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检索条件"任意字段=12th International Conference on Database Systems for Advanced Applications"

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25th international conference on database systems for advanced applications, DASFAA 2020

25th International Conference on Database Systems for Advanc...

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25th international conference on database systems for advanced applications, DASFAA 2020

ISBN: (纸本)9783030594091

the proceedings contain 161 papers. the special focus in this conference is on database systems for advanced applications. the topics include: Progressive term frequency analysis on large text collections;learning a cost-effective strategy on incomplete medical data;bus frequency optimization: when waiting time matters in user satisfaction;incorporating boundary and category feature for nested named entity recognition;incorporating concept information into term weighting schemes for topic models;how to generate reasonable texts with controlled attributes;keep you from leaving: churn prediction in online games;point-of-interest demand discovery using semantic trajectories;learning from heterogeneous student behaviors for multiple prediction tasks;a general early-stopping module for crowdsourced ranking;mrmrp: multi-source review-based model for rating prediction;guaranteed delivery of advertisements to targeted audiences under deduplication and frequency capping constraints;efficient parallel cycle search in large graphs;cross-graph representation learning for unsupervised graph alignment;predicting hospital readmission using graph representation learning based on patient and disease bipartite graph;aspect-level attributed network embedding via variational graph neural networks;semantic region retrieval from spatial rdf data;re-gcn: relation enhanced graph convolutional network for entity alignment in heterogeneous knowledge graphs;efficient graph hierarchical decomposition with user engagement and tie strength;role-oriented graph auto-encoder guided by structural information;dynamic graph repartitioning: from single vertex to vertex group;discovering real-time reachable area using trajectory connections;modeling heterogeneous edges to represent networks with graph auto-encoder;aot: pushing the efficiency boundary of main-memory triangle listing;efficient closeness centrality computation for dynamic graphs;efficient closest community search over large graphs.

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26th international conference on database systems for advanced applications, DASFAA 2021

26th International Conference on Database Systems for Advanc...

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26th international conference on database systems for advanced applications, DASFAA 2021

ISBN: (纸本)9783030731991

the proceedings contain 152 papers. the special focus in this conference is on database systems for advanced applications. the topics include: Unpaired Multimodal Neural Machine Translation via Reinforcement Learning;multimodal Named Entity Recognition with Image Attributes and Image Knowledge;multi-task Neural Shared Structure Search: A Study Based on Text Mining;a Semi-structured Data Classification Model with Integrating Tag Sequence and Ngram;inferring Deterministic Regular Expression with Unorder and Counting;MACROBERT: Maximizing Certified Region of BERT to Adversarial Word Substitutions;a Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification;neural Demographic Prediction in Social Media with Deep Multi-view Multi-task Learning;An Interactive NL2SQL Approach with Reuse Strategy;automated Context-Aware Phrase Mining from Text Corpora;consistency- and Inconsistency-Aware Multi-view Subspace Clustering;discovering Collective Converging Groups of Large Scale Moving Objects in Road Networks;efficient Mining of Outlying Sequential Behavior Patterns;clustering Mixed-Type Data with Correlation-Preserving Embedding;beyond Matching: Modeling Two-Sided Multi-Behavioral Sequences for Dynamic Person-Job Fit;a Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks;AE-UPCP: Seeking Potential Membership Users by Audience Expansion Combining User Preference with Consumption Pattern;self Separation and Misseparation Impact Minimization for Open-Set Domain Adaptation;Partial Modal Conditioned GANs for Multi-modal Multi-label Learning with Arbitrary Modal-Missing;cross-Domain Error Minimization for Unsupervised Domain Adaptation;keyword-Aware Encoder for Abstractive Text Summarization;unsupervised Domain Adaptation with Unified Joint Distribution Alignment;relation-Aware Alignment Attention Network for Multi-view Multi-label Learning;BIRL: Bidirectional-Interaction Reinforcement Learning Framework for Jo

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25th international conference on database systems for advanced applications, DASFAA 2020

25th International Conference on Database Systems for Advanc...

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25th international conference on database systems for advanced applications, DASFAA 2020

ISBN: (纸本)9783030594183

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26th international conference on database systems for advanced applications, DASFAA 2021

26th International Conference on Database Systems for Advanc...

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26th international conference on database systems for advanced applications, DASFAA 2021

ISBN: (纸本)9783030731960

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26th international conference on database systems for advanced applications, DASFAA 2021

26th International Conference on Database Systems for Advanc...

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26th international conference on database systems for advanced applications, DASFAA 2021

ISBN: (纸本)9783030731939

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Collaborative Defense Strategies: AI, ML, and Cybersecurity: A Comprehensive Study 12th

Collaborative Defense Strategies: AI, ML, and Cybersecurity:...

