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Questions tagged [topic-models]

A topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents.

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Biased viterbi training result

I try to use GMM-HMM model to infer the topic of sentences in a short paragraph. While instead of using normal Baum-Welch optimization, I use viterbi training as follows. I use average of word ...
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1answer
25 views

LDA detect new emerging topics

Thanks for stopping by. I have a directional question - I've built a Latent Dirichlet Allocation using Gensims Mallet wrapper. I trained the model once on OldDataSet.csv and measured coherence. I have ...
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7 views

Interpretation of NLP pipeline for topic discovery using gaussian mixture model clustering

I built a pipeline that does the following to discover topics out of a (very big: 50k docs per ~350 terms) Term Document Matrix: Compute the TfIdf score for each Term x Document pair; Rescale each ...
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1answer
23 views

What is the formula for c_v coherence?

I've recently been playing around with Gensim LDAModel. I use coherence to evaluate the results. Gensim offers a few coherence measures. This includes c_v and ...
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28 views

Gibbs sampler: how can thinning equal to the number of iterations work?

I fit an LDA topic model, using the R package topicmodels. No hiccups and everything runs smoothly, my question here is conceptual. When controlling the Gibbs sampler, the default value (in the ...
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21 views

Choosing the number of topics in topic modeling with multiple “elbows” in the coherence plot

When plotting the number of topics on the x-axis and the coherence score on the y-axis, I had expected to see an "elbow" (for example, here and here). In this case, however, the plot does not have a ...
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12 views

How to interpret LDA (Latent Dirichlet Allocation)?

Say I want to run topic modeling with LDA on The 20 newsgroups text dataset. So basically a dataset with texts where every text belongs to one of 20 categories. I want the LDA to split the documents ...
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23 views

Why does perplexity change with different ranges of k?

I ran a 5-fold cross-validation in R to calculate LDA perplexity for k = 2:9 using a 10% sample of my data. The output was: ...
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10 views

Using LDA to create two layered wordcloud

I create a word-cloud using LDA model what I want to do is to find the documents IDs related to that topic group. So, for example, the image here I want to allow users to click the word broccoli and ...
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10 views

Term x term matrix for text clustering. What to do with subterms of n-grams

I am doing topic discovery on a large corpus. Reading here and there I found some papers saying that in case of big, sparse document x term matrices is better to create first a term x term similarity ...
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1answer
28 views

Summary statitics to describe topic x term distribution in NLP

I created a topic model which outputted 11 topics out of 437 terms on ~60000 small documents. I wanted to show how good each topic is. But I don't know what "good" means in this case. Here's the ...
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Ideas for fixing manual misclassification

Imagine the following problem. Mechanics fix cars and use a set of parts which is recorded on invoices. They also write down a classification of the work that was done from a fixed set of possible ...
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31 views

how to prepare text data for LSTM autoencoder

My main goal is to come up with some topics using LSTM autoencoder. I want to use 20 news_group data set. after reading lots of material and looking at some GitHub project, I am still not clear how ...
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20 views

Guided LDA to categorize software requirements

I'm developing a application to categorize requirements in a requirement specification in to categories like database, front end, back end, etc. So for that I'm trying to use Guided LDA since labelled ...
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23 views

LDA visualization:

I am trying to find ways to visualize topics(LDA) to test something I am working on. I used to use pyLDAvis in python but currently what I am working on outputs only two items: 1) P(Topic | word), ...
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17 views

Combining the topics of two Latent Dirichlet Allocations

How to combine two LDAs? Let's suppose we have one corpus and we have estimated two Latent Dirichlet Allocations for two sub-corpuses : one for sub corpus A and another for sub corpus B. Now first ...
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1answer
15 views

How to understand pLSA model Q function?

I know in EM algorithm M-step, it tries to solve $$ \operatorname{argmax}_{\theta} Q(\theta, \theta^{ \text{old}}) = \sum_z p(z|x; \theta^{ \text{old}}) \log p(x,z; \theta) $$ I also understand the ...
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1answer
173 views

LDA: find percentage / number of documents per topic

I'm using LDA to find topics in a corpus. Everything works fine (I have the topics). But I would like to have the percentage / number of documents in each topic. It's possible? I looked at scikit-...
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66 views

How do I compute LDA topic similarity?

I am using the tidytext, quanteda, and tm packages in R to analyse my corpus of 220 documents. Using the topicmodels package I have extracted key topics using LDA. I now have a tidy dataframe that ...
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What are ways to build topic topic models on a corpus with high variance in text length

As the title states, I'm currently working with a corpus that has a high variance in the document length. Each input could be anything from the size of a tweet to a a full page worth of text. I'm ...
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64 views

Perplexity calculation in variational neural topic models

I'm looking at this 2016 paper from Miao et al. https://arxiv.org/abs/1511.06038 where they use a variational autoencoder for topic modelling. To evaluate the effectiveness of their model, they use ...
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66 views

Whats the difference and similarity between topic modeling (LDA) and text summarization (textrank)

The concept of these two (Topic modeling and Text summarization) are similar because Topic modeling gives you important number of topics and summarization gives you important summary of a large text. ...
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17 views

Split mixed distribution into separate ones

There is a set of customers who are doing actions. Each customer can have multiple roles. Each action is driven by a particular role that customer have. For example: $Customer_1$ has two roles: $...
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1answer
456 views

Seeded LDA using topicmodels in R

I would like to perform a LDA in R by means of topicmodels. To make the resulting topics better match the topics I want to see, I would like to input "seed words" for these topics into the LDA, ...
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220 views

Why can't K-means be used on LDA output

I started working on a topic definition task and my initial approach was as follows: Use LDA (Latent Dirichlet Allocation) to obtain the initial topic distribution for each of my documents. Then use ...
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1answer
29 views

How to see the words shared across topics in LDA model?

