Patterns Of Issue Resolution For Open Source Software Projects, Yiran Wang, Jian Cao, David Lo

Research Collection School Of Computing and Information Systems

Addressing issue reports is an integral part of open source software (OSS) projects. Although several studies have attempted to discover the factors that affect issue resolution, few pay attention to the underlying micro-process patterns of resolution processes. Discovering these micro-patterns will help us understand the dynamics of issue resolution processes so that we can manage and improve them in better ways. Of the various types of issues, those relating to corrective maintenance account for nearly half hence resolving these issues efficiently is critical for the success of OSS projects. Therefore, we apply process mining techniques to discover the micro-patterns of …

Expertise Style Transfer: A New Task Towards Better Communication Between Experts And Laymen, Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Lu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the goal of alleviating such cognitive biases. Solving this task not only simplifies the professional language, but also improves the accuracy and expertise level of laymen descriptions using simple words. This is a challenging task, unaddressed in previous work, as it requires the models to have expert intelligence in order to modify text with a deep understanding of domain knowledge and structures. We establish the benchmark performance of five state-of-the-art models for style …

Tree-Augmented Cross-Modal Encoding For Complex-Query Video Retrieval, Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The rapid growth of user-generated videos on the Internet has intensified the need for text-based video retrieval systems. Traditional methods mainly favor the concept-based paradigm on retrieval with simple queries, which are usually ineffective for complex queries that carry far more complex semantics. Recently, embedding-based paradigm has emerged as a popular approach. It aims to map the queries and videos into a shared embedding space where semantically-similar texts and videos are much closer to each other. Despite its simplicity, it forgoes the exploitation of the syntactic structure of text queries, making it suboptimal to model the complex queries. To facilitate …

Essays On Multivariate Stochastic Volatility Models, Han Chen

Dissertations and Theses Collection (Open Access)

In this dissertation, I have made several contributions to the literature on the multivariate stochastic volatility model. First, I have considered a new multivariate stochastic volatility (MSV) model based on a recently proposed novel parameterization of the correlation matrix. This modeling design is a generalization of Fisher's z-transformation to the high-dimensional case. It is fully flexible as the validity of the resulting correlation matrix is guaranteed automatically. It allows me to completely separate the driving factors of volatilities and correlations. To conduct an econometric analysis of the proposed model, I develop a new Bayesian method that relies on the Markov …

Chinese Temple Networks In Southeast Asia: A Webgis Digital Humanities Platform For The Collaborative Study Of The Chinese Diaspora In Southeast Asia, Yingwei Yan, Kenneth Dean, Chen-Chieh Feng, Guan Thye Hue, Khee-Heong Koh, Lily Kong, Chang Woei Ong, Arthur Tay, Yi-Chen Wang, Yiran Xue

Research Collection School of Social Sciences

This article introduces a digital platform for collaborative research on the Chinese diaspora in Southeast Asia, focusing on networks of Chinese temples and associations extending from Southeast China to the various port cities of Southeast Asia. The Singapore Historical Geographic Information System (SHGIS) and the Singapore Biographical Database (SBDB) are expandable WebGIS platforms gathering and linking data on cultural and religious networks across Southeast Asia. This inter-connected platform can be expanded to cover not only Singapore but all of Southeast Asia. We have added layers of data that go beyond Chinese Taoist, Buddhist, and popular god temples to also display …

Tort Law, Amirthalingam Kumaralingam, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

This review examines the ten most significant decisions in tort law for 2020. It was an interesting year for the range of significant decisions in tort law handed down by the courts on matters including limitation period, medical negligence, the scope of duty in negligence, breach of confidence, conspiracy, and defamation.

Does Media Exposure Affect Financial Reporting Quality Through Auditors?, Steven F. Cahan, Chen Chen, Rencheng Wang

Research Collection School Of Accountancy

We examine whether the media has an indirect corporate governance effect on financial reporting quality (FRQ) that operates through auditors. This occurs because greater media coverage can magnify an auditor's business risk by exposing the auditor to more potential litigation and reputation damage if an audit failure occurs. We use a path analysis to examine the direct and indirect channels of media corporate governance. We find a positive association between media coverage and FRQ that is mediated by audit fees, and the results are stronger for firms with greater incentives to engage in earnings manipulation. In contrast, we find no …

