Questions tagged [topic-model]

A topic model describes text from a large corpus as a probability distribution over topics which are probability distributions over words. There are quantified contributions from all topics to a specific text.

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0answers
125 views

Extending Author-Topic LDA

I've been trying to extend the LDA and wanted some help, direction and insight. Can Author-Topic LDA be used as a document "category" model? The premise of the Author-Topic model is that multiple ...
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1answer
406 views

What metrics must i use in my data(unstructured) preprocessing research?

i am currently working on preprocessing unstructured data (emails,logs,bug reports and irc chats). i wish to prove preprocessing improves the content quality. are there metrics available to prove ...
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4answers
5k views

How to give name to topics created using LDA?

I have categorized 800,000 documents into 500 categories using the Mahout topic modelling. Instead of representing the topic using the top 5/10 words for each topics, I want to infer a generic name ...
2
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3answers
2k views

replicability / reproducibility in topic modeling (LDA)

If I'm not wrong, topic modeling (LDA) is not replicable, i.e. it gives different results in different runs. Where does this come from (where does this randomness come from and why is it necessary?) ...
2
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2answers
462 views

How to discard trash topics from topic models?

I am undertaking text analysis of some twitter data. In the end I want to have a data that is interpretable. And so in the end I would like to reduce the data to relevant unit of analysis. Topic ...
5
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2answers
358 views

Why do my Latent Dirichlet Allocation Topics mix words that never co-occurred?

I have one corpus of documents on diabetes, another on Leonardo da Vinci, and another on animation and computer graphics. I combined all of these documents into a LDA and got a topic like the one ...
4
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2answers
377 views

Topic models for Relevance Prediction

Suppose I have data in the form of Query/Document Pairs, along with corresponding relevance scores (or class labels). Is there a way to use topic modeling to devise a model so that later given a ...
5
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3answers
2k views

Need help with LDA for selecting features

I am currently selecting features of products by using LDA to group 6000 keywords of product into topics. Here is the sample of my dataset after being organized into list of keywords for each product ...
2
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1answer
197 views

Reasons and prevention of trivial (and less trivial) misclassification errors?

I was not sure about posting this question with mentioning the name of the company, which I quite respect and admire. However, I've figured that a wider exposure might help the team to fix this and ...
9
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5answers
11k views

Tutorials on topic models and LDA

I would like to know if you people have some good tutorials (fast and straightforward) about topic models and LDA, teaching intuitively how to set some parameters, what they mean and if possible, with ...
27
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3answers
19k views

What is difference between text classification and topic models?

I know the difference between clustering and classification in machine learning, but I don't understand the difference between text classification and topic modeling for documents. Can I use topic ...
22
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2answers
28k views

What does the alpha and beta hyperparameters contribute to in Latent Dirichlet allocation?

LDA has two hyperparameters, tuning them changes the induced topics. What does the alpha and beta hyperparameters contribute to LDA? How does the topic change if one or the other hyperparameters ...
58
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6answers
26k views

Latent Dirichlet Allocation vs Hierarchical Dirichlet Process

Latent Dirichlet Allocation (LDA) and Hierarchical Dirichlet Process (HDP) are both topic modeling processes. The major difference is LDA requires the specification of the number of topics, and HDP ...

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