This book constitutes the proceedings of the 10th International Conference on Big Data Analytics, BDA 2022, which took place in Hyderabad, India, in December 2022.
The 7 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The book also contains 4 keynote talks in full-paper length. The papers are organized in the following topical sections: Big Data Analytics: Vision and Perspectives; Data Science: Architectures; Data Science: Applications; Graph Analytics; Pattern Mining; Predictive Analytics in Agriculture.
Big Data Analytics: Vision and Perspectives.- Data Challenges and
Societal Impacts the case in favor of the Blueprint for an AI Bill of
Rights.- Big Data in Cognitive Neuroscience: Opportunities and
Challenges.- Data Science: Architectures.- A Novel Feature Selection Based
Text Classification using Multi-layer ELM.- ARCORE: Software Requirements
Dataset for Service Identification.- ARCORE: Software Requirements Dataset
for Service Identification.- Learning enhancement using Question-Answer
generation for e-book using contrastive fine-tuned T5.- Data Science:
Applications.- A Machine and Deep Learning Framework to Retain Customers
based on their Lifetime Value.- A Deep Learning based Approach to Automate
Clinical Coding of Electronic Health Records.- Determining the severity of
Dementia using ensemble learning.- Determining the severity of Dementia using
ensemble learning.- A distributed ensemble machine learning technique for
emotion classification from vocal cues.- Graph Analytics. -Drugomics:
Knowledge Graph & AI to Construct Physicians' Brain Digital Twin to Prevent
Drug Side-effects and Patient Harm.- Extremely Randomized Tree based
Sentiment Polarity Classification on Online Product Reviews.- Community
Detection in Large Directed Graphs.- Pattern Mining.- FastTIRP: Efficient
discovery of Time-Interval Related Patterns.- Discovering Top-K Periodic
Patterns in Temporal Databases.- Hui2Vec: Learning Transaction Embedding
Through High Utility Itemsets.- Predictive Analytics in Agriculture.- A
Data-driven, Farmer-oriented Agricultural Crop Recommendation Engine
(ACRE).- Analyze the Impact of Weather Parameters for Crop Yield Prediction
using Deep Learning.- Analysis of Weather Condition based Reuse among Agromet
Advisory: A Validation Study.
