semvec/pypi-packages huggingface dataset:
anime-recs-synopsis 0.0.3
Anime recommender model which measures synopsis/genre similarity to generate recommendations.
Requires Python: >=3.6

# AniBrain-Anime_LDA_Topic_Similarity_Model
LDA Topic Model for Anime Synopsis Similarity

## What is topic modelling?
Topic models learn topics—typically represented as sets of important words—automatically from unlabelled documents in an unsupervised way.

## What is LDA? How does it work?
Latent Dirichlet Allocation(LDA) is a popular algorithm for topic modeling.

"LDA’s approach to topic modeling is it considers each document as a collection of topics in a certain proportion. And each topic as a collection of keywords, again, in a certain proportion.

Once you provide the algorithm with the number of topics, all it does it to rearrange the topics distribution within the documents and keywords distribution within the topics to obtain a good composition of topic-keywords distribution.

When I say topic, what is it actually and how it is represented?

A topic is nothing but a collection of dominant keywords that are typical representatives. Just by looking at the keywords, you can identify what the topic is all about." [[1]](https://www.machinelearningplus.com/nlp/topic-modeling-gensim-python/#4whatdoesldado)

## References 
[1] [Topic Modeling with Gensim (Python) by  Selva Prabhakaran](https://www.machinelearningplus.com/nlp/topic-modeling-gensim-python/#4whatdoesldado)