[PDF] Top 20 Gaussian LDA for Topic Models with Word Embeddings
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Gaussian LDA for Topic Models with Word Embeddings
... from Gaussian-LDA and LDA on the 20-news dataset for K = ...in Gaussian-LDA are ranked based on their den- sity assigned to them by the posterior predictive distribution in the final ... See full document
10
Nonparametric Spherical Topic Modeling with Word Embeddings
... nor Gaussian observational distributions used in existing topic models are appropriate to leverage such correla- ...base topic model and propose an efficient algorithm based on Stochastic ... See full document
6
Query Extension with Improved User Profiles for User tailored Search taking Advantage over Folksonomy Data
... called word embeddings, with topic models in 2 teams of pseudo-aligned ...weights-enhanced word embeddings, and also the topical relevancy between the question and also the terms ... See full document
5
A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings
... interactive topic models (ITM) (Hu et ...as Gaussian distributions over the embedding space, while constraints in ITM are sets of conceptually similar words that are interac- tively identified by ... See full document
7
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs
... mix-vMF topic model (MvTM). Mixtures of vMFs can help us capture complex topic structure that forms more dominant ...the topic, ...describe topic correlation in some ...baseline topic ... See full document
10
Multi Sense Embeddings from Topic Models
... and word embeddings separately, with sense specific word embeddings computed as a weighted sum of the two, where the weights are calculated using topic ...separate word & ... See full document
8
Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts
... Conventional topic models, such as PLSI and LDA, suffer from the sparsity problem when facing short texts, because they are lack of word co-occurrences at the document ...The models ... See full document
8
International Journal of Computer Science and Mobile Computing
... DIFFERENTIAL TOPIC MODELS 231 ...of word use, we could have employed this technique to handle shared ...model word distributions [16], however, they do not consider word correlations ... See full document
14
A Multi Dimensional Bayesian Approach to Lexical Style
... The results of the lexicon induction evaluation are in Table 1. Since the number of optimal iter- ations varies, we report the result from the best of the first five iterations, as measured by total accu- racy; the best ... See full document
7
Fast, Flexible Models for Discovering Topic Correlation across Weakly Related Collections
... our models’ ability to accommodate asymmetries be- tween arbitrary ...and topic structure — asymmetries that would be systematically overlooked using ex- isting ...of topic-level homophily, where ... See full document
11
Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings
... Another line of work explores ways of embedding larger spans of text. Although words tend to com- pose surprisingly well simply via linear combination, many phrases are more than the sum of their parts (e.g., ... See full document
10
Distributional Representations of Words for Short Text Classification
... Some try to select more useful contextual infor- mation to expand and enrich the original text, e.g. using large unlabeled corpora, such as Wikipedi- a (Banerjee et al., 2007) and WordNet (Hu et al., 2009). A ... See full document
6
Traffic Scene Analysis using Hierarchical Sparse Topical Coding
... The topic models can model relationships through the co- occurrence of simple features at different hierarchical ...some models with multi-level ...Clustering Topic Model (MCTM) which was ... See full document
10
Re Ranking Words to Improve Interpretability of Automatically Generated Topics
... Topics models, such as LDA, are widely used in Natural Language ...of topic words to generate more interpretable topic ...different word rankings with related ...improves topic ... See full document
12
Topic detection and tracking on heterogeneous information
... of topic k appearing in a feed on both collections. For each topic in the set, we then select the terms of the highest p(w | z) ...these models are trained in an unsupervised fashion with k = 300, ... See full document
24
Multivariate Gaussian Document Representation from Word Embeddings for Text Categorization
... Neural networks with convolutional and pool- ing layers have also been widely used for gen- erating representations of phrases or documents. These networks allow the model to learn which sequences of words are good ... See full document
6
EmotiKLUE at IEST 2018: Topic Informed Classification of Implicit Emotions
... use LDA topic distributions. We have four sets of embeddings that differ in size and training ...possible models. Results for mod- els using skip-gram-based embeddings are shown in ... See full document
8
Topic Models with Logical Constraints on Words
... ran LDA-DF with 1,000 itera- tions without any constraints and noticed that most topics have stop words ...of LDA-DF, which is compiled to one Dirichlet ...of LDA-DF with the isolate-link, we ... See full document
8
Improving Topic Models with Latent Feature Word Representations
... the topic representations in the small ...the topic space of the ...of LDA that uses external information about word similarity, such as thesauri and dictio- naries, to smooth the ... See full document
16
Incorporating Word Correlation Knowledge into Topic Modeling
... which topic they appear ...into LDA for word sense disambiguation, where each topic is a random process defined over the ...interactive topic modeling, which allows users to iteratively ... See full document
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