An Attribute-Aware Attentive Gcn Model For Attribute Missing In Recommendation,
2022
Singapore Management University
An Attribute-Aware Attentive Gcn Model For Attribute Missing In Recommendation, Fan Liu, Zhiyong Cheng, Lei Zhu, Chenghao Liu, Liqiang Nie
Research Collection School Of Computing and Information Systems
As important side information, attributes have been widely exploited in the existing recommender system for better performance. However, in the real-world scenarios, it is common that some attributes of items/users are missing (e.g., some movies miss the genre data). Prior studies usually use a default value (i.e., "other") to represent the missing attribute, resulting in sub-optimal performance. To address this problem, in this paper, we present an attribute-aware attentive graph convolution network (A(2)-GCN). In particular, we first construct a graph, where users, items, and attributes are three types of nodes and their associations are edges. Thereafter, we leverage the graph …
Exploiting Reuse For Gpu Subgraph Enumeration,
2022
National University of Singapore
Exploiting Reuse For Gpu Subgraph Enumeration, Wentiao Guo, Yuchen Li, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Subgraph enumeration is important for many applications such as network motif discovery, community detection, and frequent subgraph mining. To accelerate the execution, recent works utilize graphics processing units (GPUs) to parallelize subgraph enumeration. The performances of these parallel schemes are dominated by the set intersection operations which account for up to $95\%$ of the total processing time. (Un)surprisingly, a significant portion (as high as $99\%$) of these operations is actually redundant, i.e., the same set of vertices is repeatedly encountered and evaluated. Therefore, in this paper, we seek to salvage and recycle the results of such operations to avoid repeated …
Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning,
2022
Singapore Management University
Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning, Sanne Rogiers, Elias Corneillie, Filip Lievens, Frederik Anseel, Peter Veelaert, Wilfried Philips
Research Collection Lee Kong Chian School Of Business
This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional manual data analysis, machine learning proves to be able to analyze the data more deeply and to discover connections in the data invisible to the human eye. The paper describes an experiment to measure and analyze the reactions of evaluators to job applicants who adopt specific behaviors: mimicry, suppress, immediacy and natural behavior. First, evaluation of the applicant qualifications by the interviewer reveals …
Analyzing The Impact Of Covid-19 Control Policies On Campus Occupancy And Mobility Via Wifi Sensing,
2022
Singapore Management University
Analyzing The Impact Of Covid-19 Control Policies On Campus Occupancy And Mobility Via Wifi Sensing, Camellia Zakaria, Amee Trivedi, Emmanuel Cecchet, Michael Chee, Prashant Shenoy, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies, primarily to automate contact tracing and social distancing measures. As more and more countries reopen from lockdowns, there remains a pressing need to minimize crowd movements and interactions, particularly in enclosed spaces. Many COVID-19 technology solutions leverage positioning systems, generally using Bluetooth and GPS, and can theoretically be adapted to monitor safety compliance within dedicated environments. However, they may not be the ideal modalities for indoor positioning. This article conjectures that analyzing user occupancy and mobility via deployed WiFi infrastructure can help institutions …
Performance Evaluation Of Aggregation-Based Group Recommender Systems For Ephemeral Groups,
2022
Singapore Management University
Performance Evaluation Of Aggregation-Based Group Recommender Systems For Ephemeral Groups, Edgar Ceh-Varela, Huiping Cao, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Recommender Systems (RecSys) provide suggestions in many decision-making processes. Given that groups of people can perform many real-world activities (e.g., a group of people attending a conference looking for a place to dine), the need for recommendations for groups has increased. A wide range of Group Recommender Systems (GRecSys) has been developed to aggregate individual preferences to group preferences. We analyze 175 studies related to GRecSys. Previous works evaluate their systems using different types of groups (sizes and cohesiveness), and most of such works focus on testing their systems using only one type of item, called Experience Goods (EG). As …
Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters,
2022
Wuhan University
Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Research Collection School Of Computing and Information Systems
Reorganizing bus frequencies to cater for actual travel demands can significantly save the cost of the public transport system. This paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services within the waiting time threshold can be maximized. We propose two variants of the problem, FAST and FASTCO, to cater for different application needs and prove that both are NP-hard. To solve FAST effectively and efficiently, we first present an …
Secure Deterministic Wallet And Stealth Address: Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key,
2022
Singapore Management University
Secure Deterministic Wallet And Stealth Address: Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang, Xiaorong Ke, Yining Liu
Research Collection School Of Computing and Information Systems
Deterministic Wallet (DW) and Stealth Address (SA) mechanisms have been widely adopted in the cryptocurrency community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that allows an arbitrary number of derived keys to be generated from a master key. However, these algorithms suffer a vulnerability that, when one derived key is compromised somehow, the damage is not limited to the leaked derived key only, but to the master key and in consequence all derived keys are compromised. In this article, we introduce and formalize a new signature variant, called Key-Insulated and Privacy-Preserving …
Deep Learning-Based Text Recognition Of Agricultural Regulatory Document,
2022
Singapore Management University
Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan
Research Collection School Of Computing and Information Systems
In this study, an OCR system based on deep learning techniques was deployed to digitize scanned agricultural regulatory documents comprising of certificates and labels. Recognition of the certificates and labels is challenging as they are scanned images of the hard copy form and the layout and size of the text as well as the languages vary between the various countries (due to diverse regulatory requirements). We evaluated and compared between various state-of-the-art deep learningbased text detection and recognition model as well as a packaged OCR library – Tesseract. We then adopted a two-stage approach comprising of text detection using Character …
Joint Hyperbolic And Euclidean Geometry Contrastive Graph Neural Networks,
2022
Singapore Management University
Joint Hyperbolic And Euclidean Geometry Contrastive Graph Neural Networks, Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang
