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Semantic similarity is a metric defined over a set ... between multi-word terms, long pre-processing times ... annotation prediction and similarity search".
Distributional semantic models have been applied successfully to the following tasks: finding semantic similarity between words and multi-word expressions; word clustering based on semantic similarity; automatic creation of thesauri and bilingual dictionaries; word sense disambiguation; expanding search requests using synonyms and associations;
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
In recent years, sentence embedding has seen a growing level of interest due to its applications in natural language queryable knowledge bases through the usage of vector indexing for semantic search. LangChain for instance utilizes sentence transformers for purposes of indexing documents. In particular, an indexing is generated by generating ...
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...
Statistical semantics focuses on the meanings of common words and the relations between common words, unlike text mining, which tends to focus on whole documents, document collections, or named entities (names of people, places, and organizations).
In psycholinguistics, semantic processing is the stage of language processing that occurs after one hears a word and encodes its meaning: the mind relates the word to other words with similar meanings. Once a word is perceived, it is placed in a context mentally that allows for a deeper processing. Therefore, semantic processing produces memory ...