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

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
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
Pythongensim basicsWord2Vec.predict output word method
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40
Research direction
The issue requests a reverse inference method for Doc2Vec, analogous to Word2Vec's predict output word. Start by examining the source code for predict output word in gensim's Word2Vec implementation, then adapt it for Doc2Vec using the doc vector as input. The issue comments and the linked StackOverflow question may provide additional context and usage examples. Ensure the implementation returns a ranked list of words most likely predicted by a given doc vector.
potential Doc2Vec feature: reverse inference, to synthesize doc/summary words · piskvorky/gensim#2459 | Good First Issue