Utilizing Computational Trust To Identify Rumor Spreaders On Twitter,
2018
Singapore Management University
Utilizing Computational Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
Ubiquitous use of social media such as microblogging platforms opens unprecedented chances for false information to diffuse online. Facing the challenges in such a so-called “post-fact” era, it is very important for intelligent systems to not only check the veracity of information but also verify the authenticity of the users who spread the information, especially in time-critical situations such as real-world emergencies, where urgent measures have to be taken for stopping the spread of fake information. In this work, we propose a novel machine-learning-based approach for automatic identification of the users who spread rumorous information on Twitter by leveraging computational …
Attention-Based Lstm-Cnns For Uncertainty Identification On Chinese Social Media Texts,
2018
Singapore Management University
Attention-Based Lstm-Cnns For Uncertainty Identification On Chinese Social Media Texts, Binyang Li, Kaiming Zhou, Wei Gao, Xu Han Han, Linna Zhou
Research Collection School Of Computing and Information Systems
Uncertainty identification is an important semantic processing task, which is crucial to the quality of information in terms of factuality in many techniques, e.g. topic detection, question answering. Especially in social media, the texts are written informally which are widely used in many applications, so the factuality has become a premier concern. However, existing approaches that still rely on lexical cues suffer greatly from the casual or word-of-mouth peculiarity of social media, in which the cue phrases are often expressed in sub-standard form or even omitted from sentences. To tackle these problems, this paper proposes the attention-based LSTM-CNNs for the …
Living With Artificial Intelligence – Developing A Theory On Trust In Health Chatbots,
2018
Singapore Management University
Living With Artificial Intelligence – Developing A Theory On Trust In Health Chatbots, Weiyu Wang, Keng Siau
Research Collection School Of Computing and Information Systems
The current world is AI-filled and AI-fueled. Humans need to be able to live in harmony with AI. In this research, we aim to develop a theory on Trust between human and health chatbots. With the development of intelligent personal assistants, chatbots are becoming common and ubiquitous. Chatbots can behave as a conversational partner, complete information acquisition, and provide responses to inquiries. Chatbots have been widely used in the healthcare area, supporting physicians and assisting patients. The potential threats to privacy issues and the unpredictable performances of the chatbots hindered people’s trust and adoption of the new technology. This research-in-progress …
Deep Unsupervised Pixelization,
2018
Singapore Management University
Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong
Research Collection School Of Computing and Information Systems
In this paper, we present a novel unsupervised learning method for pixelization. Due to the difficulty in creating pixel art, preparing the paired training data for supervised learning is impractical. Instead, we propose an unsupervised learning framework to circumvent such difficulty. We leverage the dual nature of the pixelization and depixelization, and model these two tasks in the same network in a bi-directional manner with the input itself as training supervision. These two tasks are modeled as a cascaded network which consists of three stages for different purposes. GridNet transfers the input image into multi-scale grid-structured images with different aliasing …
Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality,
2018
Oregon State University
Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang
Research Collection School Of Computing and Information Systems
The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep …
An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science,
2018
Singapore Management University
An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science, Aldy Gunawan, Michelle L. F. Cheong, Johnson Poh
Research Collection School Of Computing and Information Systems
This paper presents a newpostgraduate level course, named Applied Statistical Analysis with R. Wepresent the course structure, teaching methodology including the assessmentframework and student feedback. The course covers the basic concepts ofstatistics, the knowledge of applying statistical theory in analyzing real dataand the skill of developing statistical applications with R programminglanguage. The first half of each lesson is dedicated to teaching students thestatistical concepts while the second half focuses on the practical aspects ofimplementing the concepts within the RStudio console. The Project-BasedLearning (PBL) approach is adopted to encourage students to apply the knowledgegained to solve real world problems, answer complex …
On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data,
2018
Singapore Management University
On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data, Pei-Chi Lo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
The Linguistic Inquiry and Word Count (LIWC) tool is a psycholinguistics tool that has been widely used in both psychology and sociology research, and the LIWC scores derived from user-generated content are known to be good features for personality prediction [1], [2]. LIWC, however, is language specific as it relies on counting the percentage of predefined dictionary words occurring in the content. For content written in English Creoles which are languages based on English, the original English LIWC may not perform optimally due to its lack of words which are only used in the English Creoles. In this paper, we …
