Information Retrieval Indexing: Part 2

Related lectures (26)

Page 1 of 3

Covers indexing techniques, distributed retrieval algorithms, and challenges in large-scale web indexing.

Explores indexing techniques, inverted files, map-reduce algorithms, and top-k document retrieval methods in text retrieval systems.

Explores concurrent programming theory and practice, covering system models, cache coherence, and graph processing.

Covers graph processing with a focus on Oracle Labs PGX, discussing graph analytics, databases, algorithms, and distributed analytics challenges.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Explores the ubiquity of graphs in modern data and analytics, focusing on the shift in organizations' perception of graph technologies.

Explores scaling pattern matching in large graphs and optimizing query execution under memory constraints using work-sharing and batch processing.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores indexing techniques, inverted files, map-reduce models, and trie usage for efficient information retrieval.

Explores learning from interconnected data using graphs, covering challenges, GNN design, research landscapes, and democratization of Graph ML.