bab2min/chronogram
Diachronic Word Embedding Model based on Word2vec Skip-gram with Chebyshev approximation
This tool helps researchers and linguists understand how the meaning of words changes over time. By inputting large collections of text data spanning different periods, it outputs a model that captures these semantic shifts. This allows you to trace the evolution of word meanings and identify how specific words were used in past eras.
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Use this if you need to analyze historical text data to observe how word meanings and usage have evolved across different time periods.
Not ideal if you're looking for a simple keyword search or a tool to analyze static text without a temporal dimension.
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Language
C++
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Last pushed
Jun 06, 2023
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