Physical Sciences and Mathematics Commons^™

View, Like, Comment, Post: Analyzing User Engagement By Topic At 4 Levels Across 5 Social Media Platforms For 53 News Organizations, Kholoud K. Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and …

Sliced Wasserstein Generative Models, Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc Van Gool

Research Collection School Of Computing and Information Systems

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions. Unfortunately, it is challenging to approximate the WD of high-dimensional distributions. In contrast, the sliced Wasserstein distance (SWD) factorizes high-dimensional distributions into their multiple one-dimensional marginal distributions and is thus easier to approximate. In this paper, we introduce novel approximations of the primal and dual SWD. Instead of using a large number of random projections, as it is done by conventional SWD approximation methods, we propose to approximate SWDs with a small number of parameterized orthogonal projections …

Stabilized Svrg: Simple Variance Reduction For Nonconvex Optimization, Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang

Research Collection School Of Computing and Information Systems

Variance reduction techniques like SVRG provide simple and fast algorithms for optimizing a convex finite-sum objective. For nonconvex objectives, these techniques can also find a first-order stationary point (with small gradient). However, in nonconvex optimization it is often crucial to find a second-order stationary point (with small gradient and almost PSD hessian). In this paper, we show that Stabilized SVRG (a simple variant of SVRG) can find an $\epsilon$-second-order stationary point using only $\tilde{O}(n^{2/3}/\epsilon^2 + n/\epsilon^{1.5})$ stochastic gradients. To our best knowledge, this is the first second-order guarantee for a simple variant of SVRG. The running time almost matches the …

Automatic Loop Summarization Via Path Dependency Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Yang Liu, Wei Le, Xiaohong Li

Research Collection School Of Computing and Information Systems

Analyzing loops is very important for various software engineering tasks such as bug detection, test case generation and program optimization. However, loops are very challenging structures for program analysis, especially when (nested) loops contain multiple paths that have complex interleaving relationships. In this paper, we propose the path dependency automaton (PDA) to capture the dependencies among the multiple paths in a loop. Based on the PDA, we first propose a loop classification to understand the complexity of loop summarization. Then, we propose a loop analysis framework, named Proteus, which takes a loop program and a set of variables of interest …

Geometric Top-K Processing: Updates Since Mdm'16 [Advanced Seminar], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

The top-k query has been studied extensively, and is considered the norm for multi-criteria decision making in large databases. In recent years, research has considered several complementary operators to the traditional top-k query, drawing inspiration (both in terms of problem formulation and solution design) from the geometric nature of the top-k processing model. In this seminar, we will present advances in that stream of work, focusing on updates since the preliminary seminar on the same topic in MDM'16.

Political Discussions In Homogeneous And Cross-Cutting Communication Spaces, Qatar Computing Research Institute, Haewoon Kwak, Universität Bamberg

Research Collection School Of Computing and Information Systems

Online platforms, such as Facebook, Twitter, and Reddit, provide users with a rich set of features for sharing and consuming political information, expressing political opinions, and exchanging potentially contrary political views. In such activities, two types of communication spaces naturally emerge: those dominated by exchanges between politically homogeneous users and those that allow and encourage crosscutting exchanges in politically heterogeneous groups. While research on political talk in online environments abounds, we know surprisingly little about the potentially varying nature of discussions in politically homogeneous spaces as compared to cross-cutting communication spaces. To fill this gap, we use Reddit to explore …

Dynamic Fusion With Intra-And Inter-Modality Attention Flow For Visual Question Answering, Peng Gao, Zhengkai Jiang, Haoxuan You, Pan Lu, Steven C. H. Hoi, Xiaogang Wang, Hongsheng Li

Research Collection School Of Computing and Information Systems

Learning effective fusion of multi-modality features is at the heart of visual question answering. We propose a novel method of dynamically fusing multi-modal features with intra- and inter-modality information flow, which alternatively pass dynamic information between and across the visual and language modalities. It can robustly capture the high-level interactions between language and vision domains, thus significantly improves the performance of visual question answering. We also show that the proposed dynamic intra-modality attention flow conditioned on the other modality can dynamically modulate the intramodality attention of the target modality, which is vital for multimodality feature fusion. Experimental evaluations on the …

Learning Unsupervised Video Object Segmentation Through Visual Attention, Wenguan Wang, Hongmei Song, Shuyang Zhao, Jianbing Shen, Sanyuan Zhao, Steven C. H. Hoi, Haibin Ling

