Stem multinomi$ (all stems)

14 papers:

ECIR-2015-KimVBR #clustering #multi

Temporal Multinomial Mixture for Instance-Oriented Evolutionary Clustering (YMK, JV, SB, MAR), pp. 593–604.

KDD-2014-YinW #approach #clustering #modelling #multi

A dirichlet multinomial mixture model-based approach for short text clustering (JY, JW), pp. 233–242.

ICML-2011-SuSM #classification #multi #naive bayes #scalability #using

Large Scale Text Classification using Semisupervised Multinomial Naive Bayes (JS, JSS, SM), pp. 97–104.

MLDM-2011-LiuM #multi #naive bayes

Smoothing Multinomial Naïve Bayes in the Presence of Imbalance (AL, CEM), pp. 46–59.

SIGIR-2008-XuA08a #modelling #multi #probability #retrieval

A new probabilistic retrieval model based on the dirichlet compound multinomial distribution (ZX, RA), pp. 427–434.

ECIR-2007-PlachourasO #documentation #modelling #multi #retrieval

Multinomial Randomness Models for Retrieval with Document Fields (VP, IO), pp. 28–39.

KDD-2007-MeiSZ #automation #modelling #multi #topic

Automatic labeling of multinomial topic models (QM, XS, CZ), pp. 490–499.

ICML-2006-Elkan #approximate #clustering #documentation #multi

Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution (CE), pp. 289–296.

KDD-2005-SanghaiSDK #architecture #clustering #design #multi #performance #simulation

A multinomial clustering model for fast simulation of computer architecture designs (KS, TS, JGD, DRK), pp. 808–813.

SIGIR-2005-ZhangCL #classification #kernel #multi

Text classification with kernels on the multinomial manifold (DZ, XC, WSL), pp. 266–273.

ICML-2004-LebanonL #classification #multi

Hyperplane margin classifiers on the multinomial manifold (GL, JDL).

KDD-2004-PavlovBDKP #classification #clustering #documentation #multi #naive bayes #preprocessor

Document preprocessing for naive Bayes classification and clustering with mixture of multinomials (DP, RB, BD, SK, JP), pp. 829–834.

SIGIR-2002-KimRL #classification #estimation #multi #naive bayes #parametricity

A new method of parameter estimation for multinomial naive bayes text classifiers (SBK, HCR, HSL), pp. 391–392.

ICML-2000-HallH #information retrieval #learning #multi #natural language

Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval (KBH, TH), pp. 351–358.