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Articles 181 - 210 of 448
Full-Text Articles in Databases and Information Systems
Multi-Level Cross-View Contrastive Learning For Knowledge-Aware Recommender System, Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao
Multi-Level Cross-View Contrastive Learning For Knowledge-Aware Recommender System, Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao
Research Collection School Of Computing and Information Systems
Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-aware recommendation (KGR). However, there is a natural deficiency for GNN-based KGR models, that is, the sparse supervised signal problem, which may make their actual performance drop to some extent. Inspired by the recent success of contrastive learning in mining supervised signals from data itself, in this paper, we focus on exploring the contrastive learning in KG-aware recommendation and propose a novel multi-level cross-view contrastive learning mechanism, named MCCLK. Different from traditional contrastive learning methods which …
Efficient Neural Neighborhood Search For Pickup And Delivery Problems, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Hongliang Guo, Yuejiao Gong, Meng Chee Chee
Efficient Neural Neighborhood Search For Pickup And Delivery Problems, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Hongliang Guo, Yuejiao Gong, Meng Chee Chee
Research Collection School Of Computing and Information Systems
We present an efficient Neural Neighborhood Search (N2S) approach for pickup and delivery problems (PDPs). In specific, we design a powerful Synthesis Attention that allows the vanilla self-attention to synthesize various types of features regarding a route solution. We also exploit two customized decoders that automatically learn to perform removal and reinsertion of a pickup-delivery node pair to tackle the precedence constraint. Additionally, a diversity enhancement scheme is leveraged to further ameliorate the performance. Our N2S is generic, and extensive experiments on two canonical PDP variants show that it can produce state-of-the-art results among existing neural methods. Moreover, it even …
Hakg: Hierarchy-Aware Knowledge Gated Network For Recommendation, Yuntao Du, Xinjun Zhu, Lu Chen, Baihua Zheng, Yunjun Gao
Hakg: Hierarchy-Aware Knowledge Gated Network For Recommendation, Yuntao Du, Xinjun Zhu, Lu Chen, Baihua Zheng, Yunjun Gao
Research Collection School Of Computing and Information Systems
Knowledge graph (KG) plays an increasingly important role to improve the recommendation performance and interpretability. A recent technical trend is to design end-to-end models based on information propagation mechanism. However, existing propagationbased methods fail to (1) model the underlying hierarchical structures and relations, and (2) capture the high-order collaborative signals of items for learning high-quality user and item representations. In this paper, we propose a new model, called Hierarchy-Aware Knowledge Gated Network (HAKG), to tackle the aforementioned problems. Technically, we model users and items (that are captured by a user-item graph), as well as entities and relations (that are captured …
Cross-Lingual Transfer Learning For Statistical Type Inference, Zhiming Li, Xiaofei Xie, Haoliang Li, Zhengzi Xu, Yi Li, Yang Liu
Cross-Lingual Transfer Learning For Statistical Type Inference, Zhiming Li, Xiaofei Xie, Haoliang Li, Zhengzi Xu, Yi Li, Yang Liu
Research Collection School Of Computing and Information Systems
Hitherto statistical type inference systems rely thoroughly on supervised learning approaches, which require laborious manual effort to collect and label large amounts of data. Most Turing-complete imperative languages share similar control- and data-flow structures, which make it possible to transfer knowledge learned from one language to another. In this paper, we propose a cross-lingual transfer learning framework, Plato, for statistical type inference, which allows us to leverage prior knowledge learned from the labeled dataset of one language and transfer it to the others, e.g., Python to JavaScript, Java to JavaScript, etc. Plato is powered by a novel kernelized attention mechanism …
Structured And Natural Responses Co-Generation For Conversational Search, Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua
Structured And Natural Responses Co-Generation For Conversational Search, Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Generating fluent and informative natural responses while maintaining representative internal states for search optimization is critical for conversational search systems. Existing approaches either 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses directly in an end-to-end manner. Both kinds of approaches have shortcomings. The former suffers from error accumulation while the semantic associations between structured acts and natural responses are confined in single direction. The latter emphasizes generating natural responses but fails to predict structured acts. Therefore, we propose a neural co-generation model that generates the two concurrently. The key …