Research Collection Yong Pung How School Of Law

This paper conducts a systematic study on the role of visual attention in Unsupervised Video Object Segmentation (UVOS) tasks. By elaborately annotating three popular video segmentation datasets (DAVIS, Youtube-Objects and SegTrack V2) with dynamic eye-tracking data in the UVOS setting, for the first time, we quantitatively verified the high consistency of visual attention behavior among human observers, and found strong correlation between human attention and explicit primary object judgements during dynamic, task-driven viewing. Such novel observations provide an in-depth insight into the underlying rationale behind UVOS. Inspired by these findings, we decouple UVOS into two sub-tasks: UVOS-driven Dynamic Visual Attention …

Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang

Research Collection School Of Computing and Information Systems

Since the introduction of Bitcoin in 2008, cryptocurrency has been undergoing a quick and explosive development. At the same time, privacy protection, one of the key merits of cryptocurrency, has attracted much attention by the community. A deterministic wallet algorithm and a stealth address algorithm have been widely adopted in the community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that an arbitrary number of derived keys can be generated from a master key. However, these algorithms suffer a vulnerability. In particular, when a minor fault happens (say, one derived key is …

Lpgl: Low-Power Graphics Library For Mobile Ar Headsets, Choi Jaewon, Hyeonjung Park, Jeongyeup Paek, Rajesh Krishna Balan, Jeonggil Ko

Research Collection School Of Computing and Information Systems

We present LpGL, an OpenGL API compatible Low-power Graphics Library for energy efficient AR headset applications. We first characterize the power consumption patterns of a state of the art AR headset, Magic Leap One, and empirically show that its internal GPU is the most impactful and controllable energy consumer. Based on the preliminary studies, we design LpGL so that it uses the device's gaze/head orientation information and geometry data to infer user perception information, intercepts application-level graphics API calls, and employs frame rate control, mesh simplification, and culling techniques to enhance energy efficiency of AR headsets without detriment of user …

Exploratory Analysis Of Individuals' Mobility Patterns And Experienced Conflicts In Workgroup, Nur Camellia Binte Zakaria, Kenneth T. Goh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Much research argues the importance of supporting social interactions in teams and communities. The field of mobile sensing alone offers significant advances in recording and understanding human and group behaviours. However, little is known about behavioural changes as a consequence of in-group phenomena. One prominent example is intra-group conflict, which naturally arises between diverse groups of people. We demonstrate the feasibility of our approach to extract mobility patterns of individual's group behaviours sensed from a WiFi indoor localisation system and explore how these patterns relate to their team processes. 62 students enrolled in a project-intensive module, Software Engineering, were tracked …

Distributed Similarity Queries In Metric Spaces, Keyu Yang, Xin Ding, Yuanliang Zhang, Lu Chen, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Similarity queries, including range queries and k nearest neighbor (kNN) queries, in metric spaces have applications in many areas such as multimedia retrieval, computational biology and location-based services. With the growing volumes of data, a distributed method is required. In this paper, we propose an Asynchronous Metric Distributed System (AMDS), to support efficient metric similarity queries in the distributed environment. AMDS uniformly partitions the data with the pivot-mapping technique to ensure the load balancing, and employs publish/subscribe communication model to asynchronous process large scale of queries. The employment of asynchronous processing model also improves robustness and efficiency of AMDS. In …

Transferrable Prototypical Networks For Unsupervised Domain Adaptation, Yingwei Pan, Ting Yao, Yehao Li, Yu Wang, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

In this paper, we introduce a new idea for unsupervised domain adaptation via a remold of Prototypical Networks, which learn an embedding space and perform classification via a remold of the distances to the prototype of each class. Specifically, we present Transferrable Prototypical Networks (TPN) for adaptation such that the prototypes for each class in source and target domains are close in the embedding space and the score distributions predicted by prototypes separately on source and target data are similar. Technically, TPN initially matches each target example to the nearest prototype in the source domain and assigns an example a …

Exploring Object Relation In Mean Teacher For Cross-Domain Detection, Qi Cai, Yingwei Pan, Chong-Wah Ngo, Xinmei Tian, Lingyu Duan, Ting Yao

