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This Book is in Good Condition. Clean Copy With Light Amount of Wear. 100% Guaranteed. Summary: 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. Buchnummer des Verkäufers

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Inhaltsangabe: 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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Buchbeschreibung Morgan and Claypool Publishers, 2008. PAP. Buchzustand: New. New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Buchnummer des Verkäufers IQ-9781598291049

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Buchbeschreibung Morgan and Claypool Publishers, 2008. PAP. Buchzustand: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Buchnummer des Verkäufers CE-9781598291049

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Buchbeschreibung Buchzustand: New. Depending on your location, this item may ship from the US or UK. Buchnummer des Verkäufers 97815982910490000000

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Buchbeschreibung Morgan Claypool Publishers, United States, 2008. Paperback. Buchzustand: New. 232 x 188 mm. Language: English . Brand New Book. 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. Buchnummer des Verkäufers AAN9781598291049

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Buchbeschreibung Morgan Claypool Publishers, United States, 2008. Paperback. Buchzustand: New. 232 x 188 mm. Language: English . Brand New Book. 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. Buchnummer des Verkäufers AAN9781598291049

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Jerome R. Bellegarda, B.H. Juang
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Buchbeschreibung Morgan & Claypool Publishers. Paperback. Buchzustand: new. BRAND NEW, Latent Semantic Mapping: Principles and Applications, Jerome R. Bellegarda, B.H. Juang. Buchnummer des Verkäufers B9781598291049

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Buchbeschreibung Morgan Claypool Publishers, United States, 2008. Paperback. Buchzustand: New. 232 x 188 mm. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. 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. Buchnummer des Verkäufers LIE9781598291049

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Buchbeschreibung Morgan & Claypool Publishers, 2008. Paperback. Buchzustand: NEW. 9781598291049 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Buchnummer des Verkäufers HTANDREE01045286

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Buchbeschreibung Morgan & Claypool, 2007. Paperback. Buchzustand: Brand New. 101 pages. 9.00x7.50x0.25 inches. In Stock. Buchnummer des Verkäufers __1598291041

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