Learning Music Composers' Styles: To Block Or To Interleave?, Sarah Shi Hui Wong, Amanda Chern Min Low, Sean H. K. Kang, Stephen Wee Hun Lim

Research Collection School of Social Sciences

The ability to recognize and distinguish among varying musical styles is essential to developing aural skills and musicianship. Yet, this task can be difficult for music learners, particularly nonexperts. To address this challenge and guide music education practice, this study drew on cognitive psychological principles to investigate the effect of interleaved presentation of music pieces by various classical music composers on learning to identify these composers’ styles. Participants with 4 or fewer years of musical experience were presented with music pieces from six composers in an interleaved manner (alternating between listening to different composers’ works) and music pieces from another …

Executive Function And Subjective Well-Being In Middle And Late Adulthood, Wei Xing Toh, Hwajin Yang, Andree Hartanto

Research Collection School of Social Sciences

Objectives: A growing body of research has investigated psychosocial predictors of subjective well-being (SWB), a key component of healthy ageing, which comprises life satisfaction and affective well-being. However, few studies have examined how executive function (EF)-a collection of adaptive, goal-directed control processes-could affect SWB in middle and late adulthood. Methods: By analyzing a nationally representative adult cohort ranging from early 30s to early 80s from the Midlife Development in the United States 2 study, we examined two potential mediators (i.e., sense of control versus positive reappraisal) that could underlie the relation between EF and SWB. Further, we assessed how these …

Intuitive Pricing By Independent Store Managers: Challenging Beliefs And Practices, Sabine Benoit, Mario Kienzler, Christian Kowalkowski

Research Collection Lee Kong Chian School Of Business

Independent store managers-who constitute a substantial portion of the retailing sector-often have limited resources with which to practice the formalized, data-driven pricing processes prescribed in the literature. On that basis, this article addresses how independent convenience store managers arrive at prices and whether their practices are effective. To begin with, 33 interviews with independent convenience store managers identified six common beliefs and ten practices underlying managers' intuitive decision making. Based on point-of-sale survey data from 1,504 customers of two convenience store chains at petrol stations, a second study compared market-oriented managerial beliefs with actual customer price perceptions and buying behaviors. …

R&D Project Portfolio Selection With Multiple Stakeholders, Wenqi Lian

Dissertations and Theses Collection (Open Access)

Research and Development (R&D) is time consuming, expensive and risky; yet product life cycles are shortening and competition is fierce. Therefore, R&D often requires the collaboration and input of multiple stakeholders. This dissertation studies how collaborations involving multiple stakeholders can effectively make R&D project portfolio selection decisions to create the optimal social welfare. The two essays in the dissertation build stylized analytical models to examine R&D project portfolio selection in two different settings, academia and industry respectively. The models explicitly acknowledge the different information, goals and operational decisions of the stakeholders. In the first essay, we study a two-stage funding …

Three Essays On Econometrics, Xin Zheng

Dissertations and Theses Collection (Open Access)

The dissertation includes three chapters on econometrics. The first chapter is about treatment effects and its application in randomized control trial. The second chapter is about specification test. The third chapter is about panel data model with fixed effects.

In the first chapter, we study the estimation and inference of the quantile treatment effect under covariate-adaptive randomization. We propose two estimation methods: (1) the simple quantile regression and (2) the inverse propensity score weighted quantile regression. For the two estimators, we derive their asymptotic distributions uniformly over a compact set of quantile indexes, and show that, when the treatment assignment …

Learning And Adaptation Under Uncertainty And Ambiguity, Lei Zheng

Dissertations and Theses Collection (Open Access)

The first essay is about how high and moderate aspiration levels compare in terms of affecting the decision making and reinforcement learning in an uncertain environment. After developing a thought experiment and a computational model, I used lab experiments to test the model’s predictions: a high (moderate) aspiration level reduces (increases) feedback ambiguity about the relative attractiveness of different options, thus increases the exploitation (exploration) tendency of the decision maker. The behavioural difference suggests that high aspirations lead to better performance in stable environments, but worse performance after disruptive shocks. The second essay investigates whether organizations should commit more (or …

Three Essays On International Economics: Global Value Chains Of Singapore And The Cptpp; The Effects Of Oil Price Shocks On Trade, Tran Bao Phuong Nguyen

