Results 1 - 10 of 12,403

Probabilistic Histograms for Probabilistic Data

by Graham Cormode, Minos Garofalakis, et al. , 2009
"... There is a growing realization that modern database management systems (DBMSs) must be able to manage data that contains uncertainties that are represented in the form of probabilistic relations. Consequently, the design of each core DBMS component must be revisited in the presence of uncertain and ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
There is a growing realization that modern database management systems (DBMSs) must be able to manage data that contains uncertainties that are represented in the form of probabilistic relations. Consequently, the design of each core DBMS component must be revisited in the presence of uncertain

Probabilistic Principal Component Analysis

by Michael E. Tipping, Chris M. Bishop - JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B , 1999
"... Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of paramet ..."
Abstract - Cited by 709 (5 self) - Add to MetaCart
Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation

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

Learning probabilistic relational models

by Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer - In IJCAI , 1999
"... A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much ..."
Abstract - Cited by 613 (30 self) - Add to MetaCart
A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much

Probabilistic Latent Semantic Analysis

by Thomas Hofmann - In Proc. of Uncertainty in Artificial Intelligence, UAI’99 , 1999
"... Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two--mode and co-occurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Sema ..."
Abstract - Cited by 771 (9 self) - Add to MetaCart
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two--mode and co-occurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent

Efficient top-k query evaluation on probabilistic data

by Christopher Ré, Nilesh Dalvi, Dan Suciu - in ICDE , 2007
"... Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Probabilistic databases can model such data naturally, but SQL query evaluation on probabilistic databases is difficult: previous approaches have either restricted the SQL queries, or computed ..."
Abstract - Cited by 182 (32 self) - Add to MetaCart
Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Probabilistic databases can model such data naturally, but SQL query evaluation on probabilistic databases is difficult: previous approaches have either restricted the SQL queries, or computed

Probabilistic data exchange

by Ronald Fagin, Benny Kimelfeld, Phokion G. Kolaitis - In Proc. ICDT , 2010
"... The work reported here lays the foundations of data exchange in the presence of probabilistic data. This requires rethinking the very basic concepts of traditional data exchange, such as solution, universal solution, and the certain answers of target queries. We develop a framework for data exchange ..."
Abstract - Cited by 40 (7 self) - Add to MetaCart
The work reported here lays the foundations of data exchange in the presence of probabilistic data. This requires rethinking the very basic concepts of traditional data exchange, such as solution, universal solution, and the certain answers of target queries. We develop a framework for data

Probabilistic Data Programming with ENFrame

by Dan Olteanu , Sebastiaan J Van Schaik
"... Abstract This paper overviews ENFrame, a programming framework for probabilistic data. In addition to relational query processing supported via an existing probabilistic database management system, ENFrame allows programming with loops, assignments, conditionals, list comprehension, and aggregates ..."
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Abstract This paper overviews ENFrame, a programming framework for probabilistic data. In addition to relational query processing supported via an existing probabilistic database management system, ENFrame allows programming with loops, assignments, conditionals, list comprehension, and aggregates

Duplicate Detection in Probabilistic Data

by Fabian Panse, Maurice Van Keulen, Ander De Keijzer, Norbert Ritter
"... Abstract — Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches hav ..."
Abstract - Cited by 5 (2 self) - Add to MetaCart
Abstract — Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches

Mixtures of Probabilistic Principal Component Analysers

by Michael E. Tipping, Christopher M. Bishop , 1998
"... Principal component analysis (PCA) is one of the most popular techniques for processing, compressing and visualising data, although its effectiveness is limited by its global linearity. While nonlinear variants of PCA have been proposed, an alternative paradigm is to capture data complexity by a com ..."
Abstract - Cited by 532 (6 self) - Add to MetaCart
Principal component analysis (PCA) is one of the most popular techniques for processing, compressing and visualising data, although its effectiveness is limited by its global linearity. While nonlinear variants of PCA have been proposed, an alternative paradigm is to capture data complexity by a
Results 1 - 10 of 12,403