Semantic similarity

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Related lectures (32)

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Latent Semantic Indexing: Concepts and Applications

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

Optimization in Machine Learning

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Neural Word Embeddings

Introduces neural word embeddings and dense vector representations for natural language processing.

Virtual Human Crowds: Behavior and Simulation

Explores virtual human crowds, object manipulation, visual attention, and crowd simulation techniques, including path planning and exposure therapy.

Text Models: Word Embeddings and Topic Models

Explores word embeddings, topic models, Word2vec, Bayesian Networks, and inference methods like Gibbs sampling.

Introduction to Natural Language Processing

Introduces the basics of Natural Language Processing, covering challenges, application domains, and linguistic processing levels.

Natural Language Generation: Evaluating Text Quality

Covers the evaluation methods for natural language generation systems, including metrics and human assessments of generated text quality.

Introduction to Information Retrieval

Introduces the basics of information retrieval, covering text-based retrieval, document features, similarity functions, and the difference between Boolean and ranked retrieval.

Semantic Web & Information Extraction

Explores Semantic Web, ontologies, information extraction, key phrases, named entities, and knowledge bases.

Contextual Representations: ELMO and BERT Overview

Covers contextual representations in NLP, focusing on ELMO and BERT architectures and their applications in various tasks.