What Makes The Story Forward?: Inferring Commonsense Explanations As Prompts For Future Event Generation, Li Lin, Yixin Cao, Lifu Huang, Shu Ang Li, Xuming Hu, Lijie Wen, Jianmin Wang
What Makes The Story Forward?: Inferring Commonsense Explanations As Prompts For Future Event Generation, Li Lin, Yixin Cao, Lifu Huang, Shu Ang Li, Xuming Hu, Lijie Wen, Jianmin Wang
Research Collection School Of Computing and Information Systems
Prediction over event sequences is critical for many real-world applications in Information Retrieval and Natural Language Processing. Future Event Generation (FEG) is a challenging task in event sequence prediction because it requires not only fluent text generation but also commonsense reasoning to maintain the logical coherence of the entire event story. In this paper, we propose a novel explainable FEG framework, Coep. It highlights and integrates two types of event knowledge, sequential knowledge of direct event-event relations and inferential knowledge that reflects the intermediate character psychology between events, such as intents, causes, reactions, which intrinsically pushes the story forward. To …
On Measuring Network Robustness For Weighted Networks, Jianbing Zheng, Ming Gao, Ee-Peng Lim, David Lo, Cheqing Jin, Aoying Zhou
On Measuring Network Robustness For Weighted Networks, Jianbing Zheng, Ming Gao, Ee-Peng Lim, David Lo, Cheqing Jin, Aoying Zhou
Research Collection School Of Computing and Information Systems
Network robustness measures how well network structure is strong and healthy when it is under attack, such as vertices joining and leaving. It has been widely used in many applications, such as information diffusion, disease transmission, and network security. However, existing metrics, including node connectivity, edge connectivity, and graph expansion, can be suboptimal for measuring network robustness since they are inefficient to be computed and cannot directly apply to the weighted networks or disconnected networks. In this paper, we define the RR-energy as a new robustness measurement for weighted networks based on the method of spectral analysis. RR-energy can cope …
Harnessing Confidence For Report Aggregation In Crowdsourcing Environments, Hadeel Alhosaini, Xianzhi Wang, Lina Yao, Zhong Yang, Farookh Hussain, Ee-Peng Lim
Harnessing Confidence For Report Aggregation In Crowdsourcing Environments, Hadeel Alhosaini, Xianzhi Wang, Lina Yao, Zhong Yang, Farookh Hussain, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Crowdsourcing is an effective means of accomplishing human intelligence tasks by leveraging the collective wisdom of crowds. Given reports of various accuracy degrees from workers, it is important to make wise use of these reports to derive accurate task results. Intuitively, a task result derived from a sufficient number of reports bears lower uncertainty, and higher uncertainty otherwise. Existing report aggregation research, however, has largely neglected the above uncertainty issue. In this regard, we propose a novel report aggregation framework that defines and incorporates a new confidence measure to quantify the uncertainty associated with tasks and workers, thereby enhancing result …
Early Rumor Detection Using Neural Hawkes Process With A New Benchmark Dataset, Fengzhu Zeng, Wei Gao
Early Rumor Detection Using Neural Hawkes Process With A New Benchmark Dataset, Fengzhu Zeng, Wei Gao
Research Collection School Of Computing and Information Systems
Little attention has been paid on EArly Rumor Detection (EARD), and EARD performance was evaluated inappropriately on a few datasets where the actual early-stage information is largely missing. To reverse such situation, we construct BEARD, a new Benchmark dataset for EARD, based on claims from fact-checking websites by trying to gather as many early relevant posts as possible. We also propose HEARD, a novel model based on neural Hawkes process for EARD, which can guide a generic rumor detection model to make timely, accurate and stable predictions. Experiments show that HEARD achieves effective EARD performance on two commonly used general …
Cosm2ic: Optimizing Real-Time Multi-Modal Instruction Comprehension, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Minh Anh Tuan Tran, Archan Misra
Cosm2ic: Optimizing Real-Time Multi-Modal Instruction Comprehension, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Minh Anh Tuan Tran, Archan Misra
Research Collection School Of Computing and Information Systems
Supporting real-time, on-device execution of multi-modal referring instruction comprehension models is an important challenge to be tackled in embodied Human-Robot Interaction. However, state-of-the-art deep learning models are resource-intensive and unsuitable for real-time execution on embedded devices. While model compression can achieve a reduction in computational resources up to a certain point, further optimizations result in a severe drop in accuracy. To minimize this loss in accuracy, we propose the COSM2IC framework, with a lightweight Task Complexity Predictor, that uses multiple sensor inputs to assess the instructional complexity and thereby dynamically switch between a set of models of varying computational intensity …
