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Pachinko allocation
Multi-View Learning for Hierarchical Topic Detection on Corpus of Documents
Nonstationary Latent Dirichlet Allocation for Speech Recognition
Large-Scale Hierarchical Topic Models
Journal of Applied Sciences Research
Incorporating Domain Knowledge in Latent Topic Models
Extração De Informação Semântica De Conteúdo Da Web 2.0
An Unsupervised Topic Segmentation Model Incorporating Word Order
A New Method and Application for Studying Political Text in Multiple Languages
Semi-Automatic Terminology Ontology Learning Based on Topic Modeling
Song Lyric Topic Modeling
Topic Modeling Based on Keywords and Context
A Latent Semantic Approach Yik-Cheung Tam CMU-LTI-09-016
Efficient Learning for Spoken Language Understanding Tasks with Word Embedding Based Pre-Training
Topics in Tweets: a User Study of Topic Coherence Metrics for Twitter Data
SPRITE: Generalizing Topic Models with Structured Priors
Inter and Intra Topic Structure Learning with Word Embeddings
Discriminative Topic Mining Via Category-Name Guided Text Embedding
Pachinko Allocation: Scalable Mixture Models of Topic Correlations
Top View
Latent Probabilistic Topic Discovery for Text Documents Incorporating Segment Structure and Word Order
Traffic Behavior Recognition Using the Pachinko Allocation Model
Topicmodels: an R Package for Fitting Topic Models
Topicmodels: an R Package for Fitting Topic Models
Mixtures of Hierarchical Topics with Pachinko Allocation
Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data
Simdoc: Topic Sequence Alignment Based Document Similarity Framework
Latent Dirichlet Allocation (LDA) and Topic Modeling: Models, Applications, a Survey
Topic Modelling of Finnish Internet Discussion Forums As a Tool for Trend Identification and Marketing Applications
Modeling Topics and Knowledge Bases with Vector Representations
Topic Models for Taxonomies
Pachinko Allocation: DAG-Structured Mixture Models of Topic Correlations
Online Inference of Topics
Topic Modeling with Nonparametric Markov Tree
Arxiv:1711.04305V2 [Cs.IR] 6 Dec 2018 Y
Ch-21 (R.Uma, B.Latha).Indd
On the Power of Pre-Trained Text Representations: Models And
Efficient Methods for Inferring Large Sparse Topic Hierarchies