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N-Poisson document modelling
1992
Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '92
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We believe that further research in using the n-Poisson distribution to model full text document collections will help in developing a comprehensive and useful statistical model for such collections. ...
Investigating
the
n-Poisson
properties
of non-
English
language
document
collections. ...
doi:10.1145/133160.133195
dblp:conf/sigir/Margulis92
fatcat:vjgglmmitnelzjhpaeoi6v6ghm
TSUNAMI THREAT EVALUATION BY HISTORICAL DOCUMENTS, NUMERICAL MODEL AND STOCHASTIC MODEL
1986
Coastal Engineering Proceedings
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An evaluation of local tsunami threat was studied first refering to the historical documents and the catalogs. ...
Secondly, an example of a numerical model of a finite difference method was discussed in relation to problems for reproducing the past local tsunamis and predicting a forthcoming tsunami. ...
using a stochastic model for an extended Poisson process. ...
doi:10.9753/icce.v20.194
fatcat:67u2to3lvralbga2c26acfr54a
Recurrent Coupled Topic Modeling over Sequential Documents
[article]
2021
arXiv
pre-print
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The abundant sequential documents such as online archival, social media and news feeds are streamingly updated, where each chunk of documents is incorporated with smoothly evolving yet dependent topics ...
A fully conjugate model is thus obtained to guarantee the effectiveness and efficiency of the inference technique. ...
One of the benchmark models learning the evolution of topics is the state space model, in which the V -dimensional topic at step evolves via ∼ N ( −1 , Σ) [9] or the linear form ∼ N ( −1 , Σ) [47] . ...
arXiv:2106.13732v1
fatcat:hbfxszcnevgfplgnxiiqfnturm
Hierarchical Dirichlet model for document classification
2005
Proceedings of the 22nd international conference on Machine learning - ICML '05
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documents into a given hierarchy. ...
We present a novel and simple hierarchical Dirichlet generative model for text corpora and derive an efficient algorithm for the estimation of model parameters and the unsupervised classification of text ...
We also note that for most generative models for document hierarchies the document length is assumed to be generated by a class-independent Poisson distribution. ...
doi:10.1145/1102351.1102468
dblp:conf/icml/VeeramachaneniSA05
fatcat:hbkemvqnevc4hjfuqi3pw2i2lu
Modèles de RI fondés sur l'information
2011
Document Numérique
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Nous introduisons ensuite une nouvelle famille de modèles probabilistes pour la RI, fondée sur la notion d'information. ...
Lorsque la loi de probabilité sous-jacente est capable de modéliser le phénomène de rafale, alors le modèle devient naturellement valide au sens des contraintes heuristiques. ...
Okapi, par exemple, suppose que les fréquences suivent un mélange de deux distributions de Poisson (2-Poisson), dans l'ensemble des documents pertinents et dans l'ensemble des documents non pertinents. ...
doi:10.3166/dn.14.2.103-123
fatcat:h7vwfgh54bgzthrt4p7cygoo4a
Medical documents classification using topic modeling
2020
Indonesian Journal of Electrical Engineering and Computer Science
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LDA topic modeling technique is applied to classify these documents into the previous mentioned topics. ...
Therefore, an automatic way to extract latent topics from these text documents is needed. Topic modeling is one of the techniques used to deal with this problem. ...
LDA proposed the following generative process [8] for each document w in a corpus D: 1) Choose the number of words N according to Poisson distribution. 2) Then choose a topic mixture for the document ...
doi:10.11591/ijeecs.v17.i3.pp1524-1530
fatcat:xzml44lljbf3dmeytnftiaubma
Modeling error of \begin{document}$ \alpha $\end{document}-models of turbulence on a two-dimensional torus
2017
Discrete and continuous dynamical systems. Series B
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The turbulence models we study belong to the class of Large Eddy Simulation models (LES), used to carry out numerical simulations of turbulent flows, that cannot be performed by the Direct Numerical Simulations ...
More specifically, we will consider the Leray-α, the simplified Bardina, and the modified Leray-α models. ...
Once the velocity is calculated, the pressures p and p α are solutions of the following Poisson equations −∆p = ∇ · ((u · ∇)u) and − ∆p α = ∇ · (N (u α )). ...
doi:10.3934/dcdsb.2020305
fatcat:i6bmf6mjgre5tm3txh4ts7faka
A Stochastic Model for Simple Document Processing
2019
International Journal of Information Technology and Computer Science
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Our simple document processing system derives from the general model described by MOUKELI and NEMBE. ...
