{"action":"opened","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/840","labels_url":"https://api.github.com/repos/fchollet/keras/issues/840/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/840/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/840/events","html_url":"https://github.com/fchollet/keras/issues/840","id":111664493,"number":840,"title":"Is Word Clustering Possible In Keras?","user":{"login":"LeavesBreathe","id":14891677,"avatar_url":"https://avatars.githubusercontent.com/u/14891677?v=3","gravatar_id":"","url":"https://api.github.com/users/LeavesBreathe","html_url":"https://github.com/LeavesBreathe","followers_url":"https://api.github.com/users/LeavesBreathe/followers","following_url":"https://api.github.com/users/LeavesBreathe/following{/other_user}","gists_url":"https://api.github.com/users/LeavesBreathe/gists{/gist_id}","starred_url":"https://api.github.com/users/LeavesBreathe/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/LeavesBreathe/subscriptions","organizations_url":"https://api.github.com/users/LeavesBreathe/orgs","repos_url":"https://api.github.com/users/LeavesBreathe/repos","events_url":"https://api.github.com/users/LeavesBreathe/events{/privacy}","received_events_url":"https://api.github.com/users/LeavesBreathe/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-10-15T17:13:19Z","updated_at":"2015-10-15T17:13:19Z","closed_at":null,"body":"Hey everyone, \r\n\r\nI've been trying to figure out a way to cluster words based upon similarity. \r\n\r\nSuppose you read many books that total to 100k different words used. It would be great if you could make ~1000 clusters with approx 100 words/cluster. In each cluster, words are similar to each other. \"Dog\" and \"Cat\" in one cluster and \"truck\" and \"car\" in a different cluster. \r\n\r\nI saw that there's the well-made skipgram word-embedding script example: https://github.com/fchollet/keras/blob/master/examples/skipgram_word_embeddings.py\r\n\r\nAnd I also saw that word2vec has made word clusters: https://code.google.com/p/word2vec/\r\n\r\nI know that they usually apply a k-means on top of of the word vectors created. I thought it would be good to start a discussion about this in case other keras-users are interested in the same thing.\r\n\r\nThanks! "}}