Test Mimicry To Assess The Exploitability Of Library Vulnerabilities, Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo
Test Mimicry To Assess The Exploitability Of Library Vulnerabilities, Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo
Research Collection School Of Computing and Information Systems
Modern software engineering projects often depend on open-source software libraries, rendering them vulnerable to potential security issues in these libraries. Developers of client projects have to stay alert of security threats in the software dependencies. While there are existing tools that allow developers to assess if a library vulnerability is reachable from a project, they face limitations. Call graphonly approaches may produce false alarms as the client project may not use the vulnerable code in a way that triggers the vulnerability, while test generation-based approaches faces difficulties in overcoming the intrinsic complexity of exploiting a vulnerability, where extensive domain knowledge …
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang
A Mean-Field Markov Decision Process Model For Spatial Temporal Subsidies In Ride-Sourcing Markets, Zheng Zhu, Jintao Ke, Hai Wang
Research Collection School Of Computing and Information Systems
Ride-sourcing services are increasingly popular because of their ability to accommodate on-demand travel needs. A critical issue faced by ride-sourcing platforms is the supply-demand imbalance, as a result of which drivers may spend substantial time on idle cruising and picking up remote passengers. Some platforms attempt to mitigate the imbalance by providing relocation guidance for idle drivers who may have their own self-relocation strategies and decline to follow the suggestions. Platforms then seek to induce drivers to system-desirable locations by offering them subsidies. This paper proposes a mean-field Markov decision process (MF-MDP) model to depict the dynamics in ride-sourcing markets …
3pc: Three Point Compressors For Communication-Efficient Distributed Training And A Better Theory For Lazy Aggregation, Peter Richtarik, Igor Sokolov, Ilyas Fatkhullin, Elnur Gasanov, Zhize Li, Eduard Gorbunov
3pc: Three Point Compressors For Communication-Efficient Distributed Training And A Better Theory For Lazy Aggregation, Peter Richtarik, Igor Sokolov, Ilyas Fatkhullin, Elnur Gasanov, Zhize Li, Eduard Gorbunov
Research Collection School Of Computing and Information Systems
We propose and study a new class of gradient communication mechanisms for communication-efficient training -- three point compressors (3PC) -- as well as efficient distributed nonconvex optimization algorithms that can take advantage of them. Unlike most established approaches, which rely on a static compressor choice (e.g., Top-$K$), our class allows the compressors to {\em evolve} throughout the training process, with the aim of improving the theoretical communication complexity and practical efficiency of the underlying methods. We show that our general approach can recover the recently proposed state-of-the-art error feedback mechanism EF21 (Richt\'arik et al., 2021) and its theoretical properties as …
Identifying Legal And Ethical Values In Ai, Keng Siau, Fiona Nah, Chunyan Ding, Fiona Fui-Hoon Nah
Identifying Legal And Ethical Values In Ai, Keng Siau, Fiona Nah, Chunyan Ding, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Artificial intelligence (AI) applications in health care, education, finance, mining, communications, and arts have brought about rapid and dramatic advances in these fields (Hyder et al., 2019). The rapidly expanding potential of AI in the economy and society has raised a set of legal and ethical issues (Wang and Siau, 2019; Siau and Wang, 2020). In-depth research into the ethical and legal aspects of AI to enable policymakers to introduce effective legislation and regulate AI development and applications is needed. This research uses a systematic qualitative research methodology, Value-Focused Thinking (VFT) (Keeney, 1996; Sheng et al., 2007), to identify the …
Development Of The Implementation Of Iot Monitoring System Based On Node-Red Technology, Anvar Kabulov, Inomjon Yarashov, Salamat Mirzataev
Development Of The Implementation Of Iot Monitoring System Based On Node-Red Technology, Anvar Kabulov, Inomjon Yarashov, Salamat Mirzataev
Karakalpak Scientific Journal
This article describes how to design and implement a process for storing environmental information in a database using the Internet of Things. The problems that need to be solved with the help of this IoT system are the growing demand for forecasts in the world, the demand of the world market for a new sustainable method of implementing the digitization environment through the Internet of Things. The design was implemented using Arduino, Node-Red and sensors, selected when choosing a component based on the required parameters and sent to the database for monitoring and processing. A study of previous work and …