Research Collection School Of Computing and Information Systems

Rendering synthetic data (e.g., 3D CAD-rendered images) to generate annotations for learning deep models in vision tasks has attracted increasing attention in recent years. However, simply applying the models learnt on synthetic images may lead to high generalization error on real images due to domain shift. To address this issue, recent progress in cross-domain recognition has featured the Mean Teacher, which directly simulates unsupervised domain adaptation as semi-supervised learning. The domain gap is thus naturally bridged with consistency regularization in a teacher-student scheme. In this work, we advance this Mean Teacher paradigm to be applicable for crossdomain detection. Specifically, we …

Single Image Reflection Removal Beyond Linearity, Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Due to the lack of paired data, the training of image reflection removal relies heavily on synthesizing reflection images. However, existing methods model reflection as a linear combination model, which cannot fully simulate the real-world scenarios. In this paper, we inject non-linearity into reflection removal from two aspects. First, instead of synthesizing reflection with a fixed combination factor or kernel, we propose to synthesize reflection images by predicting a non-linear alpha blending mask. This enables a free combination of different blurry kernels, leading to a controllable and diverse reflection synthesis. Second, we design a cascaded network for reflection removal with …

Time-Based Payout Ratio For Coordinating Supply And Demand On An On-Demand Service Platform, Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun Chen, Hai Wang

Research Collection School Of Computing and Information Systems

Many on-demand service platforms use a fixed payout ratio (i.e., the percentage of the platform’s revenue that is paid to the providers) regardless of the customer demand and the number of participating providers that tend to vary over time. In this chapter, we examine the implications of time-based payout ratios. To do so, we first present a queueing model with endogenous supply (number of participating providers) and endogenous demand (customer request rate) to model this on-demand service platform. In our model, earnings-sensitive independent providers have heterogeneous reservation price (for work participation) to serve wait-time and price-sensitive customers with heterogeneous valuation …

How ‘Hot’ Is Too Hot? Evaluating Acceptable Outdoor Thermal Comfort Ranges In An Equatorial Urban Park, Su Li Heng, Winston T. L. Chow

Research Collection School of Social Sciences

Urban green spaces offer vital ecosystem services such as regulating elevated temperatures in cities. Less information exists, however, on how urban green spaces influence outdoor thermal comfort (OTC), which is dependent on people’s perceptions of the complex interactions amongst ambient humidity, wind and both air and radiant temperatures. In this study, we analysed an existing OTC dataset compiled within a large Singapore urban park and calibrated OTC thresholds for physiological equivalent temperatures (PET) by analysing PET against thermal perception survey responses from the park visitors (n = 1508). We examined OTC according to (i) neutral, (ii) acceptable and (iii) preferred …

Examining Augmented Virtuality Impairment Simulation For Mobile App Accessibility Design, Tsu Wei, Kenny (Zhu Shuwei, Kenny) Choo, Rajesh Krishna Balan, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

With mobile apps rapidly permeating all aspects of daily living with use by all segments of the population, it is crucial to support the evaluation of app usability for specific impaired users to improve app accessibility. In this work, we examine the effects of using our augmented virtuality impairment simulation system–Empath-D–to support experienced designer-developers to redesign a mockup of commonly used mobile application for cataract-impaired users, comparing this with existing tools that aid designing for accessibility. We show that the use of augmented virtuality for assessing usability supports enhanced usability challenge identification, finding more defects and doing so more accurately …

Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.

Celltrademap: Delineating Trade Areas For Urban Commercial Districts With Cellular Networks, Yi Zhao, Zimu Zhou, Xu Wang, Tongtong Liu, Yunhao Liu, Zheng Yang

Research Collection School Of Computing and Information Systems

Understanding customer mobility patterns to commercial districts is crucial for urban planning, facility management, and business strategies. Trade areas are a widely applied measure to quantity where the visitors are from. Traditional trade area analysis is limited to small-scale or store-level studies because information such as visits to competitor commercial entities and place of residence is collected by labour-intensive questionnaires or heavily biased location-based social media data. In this paper, we propose CellTradeMap, a novel district-level trade area analysis framework using mobile flow records (MFRs), a type of fine-grained cellular network data. CellTradeMap extracts robust location information from the irregularly …

Managing The Power And Pitfalls Of Data In Ai, Singapore Management University

Perspectives@SMU

Ethics and education are crucial in maintaining data privacy and augmenting human ability

“It’s difficult to imagine the power that you’re going to have when so many different sorts of data are available.” – Tim Berners-Lee, father of the Internet

“Before Google, and long before Facebook, Bezos had realised that the greatest value of an online company lay in the consumer data it collected.” – George Packer, author for the New Yorker

The Future Robo-Advisor, Catalin Burlacu

MITB Thought Leadership Series

The accelerated digitalisation of both people and business around the world today is having a huge impact on the investment management and advisory space. The addition of new and vastly larger data sets, as well as exponentially more sophisticated analytical tools to turn that data into usable information is constantly changing the way investments are decided on, made and managed.

