- Managing large collections of movies and series efficiently requires powerful data structures and fast search algorithms.
- This project implements a self-adjusting Splay Tree and a Compressed Trie to optimize data management and retrieval of movies and series information.
- The system prioritizes frequently accessed content and enables fast prefix-based searches, making it ideal for streaming platforms, media libraries, and content recommendation engines.
- Splay Tree:
Self-adjusting binary search tree that moves frequently accessed items closer to the root for faster subsequent access. - Compressed Trie:
Space-optimized prefix tree to enable fast prefix searches and autocompletion in movie and series names. - Hash Tables:
For quick filtering and sorting by various attributes (genre, language, country, rating). - Levenshtein Distance Algorithm:
For fuzzy matching in searches, allowing typo tolerance.
- Huffman Coding for Movie Names:
Implement Huffman tree-based compression to reduce storage space for movie names, with full encode/decode functionality. - Decision Tree for Movie Recommendations:
Store and query movies using a decision tree where each node represents a question (e.g., “Is rating above 8?”). Traverse branches to suggest movies based on user preferences.