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Web Information Systems Engineering WISE 2024: 25th International Conference, Doha, Qatar, December 25, 2024, Proceedings, Part V [Mīkstie vāki]

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  • Formāts: Paperback / softback, 515 pages, height x width: 235x155 mm, 96 Illustrations, color; 41 Illustrations, black and white; XXII, 515 p. 137 illus., 96 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 15440
  • Izdošanas datums: 27-Nov-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 981960575X
  • ISBN-13: 9789819605750
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Web Information Systems Engineering WISE 2024: 25th International Conference, Doha, Qatar, December 25, 2024, Proceedings, Part VPalielināt
  • Formāts: Paperback / softback, 515 pages, height x width: 235x155 mm, 96 Illustrations, color; 41 Illustrations, black and white; XXII, 515 p. 137 illus., 96 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 15440
  • Izdošanas datums: 27-Nov-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 981960575X
  • ISBN-13: 9789819605750
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819605750.html
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This five-volume set LNCS 15436 -15440 constitutes the proceedings of the 25th International Conference on Web Information Systems Engineering, WISE 2024, held in Doha, Qatar, in December 2024.





The 110 full papers and 55 short papers were presented in these proceedings were carefully reviewed and selected from 368 submissions. The papers have been organized in the following topical sections as follows:





Part I : Information Retrieval and Text Processing; Text and Sentiment Analysis; Data Analysis and Optimisation; Query Processing and Information Extraction; Knowledge and Data Management.





Part II: Social Media and News Analysis; Graph Machine Learning on Web and Social; Trustworthy Machine Learning; and Graph Data Management.





Part III: Recommendation Systems; Web Systems and Architectures; and Humans and Web Security.





Part IV: Learning and Optimization; Large Language Models and their Applications; and AI Applications.





Part V: Security, Privacy and Trust; Online Safety and Wellbeing through AI; and Web Technologies.
.- Security, Privacy and Trust.



.- Privacy-Preserving k-core Decomposition For Graphs.



.- Anomaly Detection in Log Streams based on Time-Contextual Models.



.- Enhancing Open-Set Recognition with Global Feature Representation.



.- Dynamic-Parameter Genetic Algorithm for Multi-objective Privacy-Preserving
Trajectory Data Publishing.



.- A Graph-Based Approach for Software Functionality Classification on the
Web.



.- FUD-LDP: Fully User Driven Local Differential Privacy.



.- A Privacy-Preserving Encryption framework for Big data analysis.



.- Location nearest neighbor query scheme in edge computing based on
differential privacy.



.- Open Research Challenges for Private Advertising Systems under Local
Differential Privacy.



.- Industry-Specific Vulnerability Assessment.



.- Blockchain-Driven Medical Data Shamir Threshold Encryption with
Attribute-Based Access Control Scheme.



.- Smart Contracts Vulnerability Detection Using Transformers.



.- Weibo-FA: A Benchmark Dataset for Fake Account Detection in Weibo
Platform.



.- More Than Just a Random Number Generator! Unveiling the Security and
Privacy Risks of Mobile OTP Authenticator Apps.



.- Synthetic Data Generation: Limits and Improvement of Avatar Data.



.- A Lightweight Detection of Sequential Patterns in File System Events
During Ransomware Attacks.



.- Detection and Mitigation of Backdoor Attacks on x-Apps.



.- Cohesive database neighborhoods for differential privacy: mapping
relational databases to RDF.



.- i-Right: Identifying and classifying GDPR user rights in fitness tracker
and smart home privacy policie.



.- AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity
Recognition Dataset.



.- R-CONV: An Analytical Approach for Efficient Data Reconstruction via
Convolutional Gradients.



.- Privacy Preserving Behavioral Anomaly Detection in Dynamic Graphs for Card
Transactions.



.- Online Safety and Wellbeing through AI.



.- DisCo-FEND: Social Context Veracity Dissemination Consistency-Guided Case
Reasoning for Few-Shot Fake News Detection.



.- NLWM: a Robust, Efficient and High-quality Watermark for Large Language
Models.



.- Improving the Robustness of Rumor Detection Models with Metadata-Augmented
Evasive Rumor Datasets.



.- Rumor Alteration for Improving Rumor Generation.



.- Generating Effective Answers to Peoples Everyday Cybersecurity Questions:
An Initial Study.



.- Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent
LLMs.



.- Did You Tell a Deadly Lie? Evaluating Large Language Models for Health
Misinformation Identification.



.- Native vs Non-Native Language Prompting: A Comparative Analysis.



.- DisFact: Fact-Checking Disaster Claims.



.- Web Technologies.



.- Multi-Perspective Conformance Checking For Email-driven Processes.



.- Progressive Server-Side Rendering with Suspendable Web Templates.



.- HMSC-LLMs: A Hierarchical Multi-Agent Service Composition Method Based on
Large Language Models.



.- Enhancing Web Spam Detection through a Blockchain-Enabled Crowdsourcing
Mechanism.



.- WNSWE: Web-based Network Simulator for Web Engineering Education.