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Document Indexing with a Concept Hierarchy

by Computación Y Sistemas, Er Sidorov, Grigori Guzmán-arenas, Índice Documentos, Jerarquía Conceptos, Er Gelbukh, Grigori Sidorov, Adolfo Guzmán-arenas , 2004
"... Document indexing with a concept hierarchy ..."
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Document indexing with a concept hierarchy

Managing Gigabytes: Compressing and Indexing Documents and Images - Errata

by I. H. Witten, A. Moffat, T. C. Bell , 1996
"... > ! "GZip" page 64, Table 2.5, line "progp": "43,379" ! "49,379" page 68, Table 2.6: "Mbyte/sec" ! "Mbyte/min" twice in the body of the table, and in the caption "Mbyte/second" ! "Mbyte/minute" page 70, para 4, line ..."
Abstract - Cited by 978 (48 self) - Add to MetaCart
;a such a" ! "such a" page 98, line 6: "shows that in fact none is an answer to this query" ! "shows that only document 2 is an answer to this query" page 106, para 3, line 9: "the bitstring in Figure 3.7b" ! "the bitstring in Figure 3.7c" page 107

Probabilistic Latent Semantic Indexing

by Thomas Hofmann , 1999
"... Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized ..."
Abstract - Cited by 1225 (10 self) - Add to MetaCart
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized

Indexing by latent semantic analysis

by Scott Deerwester, Susan T. Dumais, George W. Furnas, Thomas K. Landauer, Richard Harshman - JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE , 1990
"... A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries. The p ..."
Abstract - Cited by 3779 (35 self) - Add to MetaCart
A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries

A Language Modeling Approach to Information Retrieval

by Jay M. Ponte, W. Bruce Croft , 1998
"... Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model. This sugg ..."
Abstract - Cited by 1154 (42 self) - Add to MetaCart
Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model

Computer Aided Document Indexing System

by Mladen Kolar, Igor Vukmirović, Bojana Dalbelo Bašić, Jan Šnajder
"... Abstract. An enormous number of documents is being produced that have to be stored, searched and accessed. Document indexing represents an efficient way to tackle this problem. Contributing to the document indexing process, we developed the Computer Aided Document Indexing System (CADIS) that applie ..."
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Abstract. An enormous number of documents is being produced that have to be stored, searched and accessed. Document indexing represents an efficient way to tackle this problem. Contributing to the document indexing process, we developed the Computer Aided Document Indexing System (CADIS

A Probabilistic Learning Approach for Document Indexing

by Norbert Fuhr, Chris Buckley - ACM TRANSACTIONS ON INFORMATION SYSTEMS , 1991
"... We describe a method for probabilistic document indexing using relevance feedback data that has been collected from a set of queries. Our approach is based on three new concepts: (1) Abstraction from specific terms and documents, which overcomes the restriction of limited relevance information fo ..."
Abstract - Cited by 103 (13 self) - Add to MetaCart
We describe a method for probabilistic document indexing using relevance feedback data that has been collected from a set of queries. Our approach is based on three new concepts: (1) Abstraction from specific terms and documents, which overcomes the restriction of limited relevance information

Documentation Index 2

by Paul Heald, Noor Tabbalat, Veasna Chim
"... parking21 to bring about a new era of parking in the District. ..."
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parking21 to bring about a new era of parking in the District.

BIDDING AND CONTRACT DOCUMENTS INDEX

by Robert J. Sturtcman-architect, Thompson Engineering, Richard J. Moss , 2007
"... The technical material and data contained in the specifications were prepared under the supervision and direction of the undersigned, whose seal as a Professional Architect, licensed to practice in the State of New Mexico, is affixed below. ___________________________________ _ _________ ..."
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The technical material and data contained in the specifications were prepared under the supervision and direction of the undersigned, whose seal as a Professional Architect, licensed to practice in the State of New Mexico, is affixed below. ___________________________________ _ _________

Unsupervised Learning by Probabilistic Latent Semantic Analysis

by Thomas Hofmann - Machine Learning , 2001
"... Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co-occurren ..."
Abstract - Cited by 618 (4 self) - Add to MetaCart
results for different types of text and linguistic data collections and discusses an application in automated document indexing. The experiments indicate substantial and consistent improvements of the probabilistic method over standard Latent Semantic Analysis.
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