I am trying to find the words that are shared across the topics and words unique to a topic using LDA model in R. Is there any package or function? Thanks
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1answer
77 views

How to implement topic modelling in regression analysis

I have a dataset consisting of hotel reviews, ratings, and other features such as traveller type, and word count of the review. I want to perform topic modeling (LDA) and use the topics derived from ...
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1answer
2k views

How does topic coherence score in LDA intuitively makes sense ?

referring to: http://qpleple.com/topic-coherence-to-evaluate-topic-models/ In order to decide the optimum number of topics to be extracted using LDA, topic coherence score is always used to measure ...
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1answer
161 views

Assess the dependence of LDA on the random seed

New to latent Dirichlet Allocation (LDA), I would like to be sure that my output (in the first the step, the word-per-topic probabilities) depends on the input merely, and is (somewhat) stable ...
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28 views

LDA corpus stability [closed]

I am working on an LDA to find out topics from a corpus. Everything works fine, but when I add some lines in my corpus, the topics change a lot. This should not happen because the added topics ...
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1answer
238 views

Can I use word2vec vectors as input features to NMF or LDA?

I'm trying to do some topic modelling on my corpus and I want to use Word2Vec vectors as an input to my NMF and LDA models. How do I do this? Is it even possible?
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1answer
97 views

nmf in scipy returns components with all zero weights

I'm trying to understand whether this behavior is a bug or a feature. Essentially, I have a dataset of ten thousand short pieces of text. I have used the CountVectorizer function to turn this into a ...
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how is the vector representation of a out of sample document calculated on gensim's LDA implementation? [closed]

I am not sure of how gensim's LDA implementation obtains the vector representation of an unseen document. ...
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Matrix of probabilities of unsupervised labeling vs annotations [closed]

Given a list of texts, annotated by topic (each text can have multiple topics), and the document-topic matrix output of an LDA (Latent Dirichlet Allocation), unsupervised model. For example: ...
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How to evaluate the result of topic modeling such that time matters

I have run different topic modeling approaches on my data (clinical data related to Cognitive impairment diseases). we are going to process what is important that makes it develop to a harsher disease....
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15 views

Use topic modeling to determine the topic popularity

I have a collection of documents. My end goal is to determine the popularity of the topic discussed by each document. In other words, whether (or to what extent) one document is discussing a popular ...
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22 views

Classifying trending and not trending topics using LDA

How can we differentiate the topics obtained from LDA as trending and not trending topics? What are the factors we can consider for this classification?
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1answer
59 views

How Specifically do Sampling methods help in training Machine learning models?

I get the gist of sampling methods in probability. These algorithms were developed while building the Atom Bomb to estimate some distribution. The idea was just to try a simulation and note the ...
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1answer
209 views

How to improve performance for LDA?

I am running LDA on health-related data. Specifically I have ~500 documents that contain interviews that last around 5-7 pages. Other than that, I cannot really go into the details of the data due to ...
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341 views

LDA TopicModel Alpha Parameter (Gensim)

I fit a topic model on python with 8 topics with alpha set to auto. I am trying to determine what my alpha value is for the model. the ldamodel.alpha command in gensim outputs an array, with 8 ...
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47 views

Help with variational Inference for Hierarchical Dirichlet Process

I am going over this paper by Chong Wang et. al. titled "Online Variational Inference for the Hierarchical Dirichlet Process" and I am struggling with the derivation of equation (17): $\varphi_{jtk} \...
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25 views

how to classify text that belongs to multiple (possibly missing) categories?

I have a dataframe that is very similar to the classic Reuters News topic classification dataset, and I am interested in ...
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0answers
17 views

Topic assignment in a topic document matrix. How to be robust?

I have a Document-Topic matrix whose scores were produced by multiplying a Topic-Term matrix produced by non-negative matrix factorization on a Term-Term matrix and the original Document-Term matrix ...
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49 views

Is the Latent Dirichlet Allocation topic posterior multimodal?

In fitting the Latent Dirichlet Allocation with collapsed Gibbs sampling one builds a sampled approximation to the topic posterior distribution, $P(z|w)$ and use that to calculate the topic and word ...
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40 views

Adjusting for selection bias in a structural topic model

I want to build a structural topic model that adjusts for selection bias into the sample of entities about whom documents are written. I wanted to use the stm R ...
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1answer
374 views

LDA topic modelling improvement

I am working on an LDA model to identify the topic of ~100,000 online courses based on their course descriptions and titles. In the further process, I would like to use these topics to cluster these ...
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1answer
47 views

How to use hierarchical Dirichlet process to predict new word's probability

Assuming that I have already obtained document's topic distribution and topic-word distribution, how to predict the probability of one document will contain some word w_n?
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1answer
111 views

Does it make sense using Machine Learning techniques on a sparse features matrix?

I am trying to predict the sentiment (neg/neutral/pos) of a given text. To do so I use a LDA model (Latent Dirichlet Allocation) that is a topic discovery model. The LDA model works as follows: given ...
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2answers
329 views

latent dirichlet allocation: complexity and implementation details

I was confused by how LDA (by the original variational inference) can be implemented in a way such that the number of operations for each document $j$ is $\mathcal{O}(N_j~K)$, where $N_j$ is the ...
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2answers
148 views

Does Latent Dirchlet Allocation Work with Bag Of Words Model?

I was watching a tutorial on topic modeling and no-where they talk if the number in the bag of words model is significant. i.e. they only care whether word "a" belongs in the document or not, how ...