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Latent Semantic Mapping - Jerome R. Bellegarda 9781598291049
€ 18,75
Ophalen of Verzenden
90sinds 14 okt. '24, 13:24
Kenmerken
ConditieZo goed als nieuw
TypeOverige wetenschappen
Jaar (oorspr.)2007
AuteurJerome R. Bellegarda
Beschrijving
Latent Semantic Mapping - Jerome R. Bellegarda 9781598291049
Principles and Applications.
Latent semantic mapping (LSM) is a generalization of latent semantic analysis (LSA), a paradigm originally developed to capture hidden word patterns in a text document corpus. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents. It operates under the assumption that there is some latent semantic structure in the data, which is partially obscured by the randomness of word choice with respect to retrieval.
Algebraic and/or statistical techniques are brought to bear to estimate this structure and get rid of the obscuring noise. This results in a parsimonious continuous parameter description of words and documents, which then replaces the original parameterization in indexing and retrieval.
This approach exhibits three main characteristics: Discrete entities (words and documents) are mapped onto a continuous vector space This mapping is determined by global correlation patterns; and Dimensionality reduction is an integral part of the process. Such fairly generic properties are advantageous in a variety of different contexts, which motivates a broader interpretation of the underlying paradigm. The outcome (LSM) is a data-driven framework for modeling meaningful global relationships implicit in large volumes of (not necessarily textual) data. This monograph gives a general overview of the framework, and underscores the multifaceted benefits it can bring to a number of problems in natural language understanding and spoken language processing.
It concludes with a discussion of the inherent tradeoffs associated with the approach, and some perspectives on its general applicability to data-driven information extraction.
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- Titel: Latent Semantic Mapping / Schrijver(s): Jerome R. Bellegarda / ISBN Nr: 9781598291049 / Taal: Engels / Aantal Pagina's: 101 / Versie: Paperback / 1e Druk 2007 / Genre: Taalwetenschap / Bijzonderheden: Minimale gebruikssporen aan de cover/kaft, verder is het boek in uitstekende conditie. / Intern-nr: 603
Principles and Applications.
Latent semantic mapping (LSM) is a generalization of latent semantic analysis (LSA), a paradigm originally developed to capture hidden word patterns in a text document corpus. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents. It operates under the assumption that there is some latent semantic structure in the data, which is partially obscured by the randomness of word choice with respect to retrieval.
Algebraic and/or statistical techniques are brought to bear to estimate this structure and get rid of the obscuring noise. This results in a parsimonious continuous parameter description of words and documents, which then replaces the original parameterization in indexing and retrieval.
This approach exhibits three main characteristics: Discrete entities (words and documents) are mapped onto a continuous vector space This mapping is determined by global correlation patterns; and Dimensionality reduction is an integral part of the process. Such fairly generic properties are advantageous in a variety of different contexts, which motivates a broader interpretation of the underlying paradigm. The outcome (LSM) is a data-driven framework for modeling meaningful global relationships implicit in large volumes of (not necessarily textual) data. This monograph gives a general overview of the framework, and underscores the multifaceted benefits it can bring to a number of problems in natural language understanding and spoken language processing.
It concludes with a discussion of the inherent tradeoffs associated with the approach, and some perspectives on its general applicability to data-driven information extraction.
Door veel problemen bij DHL ben ik genoodzaakt te verzenden met Postnl
KIJK OOK NAAR MIJN ANDERE AANBOD IN BOEKEN.
Advertentienummer: m2178195063
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