Dissertations and Theses Collection (Open Access)

This dissertation discusses two questions in international economics. The first two chapters focus on the matter of global value chains. We first explore the participation of Singapore in the global value chains by characterizing the position of Singapore in the global network and identifying Singapore’s key upstream and downstream trade partners. This is done at both the country aggregate and at the sector level. We trace how the country’s position in global value chains has changed in the past two decades: whether it has moved upstream or downstream, how involved it is in global value chains, how its trend compares …

Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Yichong Zhang, Xin Zheng

Research Collection School Of Economics

In this paper, we study the estimation and inference of the quantile treatment effect under covariate‐adaptive randomization. We propose two estimation methods: (1) the simple quantile regression and (2) the inverse propensity score weighted quantile regression. For the two estimators, we derive their asymptotic distributions uniformly over a compact set of quantile indexes, and show that, when the treatment assignment rule does not achieve strong balance, the inverse propensity score weighted estimator has a smaller asymptotic variance than the simple quantile regression estimator. For the inference of method (1), we show that the Wald test using a weighted bootstrap standard …

Revisiting The Automation Tax Debate In Light Of Covid-19 And Resulting Structural Unemployment, Vincent Ooi

Research Collection Yong Pung How School Of Law

As lockdowns ease around the globe and businesses reopen, the threat of jobs being automated by machines and workers being displaced as a result has significantly increased. Businesses must keep the number of workers on site to a minimum to comply with safe distancing measures. Under these constraints while social distancing remains the norm, automation might be the way forward for companies that still want to continue production while minimising human contact. The threat of a workforce being replaced by robots and automation, a threat that has already alarmed the labour movement, is heightened with Covid-19. There will be considerable …

The Promises And Perils Of Insurtech, Lin Lin, Christopher C. H. Chen

Research Collection Yong Pung How School Of Law

The insurance sector, in riding the wave of the FinTech phenomenon, has been rapidly expanding, with a slew of firms having emerged to provide so-called “InsurTech” services. These services incorporate concepts such as blockchain, artificial intelligence, digitalisation and the sharing economy to various aspects of the insurance industry. This profusion of technology brings with it the promise of various benefits including increasing efficiency and lowering costs for not only insurers and intermediaries, but also businesses or consumers as end-users of insurance. However, the development of InsurTech comes with corresponding risks and regulatory concerns not currently accounted for by the traditional …

Compensation For Abused Foreign Domestic Workers: A Problem Of Enforcement, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

In Tay Wee Kiat v Public Prosecutor [2018] 5 SLR 438; [2019] 5 SLR 1033, two offenders who had abused a foreign domestic worker had been ordered to pay her compensation, on pain of a default term of imprisonment. When they failed to pay, the Prosecution applied for the compensation order to be enforced by way of attachment of the offenders’ property or garnishment of debts due to the offenders (“garnishment/attachment orders”). The High Court refused to make garnishment/attachment orders on the grounds that (a) the Prosecution had applied for such orders belatedly; and (b) such orders would lead to …

Video-Grounded Dialogues With Pretrained Generation Language Models, Hung Le, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Pre-trained language models have shown remarkable success in improving various downstream NLP tasks due to their ability to capture dependencies in textual data and generate natural responses. In this paper, we leverage the power of pre-trained language models for improving video-grounded dialogue, which is very challenging and involves complex features of different dynamics: (1) Video features which can extend across both spatial and temporal dimensions; and (2) Dialogue features which involve semantic dependencies over multiple dialogue turns. We propose a framework by extending GPT-2 models to tackle these challenges by formulating video-grounded dialogue tasks as a sequence-to-sequence task, combining both …

The Prediction Of Delay Time At Intersection And Route Planning For Autonomous Vehicles, Genwang Gou, Yongxin Zhao, Jiawei Liang, Ling Shi

Research Collection School Of Computing and Information Systems

Intelligent Intersections (roundabout and crossroads) management is considered as one of the challenges to significantly improve urban traffic efficiency. Recent researches in artificial intelligence suggest that autonomous vehicles have the possibility of forming intelligent intersection management, and likely to occupy the leading role in future urban traffic. If route planning method can be used for route decision of autonomous vehicle, the urban traffic efficiency can be further improved. In this paper, we propose an Intelligent Intersection Control Protocol (IICP) for controlling autonomous vehicles cross intersection, and recommend route for autonomous vehicles to reduce travel time and improve urban traffic efficiency. …

