Concept

Web query

Related lectures (11)

Explores vector space retrieval, covering computation, examples, limitations of boolean retrieval, and query weights.

Explores query expansion methods, user relevance feedback, Rocchio algorithm, and practical considerations in expanding queries.

Explores practical relevance feedback in probabilistic retrieval and query optimization.

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

Explores term-offset indices in inverted files and relevance feedback solutions.

Covers query engines, shared work systems, and data processing optimization strategies.

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

Covers the implementation of a basic search engine using word embeddings and cosine similarity.

Covers text retrieval tasks with document ranking and re-ranking, using a large corpus for evaluation.

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

Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.