Garrafao/LSCDetection
Data Sets and Models for Evaluation of Lexical Semantic Change Detection
Provides a modular pipeline for detecting lexical semantic change across time periods or domains through composable steps: learning semantic representations (count vectors, embeddings, SVD) from corpora, aligning them across time periods (intersection, orthogonal procrustes, variational inference), and measuring divergence (cosine distance, local neighborhood distance). Supports multiple VSM-based representation types and integrates with gensim, scikit-learn, and VecMap for embedding alignment, with evaluation against benchmark datasets like DURel and SemEval.
No commits in the last 6 months.
Stars
31
Forks
17
Language
Python
License
GPL-3.0
Category
Last pushed
Dec 08, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/Garrafao/LSCDetection"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
RepoAnalysis/RepoSim
This repository contains experiments on comparing the similarity of Python repositories using ML models.
kunal4040/hybrid-search-eval
🔍 Benchmark embedding models in hybrid search with Weaviate. Evaluate MRR@K, Hit@K, latency, and...
cod3licious/simec
Similarity Encoder (SimEc) Neural Network Framework for learning low dimensional similarity...
paulbricman/semantica
Extending conceptual thinking with semantic embeddings.
MatthewPaver/sentence-similarity-analysis
Semantic sentence similarity demonstration using transformer-based embedding models. Explores...