Information Retrieval: Fagin's Algorithm

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Handling Text: Document Retrieval, Classification, Sentiment Analysis

Explores document retrieval, classification, sentiment analysis, TF-IDF matrices, nearest-neighbor methods, matrix factorization, regularization, LDA, contextualized word vectors, and BERT.

Information Retrieval: Indexing and Retrieval

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

Text Data Analysis: Basics and Techniques

Introduces the basics of text data analysis, covering document retrieval, classification, sentiment analysis, and topic detection using preprocessing techniques and machine learning models.

Text-Based Information Retrieval

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

Information Retrieval Basics: Overview and Text-Based Retrieval

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

Information Retrieval: Basics and Techniques

Introduces the basics of Information Retrieval, covering indexing, weighting schemes, cosine similarity, and query evaluation.

Vector Space Retrieval Exercise

Covers TF-IDF computation, document vectors, cosine similarity, and precision formulas.

Latent Semantic Indexing: Concepts and Applications

Explores Latent Semantic Indexing, a technique for mapping documents into a concept space for retrieval and classification.

Latent semantic indexing: inverted files

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

Latent Semantic Indexing: Concepts and Applications

Explores latent semantic indexing, vocabulary construction, document matrix creation, query transformation, and document retrieval using cosine similarity.