Cross Euclidean-To-Riemannian Metric Learning With Application To Face Recognition From Video,
2018
Singapore Management University
Cross Euclidean-To-Riemannian Metric Learning With Application To Face Recognition From Video, Zhiwu Huang, R. Wang, S. Shan, Gool L Van
Research Collection School Of Computing and Information Systems
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geometry of the underlying Riemannian manifolds. In this paper, we propose a novel metric learning framework to learn a distance metric across a Euclidean space and a Riemannian manifold to fuse average appearance and pattern variation of faces within one video. The proposed metric learning framework can handle three typical tasks of video-based face recognition: Video-to-Still, Still-to-Video and Video-to-Video settings. To accomplish this new framework, by exploiting typical Riemannian …
A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization,
2018
Singapore Management University
A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization, Zhize Li, Jian Li
Research Collection School Of Computing and Information Systems
We analyze stochastic gradient algorithms for optimizing nonconvex, nonsmooth finite-sum problems. In particular, the objective function is given by the summation of a differentiable (possibly nonconvex) component, together with a possibly non-differentiable but convex component. We propose a proximal stochastic gradient algorithm based on variance reduction, called ProxSVRG+. Our main contribution lies in the analysis of ProxSVRG+. It recovers several existing convergence results and improves/generalizes them (in terms of the number of stochastic gradient oracle calls and proximal oracle calls). In particular, ProxSVRG+ generalizes the best results given by the SCSG algorithm, recently proposed by [Lei et al., NIPS'17] for …
Active Matting,
2018
Singapore Management University
Active Matting, Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson Lau
Research Collection School Of Computing and Information Systems
Image matting is an ill-posed problem. It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object. A fine user input is essential to obtain a good result, which is either time consuming or suitable for experienced users who know where to place the strokes. In this paper, we explore the intrinsic relationship between the user input and the matting algorithm to address the problem of where and when the user should provide the input. Our aim is to discover the most informative sequence of regions for user input in order to produce …
Improving Strategic It Investment Decisions By Reducing Information Asymmetry,
2018
University of South Florida
Improving Strategic It Investment Decisions By Reducing Information Asymmetry, Thomas P. Stablein
USF Tampa Graduate Theses and Dissertations
The unprecedented ubiquity with which technological advancements, such as blockchain, the Internet of things (IoT), big data, machine learning, and artificial intelligence (AI), are impacting the world has forced large organizations to rethink their information technology roadmaps. Their decisions about how they invest in technology have become more important. It is against this backdrop that companies must decide how much to invest in their aging technologies versus these new potentially transformational ones. A decision is only as good as the information available to the decision-makers when they make it. This research project seeks to understand the effects that information asymmetry …
Enhancing The Design Of A Cybersecurity Risk Management Solution For Communities Of Trust,
2018
University of South Florida
Enhancing The Design Of A Cybersecurity Risk Management Solution For Communities Of Trust, James E. Fulford Jr.
USF Tampa Graduate Theses and Dissertations
Research into cybersecurity risks and various methods of evaluating those threats has become an increasingly important area of academic and practitioner investigations. Of particular interest in this field is enhancing the designs and informing capabilities of cybersecurity risk management solutions for users who desire to understand how organizations are impacted when such risks are exploited. Many of the cybersecurity risk management solutions are extremely technical and require their users to have a commensurate level of technical acumen. In the situation evaluated during this research project, the founders of the company being researched had created a highly technical risk management solution …
Performance Indicators Analysis Inside A Call Center Using A Simulation Program,
2018
University of Tirana
Performance Indicators Analysis Inside A Call Center Using A Simulation Program, Ditila Ekmekçiu, Markela Muça, Adrian Naço
International Journal of Business and Technology
This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key …
Modelling Business And Management Systems Using Fuzzy Cognitive Maps: A Critical Overview,
2018
University of Patras
Modelling Business And Management Systems Using Fuzzy Cognitive Maps: A Critical Overview, Peter P. Groumpos
International Journal of Business and Technology
A critical overview of modelling Business and Management (B&M) Systems using Fuzzy Cognitive Maps is presented. A limited but illustrative number of specific applications of Fuzzy Cognitive Maps in diverse B&M systems, such as e business, performance assessment, decision making, human resources management, planning and investment decision making processes is provided and briefly analyzed. The limited survey is given in a table with statics of using FCMs in B&M systems during the last 15 years. The limited survey shows that the applications of Fuzzy Cognitive Maps to today’s Business and Management studies has been steadily increased especially during the last …
