From Word Embeddings To Document Distances. Kusner, M., Sun, Y., Kolkin, N., & Weinberger, K. In International Conference on Machine Learning, pages 957-966. Paper abstract bibtex We present the Word Mover’s Distance (WMD), a novel distance function between text documents. Our work is based on recent results in word embeddings that learn semantically meaningful representatio...
@inproceedings{kusnerWordEmbeddingsDocument2015,
langid = {english},
title = {From {{Word Embeddings To Document Distances}}},
url = {http://proceedings.mlr.press/v37/kusnerb15.html},
abstract = {We present the Word Mover’s Distance (WMD), a novel distance function between text documents. Our work is based on recent results in word embeddings that learn semantically meaningful representatio...},
eventtitle = {International {{Conference}} on {{Machine Learning}}},
booktitle = {International {{Conference}} on {{Machine Learning}}},
urldate = {2019-02-19},
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