piskvorky/gensim

potential Doc2Vec feature: reverse inference, to synthesize doc/summary words

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#2,459 opened on Apr 21, 2019

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Description

Motivated by the SO question: https://stackoverflow.com/questions/55768598/interpret-the-doc2vec-vectors-clusters-representation/55779049#55779049

Doc2Vec could plausibly have a function that's reverse-inference: take a doc-vector, return a (ranked) list of words most-predicted by that input vector. It'd work highly analogously to Word2Vec.predict_output_word(). Such a list of words might be useful as a sort-of summary or label for a doc-vector.

Contributor guide

Research direction
Study Word2Vec.predict output word() implementation in gensim. Then, adapt it for Doc2Vec to return ranked words from a doc vector. Test with a trained Doc2Vec model.
Tech stack
python
Domain
machine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
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Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Pythongensim word2vec usage
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
45