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dselivanov · Nov 13, 2023 · 59e5607 · 59e5607
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diff --git a/NEWS.md b/NEWS.md
@@ -48,7 +48,7 @@
     * Add additional filters to `prune_vocabulary` - filter by document counts
     * Clean up LSA, fixed transform method. Added option to use randomized SVD algorithm from `irlba`.
 1. 2017-05-17
-    * Imrove `dist2` performamce for RWMD - incorporate ideas from [gensim PR discussion](https://github.com/RaRe-Technologies/gensim/pull/800#issuecomment-260743822).
+    * Imrove `dist2` performamce for RWMD - incorporate ideas from [gensim PR discussion](https://github.com/piskvorky/gensim/pull/800#issuecomment-260743822).
 1. 2017-05-17
     * **API breaking change** - vocabulary format change - now plain `data.frame` with meta-information in attributes (stopwords, ngram, number of docs, etc).
 1. 2017-03-25

diff --git a/docs/glove.Rmd b/docs/glove.Rmd
@@ -116,4 +116,4 @@ cos_sim = sim2(x = word_vectors, y = berlin, method = "cosine", norm = "l2")
 head(sort(cos_sim[,1], decreasing = TRUE), 5)
 ```
 
-You can achieve much better results by experimenting with `skip_grams_window` and the parameters of the `GloVe` class (including word vectors size and the number of iterations). For more details and large-scale experiments on wikipedia data see this [old post](http://dsnotes.com/blog/text2vec/2015/12/01/glove-enwiki/) on my blog.
+You can achieve much better results by experimenting with `skip_grams_window` and the parameters of the `GloVe` class (including word vectors size and the number of iterations). For more details and large-scale experiments on wikipedia data see this [old post](https://dsnotes.com/blog/text2vec/2015/12/01/glove-enwiki/) on my blog.
diff --git a/vignettes/glove.Rmd b/vignettes/glove.Rmd
@@ -121,4 +121,4 @@ head(sort(cos_sim[,1], decreasing = TRUE), 5)
 # 0.7859821 0.7410693 0.6490518 0.6216343 0.6160014
 ```
 
-You can achieve much better results by experimenting with `skip_grams_window` and the parameters of the `GloVe` class (including word vectors size and the number of iterations). For more details and large-scale experiments on wikipedia data see this [old post](http://dsnotes.com/blog/text2vec/2015/12/01/glove-enwiki/) on my blog.
+You can achieve much better results by experimenting with `skip_grams_window` and the parameters of the `GloVe` class (including word vectors size and the number of iterations). For more details and large-scale experiments on wikipedia data see this [old post](https://dsnotes.com/blog/text2vec/2015/12/01/glove-enwiki/) on my blog.