Indexing and Distributed Retrieval

Related lectures (25)

Page 1 of 3

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

Introduces the basics of information retrieval, covering text-based and Boolean retrieval, vector space retrieval, and similarity computation.

Explores constructing an inverted file for information retrieval indexing and the map-reduce programming model.

Introduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.

Covers the basics of information retrieval, including text-based retrieval and indexing techniques.

Explores text retrieval systems, inverted files, addressing granularity, and access structures in information retrieval.

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

Covers the basic concepts of text-based information retrieval and how documents are indexed and retrieved based on user queries.

Covers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.

Covers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.