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Questions tagged [gensim]

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gensim is the python library for topic modelling. multi-dimensional vector representation of words or sentences which preserves semantic meaning is computed through word2vec and doc2vec models.

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I have a dataset having job and description. i want to make model which can predict what are the thing that user needs to improve when the user inputs his skills. For an example, If he has skills - ...
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3 votes
2 answers
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I am new to machine learning and tried doc2vec on quora duplicate dataset. new_dfx has columns 'question1' and 'question2' which has preprocessed questions in each row. Following is the tagged ...
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I am using a LSA/TF-IDF/BM25/Ensemble models for text search and finally calculating similarity score to rank my search. I would like to decide a threshold value for the score, below which I would not ...
Prateek Coder's user avatar
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1 vote
1 answer
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Given the user data as in the following: ...
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I am totally new to this topic, that's why I am so confused or stuck in this code for a while, but I am not sure how to solve it correctly. My goal is to write a short text embedding using vector ...
test's user avatar
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1 answer
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I want to train fasttext on my own corpus. However, I have a small question before continuing. Do I need each sentences as a different item in corpus or can I have many sentences as one item? For ...
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I am now trying to use word2vec by estimating skipgram embeddings via NCE (noise contrastive estimation) rather than conventional negative sampling method, as a recent paper did (https://asistdl....
krcoder's user avatar
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2 votes
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With Gensim < 4.0, we can retrain a word2vec model using the following code: ...
NST's user avatar
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