Answer Ranking For Product-Related Questions Via Multiple Semantic Relations Modeling, Wenxuan Zhang, Yang Deng, Wai Lam

Research Collection School Of Computing and Information Systems

Many E-commerce sites now offer product-specific question answering platforms for users to communicate with each other by posting and answering questions during online shopping. However, the multiple answers provided by ordinary users usually vary diversely in their qualities and thus need to be appropriately ranked for each question to improve user satisfaction. It can be observed that product reviews usually provide useful information for a given question, and thus can assist the ranking process. In this paper, we investigate the answer ranking problem for product-related questions, with the relevant reviews treated as auxiliary information that can be exploited for facilitating …

Bridging Hierarchical And Sequential Context Modeling For Question-Driven Extractive Answer Summarization, Yang Deng, Wenxuan Zhang, Yaliang Li, Min Yang, Wai Lam, Ying Shen

Research Collection School Of Computing and Information Systems

Non-factoid question answering (QA) is one of the most extensive yet challenging application and research areas of retrieval-based question answering. In particular, answers to non-factoid questions can often be too lengthy and redundant to comprehend, which leads to the great demand on answer sumamrization in non-factoid QA. However, the multi-level interactions between QA pairs and the interrelation among different answer sentences are usually modeled separately on current answer summarization studies. In this paper, we propose a unified model to bridge hierarchical and sequential context modeling for question-driven extractive answer summarization. Specifically, we design a hierarchical compare-aggregate method to integrate the …

Towards An Optimal Outdoor Advertising Placement: When A Budget Constraint Meets Moving Trajectories, Ping Zhang, Zhifeng Bao, Yuchen Li, Guoliang Li, Yipeng Zhang, Zhiyong Peng

Research Collection School Of Computing and Information Systems

In this article, we propose and study the problem of trajectory-driven influential billboard placement: given a set of billboards U (each with a location and a cost), a database of trajectories T, and a budget L, we find a set of billboards within the budget to influence the largest number of trajectories. One core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories, while keeping the budget constraint into consideration. We show that this problem is NP-hard and present an enumeration based algorithm with (1-1/e) approximation ratio. However, the enumeration would …

Improving Event Detection Via Open-Domain Event Trigger Knowledge, Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li, Jun Xie

Research Collection School Of Computing and Information Systems

Event Detection (ED) is a fundamental task in automatically structuring texts. Due to the small scale of training data, previous methods perform poorly on unseen/sparsely labeled trigger words and are prone to overfitting densely labeled trigger words. To address the issue, we propose a novel Enrichment Knowledge Distillation (EKD) model to leverage external open-domain trigger knowledge to reduce the in-built biases to frequent trigger words in annotations. Experiments on benchmark ACE2005 show that our model outperforms nine strong baselines, is especially effective for unseen/sparsely labeled trigger words. The source code is released on https://github.com/shuaiwa16/ekd.git.

Search Me In The Dark: Privacy-Preserving Boolean Range Query Over Encrypted Spatial Data, Xiangyu Wang, Jianfeng Ma, Ximeng Liu, Robert H. Deng, Yinbin Miao, Dan Zhu, Zhuoran Ma

Research Collection School Of Computing and Information Systems

With the increasing popularity of geo-positioning technologies and mobile Internet, spatial keyword data services have attracted growing interest from both the industrial and academic communities in recent years. Meanwhile, a massive amount of data is increasingly being outsourced to cloud in the encrypted form for enjoying the advantages of cloud computing while without compromising data privacy. Most existing works primarily focus on the privacy-preserving schemes for either spatial or keyword queries, and they cannot be directly applied to solve the spatial keyword query problem over encrypted data. In this paper, we study the challenging problem of Privacy-preserving Boolean Range Query …

Recent Advances In Deep Learning For Object Detection, Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades. Visual object detection aims to find objects of certain target classes with precise localization in a given image and assign each object instance a corresponding class label. Due to the tremendous successes of deep learning based image classification, object detection techniques using deep learning have been actively studied in recent years. In this paper, we give a comprehensive survey of recent advances in visual object detection with deep learning. By reviewing a large body of recent related work in literature, …