State-of-the-art count-based word embeddings for low-resource languages with a special focus on historical languages.
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Updated
Mar 19, 2025 - Python
State-of-the-art count-based word embeddings for low-resource languages with a special focus on historical languages.
This analysis uses ConsumerAffairs reviews to uncover reasons behind 1-star Starbucks ratings in the US. It uses a text analysis to identify service, product, and cleanliness issues impacting customer satisfaction.
Analysis of a large Amazon product reviews dataset using sentiment analysis, collocation extraction, and more.
Based on Gerhard Jäger's 2013 paper called "Phylogenetic Inference from Word Lists Using Weighted Alignment with Empirically Determined Weights"
Recommender system for food pairing
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