Empirical Assessment Of Big Data Technology Adoption Factors For Organizations With Data Storage Systems, Ahmad B. Alnafoosi
Empirical Assessment Of Big Data Technology Adoption Factors For Organizations With Data Storage Systems, Ahmad B. Alnafoosi
College of Computing and Digital Media Dissertations
Many organizations have on-premises data storage systems. Data storage systems are evolving in multiple ways. One way is the adoption of Big Data. Big Data is a data storage system with the ability to analyze large volumes, velocity, and a variety of data. Per the Economist, data is now the most valuable resource (Parkins, 2017). Big Data holds the promise of unlocking a substantial value of data stored. Yet many organizations are not implementing Big Data. There is a need to identify key factors affecting adoption for such organizations. The literature review revealed multiple gaps in studied adoption factors (un-studied …
Real-Time Data Analytics For Monitoring Electricity Consumption Using Iot Technology, Waheed Muhammad Sanya, Gaurav Bajpai, Omar Haji Kombo, Evariste Twahirwa
Real-Time Data Analytics For Monitoring Electricity Consumption Using Iot Technology, Waheed Muhammad Sanya, Gaurav Bajpai, Omar Haji Kombo, Evariste Twahirwa
Tanzania Journal of Engineering and Technology (TJET)
Rising electricity bills as a result of climate variability and new home electrical and electronic appliances are becoming a major source of concern for most end users. Consumers are typically unaware of their household electricity consumption patterns and the costs associated with them, making proper planning and budgeting difficult. Monitoring and controlling energy consumption on appliances can reduce energy costs for end-users. The Internet of Things (IoT) has the potential to provide remote monitoring and control of devices via automated monitoring and control. In this study, we propose an IoT-enabled system for monitoring and controlling energy consumption in homes to …
Group-Based Data Offloading Techniques Assisted By D2d Communication In 5g Mobile Network, Juma S Ally
Group-Based Data Offloading Techniques Assisted By D2d Communication In 5g Mobile Network, Juma S Ally
Tanzania Journal of Engineering and Technology (TJET)
Machine type communication devices proposed as one of the substantial data collections in the 5G of wireless networks. However, the existing mobile communication network is not designed to handle massive access from the MTC devices instead of human type communication. In this context, we propose the device-to-device communication assisted a mobile terminal (smartphone) on data computing, focusing on data generated from a correlated source of machine type communication devices. We consider the scenario that the MTC devices after collecting the data will transmit to a smartphone for computing. With the limitation of computing resources at the smartphone, some data are …
Digital Skills And Self-Employment Among Graduates Of Technical Higher Education Institutions In Tanzania, Charles Raphael
Digital Skills And Self-Employment Among Graduates Of Technical Higher Education Institutions In Tanzania, Charles Raphael
Tanzania Journal of Engineering and Technology (TJET)
Digital skills are the driving forces for innovative, inclusive and sustainable growth through innovations and digitalization which in turn stimulate job creation, alleviate poverty, reducing inequality, facilitating the delivery of goods and services. However, large number of graduates is shown to be weak in digital skills in the industry hence affect their employability including self-employment. Recently, the Technical Higher Education Institutions (THEIs) took some initiatives to instill the digital skills to their respective students. This study therefore assessed the level of competence of digital skills among graduates following the initiatives taken by the THEIs and their influence on self-employment. It …
Implementation Of Digital Transformation In The Technical Higher Education Institutions In Tanzania, Charles Raphael
Implementation Of Digital Transformation In The Technical Higher Education Institutions In Tanzania, Charles Raphael
Tanzania Journal of Engineering and Technology (TJET)
Digital transformation has been prioritized recently in this era of fourth industrial revolution by various organizations for maintaining strong competitive advantage, especially in the fourth industrial revolution. The higher education institutions must likewise adopt and implement digital transformation to enrich their students with the knowledge, experience and the skills they need for a very different future. Technical higher education institutions are inevitable in the given transformation. However, very little is known regarding adoption of digital transformation in the given institutions. This study therefore examined the level of adoption of digital services in the technical higher education institutions in Tanzania. It …
