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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 ...
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;
Combining categories was a problem for extensional semantics, where the semantics of a word such as red is to be defined as the set of objects having this property. This does not apply as well to modifiers such as small; a small mouse is very different from a small elephant. These combinations pose a lesser problem in terms of prototype theory.
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.
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 ...
A concept search (or conceptual search) is an automated information retrieval method that is used to search electronically stored unstructured text (for example, digital archives, email, scientific literature, etc.) for information that is conceptually similar to the information provided in a search query.
Out of these experiments, they observed that people respond faster when (1) statements are true, (2) nouns are members of smaller categories, (3) items are "typical" or commonly associated with the category (also called prototypes), and (4) items are primed by a similar item previously given (University of Alaska Anchorage, n.d.). In the latter ...
The semantic similarity relationships of the SSN represent several of the general relationship types of the standard Semantic network, reducing the complexity of the (normally, very large) network for calculations of semantics. SSNs define relation types as templates (and taxonomy of relations) for semantic similarity attributes that are common ...