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Deep Bayesian Data Mining 20

Deep Bayesian Data Mining

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13th Annual ACM international conference on web Search and Data Mining (WSDM)

作者： Chien, Jen-Tzung Natl Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9781450368223

this tutorial addresses the fundamentals and advances in deep Bayesian mining and learning for natural language with ubiquitous applications ranging from speech recognition [7, 55] to document summarization [8], text classification [5, 75], text segmentation [18], information extraction [50], image caption generation [69, 72], sentence generation [25, 46], dialogue control [22, 76], sentiment classification, recommendation system, question answering [58] and machine translation [2], to name a few. Traditionally, "deep learning" is taken to be a learning process where the inference or optimization is based on the real-valued deterministic model. the "semantic structure" in words, sentences, entities, actions and documents drawn from a large vocabulary may not be well expressed or correctly optimized in mathematical logic or computer programs. the "distribution function" in discrete or continuous latent variable model for natural language may not be properly decomposed or estimated. this tutorial addresses the fundamentals of statistical models and neural networks, and focus on a series of advanced Bayesian models and deep models including hierarchical Dirichlet process [61], Chinese restaurant process [4], hierarchical Pitman-Yor process [60], Indian buffet process [35], recurrent neural network (RNN) [26, 41, 48, 65], long short-term memory, sequence-to-sequence model [59], variational auto-encoder (VAE) [44], generative adversarial network (GAN) [36], attention mechanism [27, 56], memory-augmented neural network [39, 58], skip neural network [6], temporal difference VAE [40], stochastic neural network [3, 47], stochastic temporal convolutional network [1], predictive state neural network [31], and policy neural network [49, 74]. Enhancing the prior/posterior representation is addressed [53, 62]. We present how these models are connected and why they work for a variety of applications on symbolic and complex patterns in natural language. the variational inference an

关键词： deep learning Bayesian learning data mining information retrieval natural language processing

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Predicting QoS for web Service Recommendations Based on Reputation and Location Clustering with Collaborative Filtering

Predicting QoS for Web Service Recommendations Based on Repu...

引用

Contemporary information technology and Mathematics (ICCITM), international conference on

作者： Muayad N. Abdullah Wesam S. Bhaya College of IT University of Babylon Babil IRAQ

ISBN: (纸本)9781665420334

Nowadays, numerous web services with equivalent functionality have become available on the Internet. the Quality of Service (QoS) for web services seems to have an essential role when it comes to selecting the best web services. However, evaluating the user-side efficiently in terms of quality of web services has become a critical research topic. Predicting the QoS values of web services and the credibility of the values published by different users are major challenges in this area. A commonly used technique to predict QoS values of web services is collaborative filtering (CF). To address these critical challenges, a personalized QoS predicting technique is proposed for web services which depends on the reputation and location-based CF approach. Firstly, a set of untrusted users is identified through the Dirichlet probability distribution on the basis of the user's reputation, followed by processing the unreliable data contributed by untrusted users. Secondly, the users are clustered based on their geographic information to improve the neighborhood similarity computation. Finally, the similarity weights of neighboring users are used to predict unknown QoS values in each cluster. It has been observed that the proposed model realized a more favorable performance in terms of accuracy and efficiency as compared to other existing approaches. According to the matrix densities from 10% to 90%, the measures of MAE and RMSE for the response time attribute range from 0.47 to 0.30 and from 1.26 to 0.95, respectively, and the measures of MAE and RMSE for the throughput attribute range from 15.64 to 7.58 and from 50.50 to 34.15, respectively.

关键词： web services Density measurement Collaborative filtering Quality of service Machine learning throughput Time measurement

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Access Control Design Based on User Role Type in Telemedicine System Using Ethereum Blockchain 21

Access Control Design Based on User Role Type in Telemedicin...

引用

Proceedings of the 7th international conference on Communication and information processing

作者： Muhammad Hamzah Diyanatul Husna Fransiskus Astha Ekadiyanto Ketut Purnama Afif Nurul Hidayati Mauridhi Hery Purnomo Supeno Mardi Susiki Nugroho Reza Fuad Rachmadi Ingrid Nurtanio Anak Agung Ratna Department of Electrical Engineering Universitas Indonesia Indonesia Department of Computer Engineering Sepuluh November Institute of Technology Indonesia Department of Dermatology and Venereology Airlangga University Indonesia Department of Informatics Hassanudin University Indonesia

ISBN: (纸本)9781450385190

To fulfill health as basic human needs, health care services technology is always improved but also must maintain security and privacy of the data due to huge amount of data is created and distributed. Telemedicine with telecommunication technology offers convenience and cheaper cost, but still is vulnerable to cyber attacks, making it a threat for patients’ data's privacy. One approach that can be used to secure the data is applying access control to the data. Immutable blockchain can helps to enforce access control so it cannot be violated. We propose a system which implements Ethereum for the blockchain and React web application for the interface of the system. Data management and the access control are provided through Ethereum smart contracts, and the access control requires different role-based permission to upload and access the patients’ data. the system works successfully with average time taken to verify the role is 1.8033 seconds per session. the privacy of the patients’ data is ensured because only the patients that are allowed to keep the ID of their own data.

