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  2. WordNet - Wikipedia

    en.wikipedia.org/wiki/WordNet

    WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into synsets with short definitions and usage examples. It can thus be seen as a combination and extension of a dictionary and thesaurus.

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The word with embeddings most similar to the topic vector might be assigned as the topic's title, whereas far away word embeddings may be considered unrelated. As opposed to other topic models such as LDA , top2vec provides canonical ‘distance’ metrics between two topics, or between a topic and another embeddings (word, document, or otherwise).

  4. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...

  5. Lexical chain - Wikipedia

    en.wikipedia.org/wiki/Lexical_chain

    The semantic relationship is obtained through WordNet, which works a ground truth to indicate which lexical structure connects two words (e.g., hypernyms, hyponyms, meronyms). If a word without any semantic affinity with the current chain presents itself, a new lexical chain is initialized.

  6. Explicit semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Explicit_semantic_analysis

    Mathematically, this list is an N-dimensional vector of word-document scores, where a document not containing the query word has score zero. To compute the relatedness of two words, one compares the vectors (say u and v) by computing the cosine similarity,

  7. Similarity search - Wikipedia

    en.wikipedia.org/wiki/Similarity_search

    Similarity search is the most general term used for a range of mechanisms which share the principle of searching (typically very large) spaces of objects where the only available comparator is the similarity between any pair of objects. This is becoming increasingly important in an age of large information repositories where the objects ...

  8. Ontology learning - Wikipedia

    en.wikipedia.org/wiki/Ontology_learning

    Ontology learning (ontology extraction,ontology augmentation generation, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between the concepts that these terms represent from a corpus of natural language text, and encoding them with an ontology language for easy ...

  9. Semantic similarity network - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity_network

    The latest evolution in Artificial Intelligence (like ChatGPT, based on Large language model), relay strongly on evolutionary computation, the next level will be to include semantic unification (like in the Semantic Networks and this Semantic similarity network) to extend the current models with more powerful understanding tools.