Shypd.aiThe largest open index of AI toolsWMD (Word Mover's Distance) is an open-source tool providing Python and Matlab code for calculating document distances using word embeddings. It implements Matthew J Kusner's paper "From Word Embeddings to Document Distances."
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WMD (Word Mover's Distance) is an open-source implementation of the Word Mover's Distance algorithm, as described in Matthew J Kusner's paper "From Word Embeddings to Document Distances." This tool provides both Python and Matlab code, making it accessible for researchers and practitioners in natural language processing. It allows users to compute the distance matrix between documents based on their word embeddings, offering a robust method for comparing textual content. The repository includes scripts for extracting word vectors, computing WMD, and even a KNN function for classification. It also provides access to datasets used in the original paper, facilitating replication and further research. Prerequisites include Python 2.7 packages like gensim, numpy, and scipy, along with pre-trained word2vec embeddings.
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