Analysis on Complete Works of Swami Vivekananda

Fri, 08 Dec 2023 00:00:00 +0000

This project aims to apply the Flajolet-Martin Algorithm to estimate the cardinality of unique elements in the entire collection of Swami Vivekananda’s complete works. The Flajolet-Martin Algorithm is a probabilistic method commonly used for large-scale data sets, providing an efficient way to estimate the number of distinct elements without needing to store them explicitly.

Objectives

Implement the Flajolet-Martin Algorithm in a scalable manner suitable for processing the extensive corpus of Swami Vivekananda’s works.
Develop a robust data processing pipeline to handle the text data and generate the necessary input for the algorithm.
Fine-tune the algorithm parameters and validate its accuracy against known cardinality benchmarks to ensure reliable estimates.

Technologies and Tools

Programming Language: Python
Data Processing: Pandas, Spark
Flajolet-Martin Algorithm Implementation: Custom Python code
Version Control: Git
Documentation: Markdown

Expected Outcomes

A scalable and efficient implementation of the Flajolet-Martin Algorithm tailored for the unique characteristics of Swami Vivekananda’s complete works.
Accurate cardinality estimates for the distinct elements in the dataset.
Documentation detailing the project methodology, implementation details, and findings.

Future Work

Potential future enhancements could include exploring other probabilistic algorithms for cardinality estimation, optimizing the algorithm further, or extending the analysis to specific subsets of Swami Vivekananda’s works.

Data Mining on Ujjwal Chowdhury

Analysis on Complete Works of Swami Vivekananda

Objectives

Technologies and Tools

Expected Outcomes

Future Work