It is about an adaptation of the said general model to determine in terms of metrics and performance, its behavior in the particular case of simple document processing. ...
Dynamic model of the system The dynamic model is used to describe the temporal behavior (evolution) of the system, which is modeled as N priority queues, and K document classes or document priority levels ...
doi:10.5815/ijitcs.2019.07.06
fatcat:7se2b43pbfgcllkidpuvffcbge
Gamma Process Poisson Factorization for Joint Modeling of Network and Documents
[chapter]
2015
Lecture Notes in Computer Science
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This paper introduces Joint Gamma Process Poisson Factorization (J-GPPF) to jointly model network and side-information. ...
Developing models to discover, analyze, and predict clusters within networked entities is an area of active and diverse research. ...
For notational convenience, we represent the set of documents the n th author contributes to as Z n and the set of authors contributing to the d th document as Z d . ...
doi:10.1007/978-3-319-23528-8_18
fatcat:ohj5orawwnex3l4ct6gyukc474
Sparse Relational Topic Models for Document Networks
[chapter]
2013
Lecture Notes in Computer Science
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Previous work on relational topic models (RTM) has shown promise on learning latent topical representations for describing relational document networks and predicting pairwise links. ...
Our model can also handle imbalance issues in real networks via introducing various cost parameters for positive and negative links. ...
Graphical Model for SRTM considering only one document pair as an illustration '
d
'
d n
s
'
d n
w
d
dn
s
dn
w
. ...
doi:10.1007/978-3-642-40988-2_43
fatcat:h3xnk5l7abb3vi22lfbhylv7z4
Creating, documenting and sharing network models
2012
Network
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network model terminology, notation, and descriptions and explicit documentation of model scaling. ...
However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. ...
description languages, which would aid modelers in effectively documenting models for publication and exchange. ...
doi:10.3109/0954898x.2012.722743
pmid:22994683
fatcat:oidvtvi5izfa7dbabjnre46rby
A Dual Embedding Space Model for Document Ranking
[article]
2016
arXiv
pre-print
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We postulate that the proposed Dual Embedding Space Model (DESM) captures evidence on whether a document is about a query term in addition to what is modelled by traditional term-frequency based approaches ...
We train a word2vec embedding model on a large unlabelled query corpus, but in contrast to how the model is commonly used, we retain both the input and the output projections, allowing us to leverage both ...
For example, under the 2-Poisson model a document about Eminem will tend to mention the term 'eminem' repeatedly. ...
arXiv:1602.01137v1
fatcat:i6p7knyn3bdmfprli2f5cmdnze
A Statistical Model for Topically Segmented Documents
[chapter]
2011
Lecture Notes in Computer Science
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Experimental results have shown that, compared to existing generative models, our proposed model provides better perplexity of language modeling and better support for effective clustering of documents ...
Generative models for text data are based on the idea that a document can be modeled as a mixture of topics, each of which is represented as a probability distribution over the terms. ...
STM is based on a twoparameter Poisson Dirichlet process that employs a collapsed Gibbs sampler in a hierarchical model structure. ...
doi:10.1007/978-3-642-24477-3_21
fatcat:fbgyeihtd5c7vors6bjwwxhyz4
Two-way Poisson mixture models for simultaneous document classification and word clustering
2006
Computational Statistics & Data Analysis
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An approach to simultaneous document classification and word clustering is developed using a two-way mixture model of Poisson distributions. ...
A mixture of Poisson distributions is used to model the multivariate distribution of the word counts in the documents within each class. ...
Two-way mixtures of Poisson distributions We estimate the distribution of the document vector in each class using a parametric mixture model. ...
doi:10.1016/j.csda.2004.07.013
fatcat:os6mcafb2zchthcy7glrubjfge
Comparison of Generalized and Multilevel Poisson Regression Model with Poisson Model in Fertility Data in Rural of Fars Province (Iran)
2010
Majallah-i Dānishgāh-i ̒Ulūm-i Pizishkī-i Bābul
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If Poisson model is not applicable in a specific situation, it is better to apply generalized Poisson model and in cases that multilevel variable exists, it is better to use multilevel Poisson model. ...
In cases that dependent variable is count, Poisson model is applied. ...
This document was created with Win2PDF available at http://www.daneprairie.com. The unregistered version of Win2PDF is for evaluation or non-commercial use only. ...
doaj:5f8b1fdeaa7e4c00a55af66a8fa923cc
fatcat:3kfvp67qjra4vhhxfxrvdqdeci
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