Personalized Microblog Sentiment Classification Via Adversarial Cross-Lingual Learning,
2018
Singapore Management University
Personalized Microblog Sentiment Classification Via Adversarial Cross-Lingual Learning, Weichao Wang, Shi Feng, Wei Gao, Daling Wang, Yifei Zhang
Research Collection School Of Computing and Information Systems
Sentiment expression in microblog posts can be affected by user’s personal character, opinion bias, political stance and so on. Most of existing personalized microblog sentiment classification methods suffer from the insufficiency of discriminative tweets for personalization learning. We observed that microblog users have consistent individuality and opinion bias in different languages. Based on this observation, in this paper we propose a novel user-attention-based Convolutional Neural Network (CNN) model with adversarial cross-lingual learning framework. The user attention mechanism is leveraged in CNN model to capture user’s language-specific individuality from the posts. Then the attention-based CNN model is incorporated into a novel …
Cross-Border Interbank Payments And Settlements: Emerging Opportunities For Digital Transformation,
2018
Singapore Management University
Cross-Border Interbank Payments And Settlements: Emerging Opportunities For Digital Transformation, Yi Meng Lau, Et Al
Research Collection School Of Computing and Information Systems
The report “Cross-Border Interbank Payments and Settlements” is a cross-jurisdictional industry collaboration between Canada, Singapore and the United Kingdom to examine the existing challenges and frictions that arise when undertaking crossborder payments. This report explores proposals for new and more efficient models for processing cross-border transactions.
Joint Representation Learning Of Cross-Lingual Words And Entities Via Attentive Distant Supervision,
2018
Singapore Management University
Joint Representation Learning Of Cross-Lingual Words And Entities Via Attentive Distant Supervision, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, Tiansi Dong
Research Collection School Of Computing and Information Systems
Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for joint representation learning of cross-lingual words and entities. It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts. Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases. We utilize two types of regularizers to align cross-lingual words and entities, and design knowledge attention and crosslingual attention to further reduce noises. We conducted a series of experiments on …
Vpsearch: Achieving Verifiability For Privacy-Preserving Multi-Keyword Search Over Encrypted Cloud Data,
2018
Shandong University
Vpsearch: Achieving Verifiability For Privacy-Preserving Multi-Keyword Search Over Encrypted Cloud Data, Zhiguo Wan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Although cloud computing offers elastic computation and storage resources, it poses challenges on verifiability of computations and data privacy. In this work we investigate verifiability for privacy-preserving multi-keyword search over outsourced documents. As the cloud server may return incorrect results due to system faults or incentive to reduce computation cost, it is critical to offer verifiability of search results and privacy protection for outsourced data at the same time. To fulfill these requirements, we design aVerifiablePrivacy-preserving keywordSearch scheme, called VPSearch, by integrating an adapted homomorphic MAC technique with a privacy-preserving multi-keyword search scheme. The proposed scheme enables the client to …
Latent Dirichlet Allocation For Textual Student Feedback Analysis,
2018
Singapore Management University
Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Lin
Research Collection School Of Computing and Information Systems
Education institutions collect feedback from students upon course completion and analyse it to improve curriculum design, delivery methodology and students' learning experience. A large part of feedback comes in the form textual comments, which pose a challenge in quantifying and deriving insights. In this paper, we present a novel approach of the Latent Dirichlet Allocation (LDA) model to address this difficulty in handling textual student feedback. The analysis of quantitative part of student feedback provides generalratings and helps to identify aspects of the teaching that are successful and those that can improve. The reasons for the failure or success, however, …
River: A Real-Time Influence Monitoring System On Social Media Stream,
2018
Singapore Management University
River: A Real-Time Influence Monitoring System On Social Media Stream, Mo Sha, Yuchen Li, Yanhao Wang, Wentian Guo, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Social networks generate a massive amount of interaction data among users in the form of streams. To facilitate social network users to consume the continuously generated stream and identify preferred viral social contents, we present a real-time monitoring system called River to track a small set of influential social contents from high-speed streams in this demo. River has four novel features which distinguish itself from existing social monitoring systems: (1) River extracts a set of contents which collectively have the most significant influence coverage while reducing the influence overlaps; (2) River is topic-based and monitors the contents which are relevant …
