Vol. 3 — 2019

Edinburgh Journal of Natural Language Processing and AI

We are pleased to present the latest volume of the Edinburgh Journal of Natural Language Processing and AI (EJNLPAI). This issue highlights the latest developments in NLP, machine translation, and intelligent language systems. With contributions from global scholars, this edition bridges theoretical discourse and practical innovation in computational linguistics, deep learning for language understanding, and AI-driven human-computer interaction. EJNLPAI remains committed to fostering interdisciplinary research that reflects the evolving intersection of AI and human language. Each article published herein contributes to redefining how machines process, understand, and generate human language.

Articles

10 papers
01

AI-Powered Impact Analysis for Multi-Site Schema Evolution

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PP. 1-36
02

Environment-Aware Failure Propagation Simulator Using Reinforcement Agents

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PP. 132-163
03

Graph-Neural Threat Detection at the Hypervisor Layer

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PP. 100-131
04

Multi-Agent Negotiation for Adaptive Capacity Scaling in Post-Merger Payment Networks

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PP. 68-99
05

Privacy-Preserving Federated Learning for Reward-Redemption Optimization

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PP. 37-67
06

Development of AI-Driven Digital Pathology Platforms for Cancer Diagnosis: Utilizing Convolutional Neural Networks for Automated Image Analysis, Tumor Detection, and Prognostic Assessment

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PP. 164-199
07

Improving Multi- Agent AI Model Based Distributed Intrusion Detection Systems

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PP. 241-245
08

Utilizing AI for Personalized Nutritional Genomics: Developing Machine Learning Models for Diet Optimization Based on Genomic, Metabolic, and Microbiome Data

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PP. 200-240
09

Deep Learning Algorithms for Demand Forecasting and Inventory Optimization in Global Supply Chains

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PP. 246-282
10

Dynamic Pricing Strategies in E-Commerce: Leveraging Machine Learning for Real-Time Decision-Making

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PP. 283-320