Latent semantic mapping
Encyclopedia
Latent semantic mapping is a data-driven framework to model globally meaningful relationships implicit in large volumes of (often textual) data. It is a generalization of latent semantic analysis
. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents.
LSM was derived from earlier work on latent semantic analysis. There are 3 main characteristics of latent semantic analysis: Discrete entities, usually in the form of words and documents, are mapped onto continuous vectors, the mapping involves a form of global correlation pattern, and dimensionality reduction is an important aspect of the analysis process. These constitute generic properties, and have been identified as potentially useful in a variety of different contexts. This usefulness has encouraged great interest in LSM. The intended product of latent semantic mapping, is a data-driven framework for modeling relationships in large volumes of data.
Mac OS X v10.5
includes a framework
implementing latent semantic mapping.
Latent semantic analysis
Latent semantic analysis is a technique in natural language processing, in particular in vectorial 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. LSA assumes that words that are close...
. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents.
LSM was derived from earlier work on latent semantic analysis. There are 3 main characteristics of latent semantic analysis: Discrete entities, usually in the form of words and documents, are mapped onto continuous vectors, the mapping involves a form of global correlation pattern, and dimensionality reduction is an important aspect of the analysis process. These constitute generic properties, and have been identified as potentially useful in a variety of different contexts. This usefulness has encouraged great interest in LSM. The intended product of latent semantic mapping, is a data-driven framework for modeling relationships in large volumes of data.
Mac OS X v10.5
Mac OS X v10.5
Mac OS X Leopard is the sixth major release of Mac OS X, Apple's desktop and server operating system for Macintosh computers. Leopard was released on 26 October 2007 as the successor of Tiger , and is available in two variants: a desktop version suitable for personal computers, and a...
includes a framework
Software framework
In computer programming, a software framework is an abstraction in which software providing generic functionality can be selectively changed by user code, thus providing application specific software...
implementing latent semantic mapping.