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12th international conference on Frontiers of Intelligent Computing: theory and applications, FICTA 2024

作者： Borah, Samarjeet Dhabliya, Dharmesh Dhage, Prashant Shukla, Jyoti Rai, Sumit Kumar Bhattacharya, Saurabh Department of Computer Applications Sikkim Manipal Institute of Technology Sikkim Manipal University Sikkim India Department of Information Technology Vishwakarma Institute of Information Technology Maharashtra Pune India Nagpur Campus Pune India Computer Science and Engineering Arya College of Engineering Jaipur India Department of Mechanical Engineering Dr. D. Y. Patil Institute of Technology Maharashtra Pimpri Pune India Assistant Professor SCSE Galgotias University Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819601462

In the fast-changing field of cybersecurity, the rise of advanced threats requires new and creative defense strategies. this study thoroughly examines collaborative defense strategies, focusing on the utilization of artificial intelligence (AI) and machine learning (ML) techniques. the study aims to evaluate the effectiveness of five prominent machine learning algorithms (random forest, support vector machine (SVM), gradient boosting, isolation forest, and one-class SVM) in the field of cybersecurity. the assessment is carried out utilizing the NSL-KDD dataset, which is a standard in the industry. the study commences by investigating the origins of collaborative defense, analyzing its historical development and fundamental principles. the text explains the importance of AI in collaborative defense, highlighting machine learning algorithms and natural language processing as essential elements. the study explores the uses of artificial intelligence, specifically in identifying, averting, and reacting to threats. A substantial part of the research focuses on evaluating the effectiveness of the five chosen machine learning algorithms. the evaluation includes predictive analysis to forecast cyber threats and proactive defense measures. the study examines how machine learning improves the sharing of threat intelligence by facilitating real-time information exchange between collaborating entities. the challenges and considerations related to incorporating AI and ML into cybersecurity are examined, emphasizing ethical implications, bias, fairness, transparency, and accountability. Case studies and success stories from real-world scenarios showcase examples of successful collaborative defense strategies applied in various industries and sectors. the study evaluates and contrasts the random forest, SVM, gradient boosting, isolation forest, and one-class SVM algorithms based on performance metrics like accuracy, precision, recall, and F1 score, utilizing the NSL-KDD dataset. T

关键词： Adversarial machine learning

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An Important and Successful Multi-image Stereography-Based Secret Communication System for Military applications 12th

An Important and Successful Multi-image Stereography-Based S...

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12th international conference on Frontiers of Intelligent Computing: theory and applications, FICTA 2024

作者： Ravi, C.N. Suhasini, T.S. Narasimharao, Jonnadula Mahendar, A. Amruthraj, B. Venkateswara Reddy, R. Department of Computer Science and Engineering CMR Engineering College Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of Computer Science and Engineering CMR Technical Campus Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of Computer Science and Engineering CMR College of Engineering and Technology Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601387

A significant factor in data transfer is computer science. Security considerations make it difficult to transmit sensitive data or have conversations via the internet. Typically, cryptography is used to transmit text-based underground messages and conceal in sequence. these days, there are numerous methods for concealing information on any media. A technique like this is steganography. the creation of a covert communication system that uses multi-image steganography will enable safe communication among the dispatcher and the recipient free from hacker intervention. Image steganography is the main technique for information hiding. It involves integrating the cipher text within a picture called the cover picture that is very difficult for strangers to view through an unassisted eye. Within a cover image, the concealed data may take the shape of any kind of text, picture, music, or even video. the secret code is split up into several pieces and etched into several cover images, according to the conceptual notion of multi-image steganography. thus, in order to make it extremely difficult for the hackers to hide the data, we suggested two image steganography concepts. In order to create a safe and protected system, this learning suggest by means of the advanced Encryption Standard (AES) approach of cryptography with the Least Significant Bit (LSB) method of steganography. Here, a symmetric key—which is used by both the sender and the recipient to encrypt and decode data—is used by both parties. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Stereo image processing

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30th international conference on database and Expert systems applications, DEXA 2019

30th International Conference on Database and Expert Systems...

