Final Program

EAI BDTA 2022

12th  EAI International Conference on Big Data Technologies and Applications

Day 1: Saturday 10 December 2022Time ZoneEET, Cairo, Egypt

10:00 – 10:15 Opening Ceremony
An opening message by the conference organizers.

10:15 – 10:30 Welcome Message by EAI

10:30 – 11:30 Keynote by Dr. Ayman Taha – Senior Researcher, Technological University Dublin, Ireland

Title: Feature Engineering for Big Data Applications: An Insurance case study

11:30 – 11:45 Coffee/ Tea Break

11:45 – 13:05 Session 1: Learning Analysis and Blockchain Technologies

11:45 – 12:05 A Comparative study for anonymizing datasets with multiple sensitive attribute and multiple records

12:05 – 12:25 A Proposed Keyword-Based Feature Extraction Approach for Single/Multi-Labeling Classification of User Requirements for Egyptian Mobile Apps Arabic Slang Reviews

12:25 – 12:45 A Proposed Framework for Cloud Immunization Information System: Challenges and Opportunities

12:45 – 13:05 The Role of Block Chain Technology in Reducing Corruption within the Local Governance in Egypt

13:05 – 13:20 Coffee/ Tea Break

13:20 – 14:40 Session 2: Machine Learning and Big Data applications

13:20 – 13:40 Using Requirements Clustering to Discover Dependent Requirements for Hidden Impact Analysis

13:40 – 14:00 A Proposed Virtual Learning Model based on Statistical Analysis of Educational Data of Egypt

14:00 – 14:20 Diagnosis Hepatitis B Using Machine and Deep Learning: Survey

14:20 – 14:40 Using Grasshopper Optimization in Big Data

14:40 – 15:00 Lunch break

Day 2: Sunday 11 December 2022Time ZoneEET, Cairo, Egypt

11:00 – 12:20 Session 3: Deep Learning application and Bio-inspired Optimization

11:00 – 11:20 Detecting Fake News Spreaders on Twitter Through Follower Networks

11:20 – 11:40 NODDLE: Node2vec based deep learning model for link prediction

11:40 – 12:00 Hybrid Coral Reef Optimization Algorithm Employed Local Search Technique for Job Shop Scheduling Problems

12:00 – 12:20 Efficient Human Activity Recognition based on Grouped Representations of Multimodal Wearable Data

12:20 – 12:30 Coffee/ Tea Break

12:30 – 17:20 Session 4: Semi-supervised Learning and IoT applications

12:30 – 12:50 A Semi-supervised Learning Application for Hand Posture Classification

12:50 – 13:10 A data brokering architecture to guarantee nonfunctional requirements in IoT applications

13:10 – 13:30 Explore the relationship between procedural score feedback and subsequent time allocation and learning outcomes of learners in a MOOC

13:30 – 13:50 DoS attacks detection in the network of drones: An efficient Decision Tree-based method

13:50 – 14:10 Closing Remarks + Best Paper Award