stevend94/Feature2Vec
Code used in the paper, Feature2Vec: Distributional semantic modelling of human property knowledge
This project helps cognitive scientists and linguists understand how humans associate properties with concepts, like 'a banana is yellow.' It takes a dataset of concepts and their associated features (like 'banana' and 'yellow') and generates numerical representations (embeddings) that capture these relationships. The output can be used to visualize and analyze semantic connections, offering insights into human knowledge organization.
No commits in the last 6 months.
Use this if you are a researcher studying human semantic memory, property knowledge, or the cognitive representation of concepts, and you want to model these relationships computationally.
Not ideal if you are looking for a general-purpose text embedding tool for tasks like document classification or sentiment analysis, as its focus is on modeling human property knowledge.
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9
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3
Language
Python
License
BSD-2-Clause
Category
Last pushed
Aug 13, 2020
Commits (30d)
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