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30th international conference on database and Expert systems applications, DEXA 2019

ISBN: (纸本)9783030276140

the proceedings contain 66 papers. the special focus in this conference is on database and Expert systems applications. the topics include: A Probabilistic Algorithm to Predict Missing Facts from Knowledge Graphs;semantic Oppositeness Embedding Using an Autoencoder-Based Learning Model;COMET: A Contextualized Molecule-Based Matching Technique;differentially Private Non-parametric Machine Learning as a Service;PURE: A Privacy Aware Rule-Based Framework over Knowledge Graphs;FFT-2PCA: A New Feature Extraction Method for Data-Based Fault Detection;A DaQL to Monitor Data Quality in Machine Learning applications;automated Detection and Monitoring of advanced Data Quality Rules;effect of Imprecise Data Income-Flow Variability on Harvest Stability: A Quantile-Based Approach;rainfall Estimation from Traffic Cameras;fairness-Enhancing Interventions in Stream Classification;early Turnover Prediction of New Restaurant Employees from their Attendance Records and Attributes;an Efficient Premiumness and Utility-Based Itemset Placement Scheme for Retail Stores;data Lakes: Trends and Perspectives;an Efficient Greedy Algorithm for Sequence Recommendation;discovering Diverse Popular Paths Using Transactional Modeling and Pattern Mining;representative Sample Extraction from Web Data Streams;LogLInc: LoG Queries of Linked Open Data Investigator for Cube Design;handling the Information Backlog for Data Warehouse Development;ontario: Federated Query Processing Against a Semantic Data Lake;towards Identifying De-anonymisation Risks in Distributed Health Data Silos;a Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition;named Entity Recognition in Local Intent Web Search Queries;database Processing-in-Memory: A Vision;Context-Aware GANs for Image Generation from Multimodal Queries;An Attribute-Based Fine-Grained Access Control Mechanism for HBase.

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Concept and Considerations for the Development of an Information database for Efficient international Freight Transport

Concept and Considerations for the Development of an Informa...

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international conference on Computational Cybernetics (ICCC)

作者： Petra Opitz Tamás Haidegger Enikö Nagy John von Neumann Faculty of Informatics Óbuda University Budapest Hungary University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary School of Computing Queen's University Kingston ON John von Neumann Faculty of Informatics Óbuda University Antal Bejczy Center for Intelligent Robotics Budapest Hungary

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

international freight transport is a growing market and a crucial component of the global economy, enabling the seamless flow of goods across regions and supporting global trade. However, the industry faces significant challenges, particularly in road transport orchestration, due to the increasing complexity of operations and the demand for real-time decision-making. this study sketched the algorithmic and programming framework to address these challenges by presenting an optimized database architecture designed to improve decision support systems for freight transport. the proposed system architecture may leverage the flexibility and scalability of NoSQL databases to manage large, semi-structured datasets in the future, while REST APIs enable seamless integration and real-time data manipulation. To enhance usability and transparency, the system incorporates advanced data visualization tools, allowing stakeholders to derive actionable insights and improve operational efficiency. By focusing on areas such as real-time tracking, sustainability, and process optimization, this work not only addresses current operational needs but also provides a robust foundation for future developments, including advanced analytics and mobile application integration. this contribution supports the logistics industry's shift toward more adaptive, efficient, and sustainable transport solutions.

关键词： Industries NoSQL databases Data visualization systems architecture Real-time systems Visual databases Usability Sustainable development Optimization Logistics

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Schema Transformation from RDBMS to NoSQL Using Hypergraph 12th

Schema Transformation from RDBMS to NoSQL Using Hypergraph

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12th international conference on Big Data Analytics, BDA 2024

作者： Baranwal, Richa Ranjan, Himanshu Bansal, Neha Sachdeva, Shelly National Institute of Technology Delhi India Bennett University Greater Noida India

ISBN: (纸本)9783031861925

the current study explores methodologies (like TLD, CLDA, and Kuzera) and the challenges of migrating schemas from RDBMS to NoSQL document stores. these challenges include data misinterpretations, increased response time due to costly joins, poor data locality, and unalignment of schema design with query patterns. To encounter these challenges, the proposed model presents a schema transformation approach from a Relational database Management System (RDBMS) to NoSQL using Hypergraph. the existing methodologies use a graph data model that cannot represent complex relationships, whereas the Hypergraph provides accurate group-wise complex relationships. the paper contains four phases: input, data modeling decision, transformation, and output phase. the input phase contains relational tables and workload queries. the data modeling decision phase incorporates the calculation of normalized weight followed by the decision to select the type of data model (embedding or referencing). the role of the transformation phase is to generate a collection of tables that reflect the table hierarchy, utilized to create the NoSQL schema. the transformation phase comprises hypergraph generation, matrix transformation, and matrix enumeration. the hypergraph generation phase includes query mapping, inverse query mapping, and hypergraph generation. the matrix transformation phase covers the creation of the incidence matrix and square matrix, which are used for matrix enumeration. the incidence matrix shows which queries are related to which tables. the square matrix represents the frequency and strength of these relationships. Matrix enumeration is used to finalize the grouping of related tables based on query patterns, optimizing the schema for better performance by reducing the need for complex joins. In the output phase, the final NoSQL schema is created by using the results of the preceding phases (data modeling decision phase and transformation phase). An experiment has been conducted

关键词： Relational database systems

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