关键词： Blockchain web Smart Contract Telemedicine User Role

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A Feature-Augmented Deep Learning Model for Extractive Summarization 7th

A Feature-Augmented Deep Learning Model for Extractive Summa...

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7th EAI international conference on Industrial Networks and Intelligent Systems, INISCOM 2021

作者： Anh, Bui thi Mai Trang, Nguyen thi thu Software Engineering Department School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9783030774233

Extractive text summarization can be seen as a classification task in which sentences from the document are labelled with either in-summary or not-in-summary. the most salient sentences (i.e., with highest ranking score) from the original document will be selected to generate the summary. Recent success of deep learning in the field of Natural language processing (NLP) has raised a trending research direction for text summarization task. Many neural models have been proposed in which applying recurrent neural network (rNN) for extractive summarization is also becoming increasingly popular. In this paper, we aim to improve the baseline sequence to sequence model proposed by Nallapati et al. by augmenting more sentence features so that the generated summary can benefit from potential features of the whole document. On one hand, the additional sentence-based features enrich the representation vector resulting from the sentence-level RNN of the baseline model. On the other hand, the relevant information from word-level will also be added to the final vector to increase the accuracy of the classification task. the experiment has been conducted for the DailyMail/CNN dataset to evaluate our proposed method and the state of the art works. the empirical results show that the proposed model with augmented features increases about 0.3-0.4 points of ROUGE-1 and ROUGE-2 in comparison with related works. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Recurrent neural networks

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PADI-web: An Event-Based Surveillance System for Detecting, Classifying and processing Online News 8th

PADI-web: An Event-Based Surveillance System for Detecting, ...

引用

8th language and technology conference - Challenges for Computer Science and Linguistics (LTC)

作者： Valentin, Sarah Arsevska, Elena Mercier, Alize Falala, Sylvain Rabatel, Julien Lancelot, Renaud Roche, Mathieu Univ Montpellier UMR TETIS AgroParisTech CIRADCNRSINRAE F-34398 Montpellier France Univ Montpellier UMR ASTRE CIRAD INRAE F-34398 Montpellier France CIRAD Montpellier France

ISBN: (纸本)9783030665272;9783030665265

the Platform for Automated Extraction of Animal Disease information from the web (PADI-web) is a multilingual text mining tool for automatic detection, classification, and extraction of disease outbreak information from online news articles. PADI-web currently monitors the web for nine animal infectious diseases and eight syndromes in five animal hosts. the classification module is based on a supervised machine learning approach to filter the relevant news with an overall accuracy of 0.94. the classification of relevant news between 5 topic categories (confirmed, suspected or unknown outbreak, preparedness and impact) obtained an overall accuracy of 0.75. In the first six months of its implementation (January-June 2016), PADI-web detected 73% of the outbreaks of African swine fever;20% of foot-and-mouth disease;13% of bluetongue, and 62% of highly pathogenic avian influenza. the information extraction module of PADI-web obtained F-scores of 0.80 for locations, 0.85 for dates, 0.95 for diseases, 0.95 for hosts, and 0.85 for case numbers. PADI-web allows complementary disease surveillance in the domain of animal health.

关键词： Epidemic intelligence Animal health web monitoring Text mining Classification information extraction

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An Extraction Model Based on RoBERTa-BiLSTM-CRF for Chinese Financial Event

An Extraction Model Based on RoBERTa-BiLSTM-CRF for Chinese ...

引用

IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Dagao Duan Wenwen Liu Zhongming Han School of International Economics and Management Beijing Technology and Business University Beijing China School of Computer Science and Engineering Beijing Technology and Business University Beijing China

ISBN: (纸本)9781665441506

Event Extraction is one of the important research tasks of information Extraction in Natural language processing. It tries to extract information from a large amount of chaotic data and presents information in a structural form. the existing Chinese event extraction methods have the inaccuracies of Chinese word segmentation, which will directly lead to incorrect identification of Chinese financial entities, affecting the accuracy of event element extraction. this paper takes Chinese financial event extraction as a sequence labeling task. It proposes an event extraction model based on PreTraining Model, Bidirectional Long-Short Term Memory Network, and Conditional Random Field. Additionally, this paper constructs the Chinese financial event dataset FinEE. At the same time, financial events are filtered from public dataset DuEE to construct dataset DuEE_Fin. As the experimental results show that the proposed Chinese financial event extraction model Roberta-BilSTM-CRF has improved accuracy, recall rate, and F1 score compared with existing models on FinEE and DuEE_Fin datasets.

关键词： Cloud computing Computational modeling conferences information retrieval Natural language processing Data mining Labeling

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Research on Infrared Sequential Image Generation Techniques in Pure Background

Research on Infrared Sequential Image Generation Techniques ...