Neural Multimodal Belief Tracker With Adaptive Attention For Dialogue Systems, Zheng Zhang, Lizi Liao, Minlie Huang, Xiaoyan Zhu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multimodal dialogue systems are attracting increasing attention with a more natural and informative way for human-computer interaction. As one of its core components, the belief tracker estimates the user's goal at each step of the dialogue and provides a direct way to validate the ability of dialogue understanding. However, existing studies on belief trackers are largely limited to textual modality, which cannot be easily extended to capture the rich semantics in multimodal systems such as those with product images. For example, in fashion domain, the visual appearance of clothes play a crucial role in understanding the user's intention. In this …

Multimodal Review Generation For Recommender Systems, Quoc Tuan Truong, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Key to recommender systems is learning user preferences, which are expressed through various modalities. In online reviews, for instance, this manifests in numerical rating, textual content, as well as visual images. In this work, we hypothesize that modelling these modalities jointly would result in a more holistic representation of a review towards more accurate recommendations. Therefore, we propose Multimodal Review Generation (MRG), a neural approach that simultaneously models a rating prediction component and a review text generation component. We hypothesize that the shared user and item representations would augment the rating prediction with richer information from review text, while sensitizing …

Adversarial Sample Detection For Deep Neural Network Through Model Mutation Testing, Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang, Zhang Peixin

Research Collection School Of Computing and Information Systems

No abstract provided.

A Homophily-Free Community Detection Framework For Trajectories With Delayed Responses, Chung-Kyun Han, Shih-Fen Cheng, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

No abstract provided.

Concluding Remarks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch

Research Collection School Of Computing and Information Systems

This chapter summarizes the major contributions in this book and discusses their possible positions and requirements in some future scenarios. Section 8.1 follows the book structure to revisit the key contributions of this book in both theories and applications. The developed algorithms, such as the VA-ARTs for hyperparameter adaptation and the GHF-ART for multimedia representation and fusion, and the four applications, such as clustering and retrieving socially enriched multimedia data, are concentrated using one paragraph and three paragraphs, respectively. In Sect. 8.2, the roles of the proposed ART-embodied algorithms in social media clustering tasks are highlighted, and their possible evolutions …

Neural Multimodal Belief Tracker With Adaptive Attention For Dialogue Systems, Zheng Zhang, Lizi Liao, Minlie Huang, Xiaoyan Zhu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multimodal dialogue systems are attracting increasing attention with a more natural and informative way for human-computer interaction. As one of its core components, the belief tracker estimates the user's goal at each step of the dialogue and provides a direct way to validate the ability of dialogue understanding. However, existing studies on belief trackers are largely limited to textual modality, which cannot be easily extended to capture the rich semantics in multimodal systems such as those with product images. For example, in fashion domain, the visual appearance of clothes play a crucial role in understanding the user's intention. In this …

9.6 Million Links In Source Code Comments: Purpose, Evolution, And Decay, Hideaki Hata, Christoph Treude, Raula Gaikovina Kula, Takashi Ishio

Research Collection School Of Computing and Information Systems

Links are an essential feature of the World Wide Web, and source code repositories are no exception. However, despite their many undisputed benefits, links can suffer from decay, insufficient versioning, and lack of bidirectional traceability. In this paper, we investigate the role of links contained in source code comments from these perspectives. We conducted a large-scale study of around 9.6 million links to establish their prevalence, and we used a mixed-methods approach to identify the links' targets, purposes, decay, and evolutionary aspects. We found that links are prevalent in source code repositories, that licenses, software homepages, and specifications are common …

Automatically Generating Documentation For Lambda Expressions In Java, Anwar Alqaimi, Patanamon Thongtanunam, Christoph Treude

Research Collection School Of Computing and Information Systems

When lambda expressions were introduced to the Java programming language as part of the release of Java 8 in 2014, they were the language’s first step into functional programming. Since lambda expressions are still relatively new, not all developers use or understand them. In this paper, we first present the results of an empirical study to determine how frequently developers of GitHub repositories make use of lambda expressions and how they are documented. We find that 11% of Java GitHub repositories use lambda expressions, and that only 6% of the lambda expressions are accompanied by source code comments. We then …