Lecture
Information Retrieval: Fagin's Algorithm
Related lectures (30)
Information retrieval: vector space
Covers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.
Latent semantic indexing: inverted files
Explores term-offset indices in inverted files and relevance feedback solutions.
Information Retrieval Basics
Introduces the basics of information retrieval, covering text-based and Boolean retrieval, vector space retrieval, and similarity computation.
Indexing and Distributed Retrieval
Explores indexing techniques, inverted files, map-reduce algorithms, and top-k document retrieval methods in text retrieval systems.
Vector Space Semantics (and Information Retrieval)
Explores the Vector Space model, Bag of Words, tf-idf, cosine similarity, Okapi BM25, and Precision and Recall in Information Retrieval.
Data Wrangling with Hadoop
Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Information Retrieval Basics
Introduces the basics of information retrieval, covering document representation, query expansion, and TF-IDF for document ranking.
Probabilistic Retrieval
Covers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.
Information Retrieval: Indexing and Retrieval
Covers indexing techniques, distributed retrieval algorithms, and challenges in large-scale web indexing.
Query Processing with Relational Operations
Covers query processing with relational operations, including query optimization and different join algorithms.