Efficient And Simple Heuristic Algorithm For Portfolio Optimization Collether John, Collether John
Efficient And Simple Heuristic Algorithm For Portfolio Optimization Collether John, Collether John
Tanzania Journal of Engineering and Technology (TJET)
Markowitz model considers what is termed as standard portfolio optimization. The portfolio optimization problem is a problem which based on asset allocation and diversification for maximum return with minimum risk. Thus, the standard portfolio optimization problem happens when the constraints considered are budget and no-short selling. In reality however, portfolio optimization has realistic constraints to be incorporated such as holding sizes, cardinality and transaction cost. When realistic constraints are added into portfolio optimization problem, it becomes too complex to be solved by standard optimization methods which in this case turns to be an extended portfolio optimization problem. Markowitz solution and …
Analyzing The Influence Of Smart-Device Visual Features, Viewing Distance And Content Factors On Video Streaming Qoe, Alex Frank Mongi
Analyzing The Influence Of Smart-Device Visual Features, Viewing Distance And Content Factors On Video Streaming Qoe, Alex Frank Mongi
Tanzania Journal of Engineering and Technology (TJET)
Quality of experience (QoE) over wireless networks has attracted attention from industry and academia due to an increase in video streaming applications. Several researchers have attempted to understand the factors affecting QoE and design appropriate quality control strategies. Normally, video streaming is initiated by a user who accesses video content over a network using a smart device that may be held at various viewing distances. Each aforementioned factor has the potential to affect QoE. However, several studies explore the behavior of wireless networks on video streaming QoE. To understand the effects of other factors on QoE, this paper investigates the …
Cyber Security Challenges, Its Emerging Trends On Latest Information And Communication Technology And Cyber Crime In Mobile Money Transaction Services, Hakeem J. Pallangyo
Cyber Security Challenges, Its Emerging Trends On Latest Information And Communication Technology And Cyber Crime In Mobile Money Transaction Services, Hakeem J. Pallangyo
Tanzania Journal of Engineering and Technology (TJET)
This paper investigates the challenges emerging trends on latest Information and Communication Technology and cybercrime in mobile money transaction services in Tanzania. The objective of this is to evaluate the challenges associated with this rapid growth in ICT and to determine factors influencing Cybersecurity readiness and Cybercrimes in mobile money transaction services. Cyber Security plays a significant role in the field of Information and Communication Technology especially on mobile money transaction services. The study recognizes the provision of mobile money services by both telecommunication companies and local banks, the fact is that whenever we think about the cyber security, the …
Data As A Service Ecosystem For Data-Driven Research, Leonardo Vieira
Data As A Service Ecosystem For Data-Driven Research, Leonardo Vieira
Theses and Dissertations
For the last two decades, the cloud computing ecosystems has become a major defining force for America, because of their unique economic, social and national importance. These ecosystems have now taken their place alongside the nation’s other infrastructure such as the food/agricultural, energy healthcare, and roads/highways. Scientists, engineers, and researchers over the same period have experienced a tremendous growth in the need for resources to that support assorted research. Cloud computing enables these communities to undertake wide-ranging research efforts, while requiring no maintenance, management or significant invest of local resources. The genius of this project examines how create on-ramps for …
A Large-Scale Sentiment Analysis Of Tweets Pertaining To The 2020 Us Presidential Election, Rao Hamza Ali, Gabriela Pinto, Evelyn Lawrie, Erik J. Linstead
A Large-Scale Sentiment Analysis Of Tweets Pertaining To The 2020 Us Presidential Election, Rao Hamza Ali, Gabriela Pinto, Evelyn Lawrie, Erik J. Linstead
Engineering Faculty Articles and Research
We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user accounts in our database that were later deleted or suspended from Twitter. This approach allows us to observe the sentiment held for each presidential candidate across various groups of users and tweets: accessible tweets and accounts, deleted tweets and accounts, and suspended or inaccessible tweets and accounts. We compare the sentiment scores calculated for these groups and provide key insights into the …
Steps Towards Digital Transformation In The Pharmaceutical Manufacturing Landscape Knowledge-Enabled Technology Transfer, Anne Greene Professor, Martin Lipa Dr
Steps Towards Digital Transformation In The Pharmaceutical Manufacturing Landscape Knowledge-Enabled Technology Transfer, Anne Greene Professor, Martin Lipa Dr
Level 3
No abstract provided.
