About this document
PAACDA: Graph-Based Data Corruption Detection by invaliduser163 is a document available to read on EtoBox.
The document presents a novel algorithm called PAACDA (Proximity-based Adamic-Adar Corruption Detection Algorithm) for detecting corrupted and anomalous data patterns using graph-based techniques. It compares the performance of PAACDA and its hybrid extension with traditional models, demonstrating superior accuracy rates of 94% and 100% respectively. The system is implemented via a Django web interface, allowing users to visualize results and apply multiple detection algorithms interactively.
- Author
- invaliduser163
- Language
- EN