Research Collection School Of Computing and Information Systems
Graph Neural Networks (GNNs) have demonstrated state-of-the-art performance in a wide variety of analytical tasks. Current GNN approaches focus on learning representations in a Euclidean space, which are effective in capturing non-tree-like structural relations, but they fail to model complex relations in many real-world graphs, such as tree-like hierarchical graph structure. This paper instead proposes to learn representations in both Euclidean and hyperbolic spaces to model these two types of graph geometries. To this end, we introduce a novel approach - Joint hyperbolic and Euclidean geometry contrastive graph neural networks (JointGMC). JointGMC is enforced to learn multiple layer-wise optimal combinations …
Eeg-Video Emotion-Based Summarization: Learning With Eeg Auxiliary Signals,
2022
Singapore Management University
Eeg-Video Emotion-Based Summarization: Learning With Eeg Auxiliary Signals, Wai-Cheong L. Lew, Di Wang, Kai-Keng Ang, Joo-Hwee Lim, Chai Quek, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Video summarization is the process of selecting a subset of informative keyframes to expedite storytelling with limited loss of information. In this paper, we propose an EEG-Video Emotion-based Summarization (EVES) model based on a multimodal deep reinforcement learning (DRL) architecture that leverages neural signals to learn visual interestingness to produce quantitatively and qualitatively better video summaries. As such, EVES does not learn from the expensive human annotations but the multimodal signals. Furthermore, to ensure the temporal alignment and minimize the modality gap between the visual and EEG modalities, we introduce a Time Synchronization Module (TSM) that uses an attention mechanism …
Constrained Multiagent Reinforcement Learning For Large Agent Population,
2022
Singapore Management University
Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar
Research Collection School Of Computing and Information Systems
Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …
Toward Intention Discovery For Early Malice Detection In Bitcoin,
2022
Singapore Management University
Toward Intention Discovery For Early Malice Detection In Bitcoin, Ling Cheng, Feida Zhu, Yong Wang, Huiwen Liu
Research Collection School Of Computing and Information Systems
Bitcoin has been subject to illicit activities more often than probably any other financial assets, due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all the three properties of (I) early detection, (II) good interpretability, and (III) versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without satisfying interpretability and are only available for retrospective analysis of a specific illicit type.First, we present asset transfer paths, which aim to describe addresses' early characteristics. Next, with a decision tree based …
Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry,
2022
Singapore Management University
Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry, Yang Gao, Wenjing Duan, Huaxia Rui
Research Collection School Of Computing and Information Systems
Social media has become a vital platform for voicing product-related experiences that may not only reveal product defects but also impose pressure on firms to act more promptly than before. This study scrutinizes the rarely-studied relationship between these voices and the speed of product recalls in the context of the pharmaceutical industry where social media pharmacovigilance is becoming increasingly important for the detection of drug safety signals. Using Federal Drug Administration (FDA) drug enforcement reports and social media data crawled from online forums and Twitter, we investigate whether social media can accelerate the product recall process in the context of …
Towards A Model On Digital Transformation Within The Higher Education Sector – A South African Perspective,
2022
Independent Institute of Education
Towards A Model On Digital Transformation Within The Higher Education Sector – A South African Perspective, Olusegun A. Ajigini
African Conference on Information Systems and Technology
Digital transformation is the application of technology to build new business models, processes, software and systems that result in more profitable revenue, greater competitive advantage and higher efficiency. The factors influencing digital transformation in the higher educational sector were examined in this study. Specifically, data was drawn from 400 respondents and the following variables: organizational IT application portfolio, organizational culture, organizational structure, leadership and ethics predict digital transformation in higher educational sector by using regression analysis. The researcher found that the organizational culture contribution was the highest by predicting 78.9% of digital transformation in the higher education sector.
Towards A Conceptual Model For Developing A Career Prediction System For Students’ Subject Selection At Secondary School Level,
2022
Makerere University
Towards A Conceptual Model For Developing A Career Prediction System For Students’ Subject Selection At Secondary School Level, Moses Kamondo Tuhame, Gilbert Maiga, Annabella Habinka, Barbara Kayondo
African Conference on Information Systems and Technology
Career choice prediction has been a complex phenomenon both in developed and developing countries. Though various theories that describe career prediction have emerged, their practical implementation in the form of a system has been hampered by the shortfalls that come along with each of them. However, there is no existing theoretically based holistic model that merges various theories that can inform the development of such a system in the developing world context. This paper, therefore, aims at proposing a holistic conceptual model that integrates a number of variables to inform the development of a career prediction system in the developing …
Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology,
2022
Chapman University
Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead
Art Faculty Articles and Research
We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.
28 Ghz Patch Antenna Array With Reduced Mutual Coupling For 5g Communications Systems,
2022
University of Dar es salaam
28 Ghz Patch Antenna Array With Reduced Mutual Coupling For 5g Communications Systems, Rahabu F. Mwang’Amba, Hashimu Uledi Iddi
Tanzania Journal of Engineering and Technology (TJET)
A 28 GHz patch antenna array with reduced mutual coupling for 5G communication systems is presented in this paper. Two elements antenna array was simulated with a periodic boundary to represent an infinity array. The antenna array is attached with a pair of the coupled directional coupler with a coupling value of -3.47 dB, and transmission lengths of 3.40 mm and 7.62 mm depending on the antenna array's magnitude and phase coefficient were designed and simulated. A reduced mutual coupling of -31.86 dB compared to -10.75 dB for an array without a decoupling network was observed. The wide scanning angle …
(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases,
2022
CUNY New York City College of Technology
(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