引用

7th international conference on Communications, Signal processing, and Systems (CSPS)

作者： Ge, Changyun Zhang, Haibei Han, Ti Li, Jiaqi Zhao, Xiujie Lin, Baowei Yan, Shuhan Huang, Baoxin Dalian Neusoft Univ Informat Dept Elect Engn Dalian 116023 Liaoning Peoples R China Ali Beijing Peoples R China Dalian Neusoft Univ Informat Dept Foreign Language Dalian 116023 Liaoning Peoples R China

ISBN: (纸本)9789811365041;9789811365034

Infrared image generation technology is an important part of infrared target guidance simulation. this paper studies the method of environment modeling, introduces the method of constructing SNR model and the method of coordinate transformation. the infrared image sequence is generated by SNR, coordinate information, and projectile information. the infrared image generated has three different target models: sky, sea, and land. the background is pure, the target is clear, and the experiment shows that it is feasible.

关键词： Infrared image generation SNR Coordinate transformation

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Detection of Tunneling in DNS over HTTPS

Detection of Tunneling in DNS over HTTPS

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international conference on Signal processing and Communication (ICSC)

作者： Hrithik Jha Iishi Patel Gang Li Aswani Kumar Cherukuri Sumaiya thaseen Vellore Institute of Technology Vellore India Deakin University Melbourne Australia

ISBN: (纸本)9781665427401

Domain Name Service (DNS) enables users to query domain names which are then converted to IP addresses leading traffic to that specific website on the web. DNS over HTTPS (DoH) is a protocol for performing remote DNS resolution via the HTTP protocol. It enables increased user privacy and security by preventing eavesdropping and manipulation of DNS data by man-in-the-middle attacks. DoH helps keep the requests encrypted and minimizes the information exchanged during queries. Along with the added privacy and security advancements, DoH makes it harder to detect tunneling which can be used by malicious actors to transmit sensitive data out of the victim’s computer. DoH Tunneling enables these actors to insert malware or pass stolen information into DNS queries, creating a covert communication channel that bypasses most firewalls and results in sensitive data leakage. In this paper, we explore methods of data collection and detection of DoH tunneling using machine learning techniques based on the packet sizes and duration of requests.

关键词： Data privacy Protocols Firewalls (computing) Machine learning Tunneling Signal processing Data collection

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A Container-Based Edge Computing System for Smart Healthcare Applications 7th

A Container-Based Edge Computing System for Smart Healthcare...

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7th EAI international conference on Industrial Networks and Intelligent Systems, INISCOM 2021

作者： Le-Anh, Tuan Ngo-Van, Quan Vo-Huy, Phuong Huynh-Van, Dang Le-Trung, Quan UiTiOt Research Group Department of Computer Networks University of Information Technology Vietnam National University – Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030774233

Edge computing is evolving how data are processed and analyzed from a large figure of various Internet of things (IoT) devices globally. the rapid development of IoT, 5G, artificial intelligence (AI), and applications that require real-time computing capability steadily propel edge computing systems. In this paper, we propose a container-based edge computing system for smart healthcare applications. the smart care mobile and web-based applications aim to assist doctors or nurses with intelligent monitoring and caring for patients in the recovery phase in real-time. the proposed system’s design takes advantage of edge computing’s capabilities to timely deal with the patient’s facial emotion detection and heart disease diagnosis AI applications and a robust cloud computing infrastructure to centralize the patient’s data in the secure, scalable, and fault-tolerance database. Moving these AI applications to the edge outperforms cloud computing in processing time, energy efficiency, and bandwidth saving. Finally, implementing the AI applications on a lightweight container orchestration platform for management efficiency with high availability, scalability, and deployment automation. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Containers

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i-AEGIS-128: An Improved Authenticated Encryption Based on AEGIS-128

i-AEGIS-128: An Improved Authenticated Encryption Based on A...

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international conference on Optimization and Applications (ICOA)

作者： Muhammad Ghulam Ghouse Sapiee Jamel Muhammad Aamir Muhammad Zulqarnain Mustafa Mat Deris Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia College of Science and Engineering University of Derby United Kingdom Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia

ISBN: (纸本)9781665431156

Authenticated Encryption (AE) is the latest cryptographic algorithm standard introduced through CAESAR (Com-petition for Authenticated Encryption: Security, Applicability, and Robustness). AE schemes provide a process for simultaneously achieving the security goals of confidentiality and integrity assurance. the constructions of authentication encryption is secure and efficient to protect the modern electronic information systems. In this research paper, we proposed an Improved AEGIS-128 Algorithm (i-AEGIS-128) for improving the standard AEGIS-128 algorithm to enhance the performance in which quarter round-based AES (advanced Encryption Standard) is used for the encryption and decryption process. the proposed i-AEGIS-128 is based on an AEGIS-128 AES-round permutation modification for hardware implementation. the Results of i-AEGIS-128 on Intel(R)Core(TM) i7-3700 Processor running at 3.40 GHz speed with 16GB of RAM using C/C++ and HDL (Hardware Description language) languages and platforms to determine the encryption and decryption time, throughput processing unit memory during encryption and decryption. Finally we compared the efficiency and power analysis of the hardware. the i-AEGIS-128 algorithm relies on the use of ¼ AES-round in authentication encryption to reduce the area consumed during processing, perform fast encryption and decryption, use less power and provide the best efficiency.

关键词： Performance evaluation Power demand Authentication Random access memory throughput Hardware Robustness

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