Using Graph Theoretical Methods And Traceroute To Visually Represent Hidden Networks, Jordan M. Sahs
Using Graph Theoretical Methods And Traceroute To Visually Represent Hidden Networks, Jordan M. Sahs
UNO Student Research and Creative Activity Fair
Within the scope of a Wide Area Network (WAN), a large geographical communication network in which a collection of networking devices communicate data to each other, an example being the spanning communication network, known as the Internet, around continents. Within WANs exists a collection of Routers that transfer network packets to other devices. An issue pertinent to WANs is their immeasurable size and density, as we are not sure of the amount, or the scope, of all the devices that exists within the network. By tracing the routes and transits of data that traverses within the WAN, we can identify …
Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill
Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill
Computer Science Faculty Research & Creative Works
In federated scheduling of parallel real-time tasks on multiprocessor systems, high-utilization tasks are allocated dedicated processors on which they execute exclusively. Several methods exist for allocating a sufficient number of processors to guarantee that each task meets its deadline. In this paper, we propose two new strategies for allocating unit-speed cores to tasks with integer workload and deadline values. The first method can be performed in constant time for each high-utilization task, given the task's total workload, critical-path length, and deadline. The second method exploits the DAG structure of high-utilization tasks, providing a potentially better schedule in pseudo-polynomial time. We …
A Survey On Visual Analysis Of Massive Open Online Courses (Mooc) Data [大型开放式在线课程(Mooc)数据可视分析综述], Zhiguang Zhou, Saqing Wang, Yuhua Liu, Yong Wang, Yigang Wang
A Survey On Visual Analysis Of Massive Open Online Courses (Mooc) Data [大型开放式在线课程(Mooc)数据可视分析综述], Zhiguang Zhou, Saqing Wang, Yuhua Liu, Yong Wang, Yigang Wang
Research Collection School Of Computing and Information Systems
Massive open online courses(MOOC)are free online courses that provide educational resources to users.In this paper,related works are summarized from the following perspectives:data types of MOOC,MOOC data visualization,and visual analysis applications of MOOC data.First,MOOC data is categorized into four types,including text data,video data,topological data,spatio-temporal data,and their concepts and applications are introduced.Then,the common visualization methods of different data types are discussed.Furthermore,the major applications of visual analytics approaches in MOOC data analysis are summarized,including online course learning,online tests and exams,online forum interaction and so on.Finally,the challenges and future work on visual analytics of MOOC data are discussed and concluded.
Class Re-Activation Maps For Weakly-Supervised Semantic Segmentation, Zhaozheng Chen, Tan Wang, Xiongwei Wu, Xian-Sheng Hua, Hanwang Zhang, Qianru Sun
Class Re-Activation Maps For Weakly-Supervised Semantic Segmentation, Zhaozheng Chen, Tan Wang, Xiongwei Wu, Xian-Sheng Hua, Hanwang Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
Extracting class activation maps (CAM) is arguably the most standard step of generating pseudo masks for weakly supervised semantic segmentation (WSSS). Yet, we find that the crux of the unsatisfactory pseudo masks is the binary cross-entropy loss (BCE) widely used in CAM. Specifically, due to the sum-over-class pooling nature of BCE, each pixel in CAM may be responsive to multiple classes co-occurring in the same receptive field. To this end, we introduce an embarrassingly simple yet surprisingly effective method: Reactivating the converged CAM with BCE by using softmax crossentropy loss (SCE), dubbed ReCAM. Given an image, we use CAM to …