[WIP] Added function "predict_output_word" to predict the output word given the context words. Fixes issue #863.

gensim/models/word2vec.py

@@ -1203,6 +1203,27 @@ def similarity(self, w1, w2):
     def n_similarity(self, ws1, ws2):
         return self.wv.n_similarity(ws1, ws2)
 
+    def predict_output_word(self, context_words_list, topn=10):
+        #verify that required parameters have not been discarded
+        if not hasattr(self.wv, 'syn0') or not hasattr(self, 'syn1neg'):
+            raise RuntimeError("Parameters required for predicting the output words not found.")
+
+        word_vocabs = [self.wv.vocab[w] for w in context_words_list if w in self.wv.vocab]
+
+        word2_indices = []
+        for pos, word in enumerate(word_vocabs):
+            word2_indices.append(word.index)
+
+        l1 = np_sum(self.wv.syn0[word2_indices], axis=0)
+        if word2_indices and self.cbow_mean:
+            l1 /= len(word2_indices)
+
+        if self.negative :
+            prob_values = exp(dot(l1, self.syn1.T))     # propagate hidden -> output and take softmax to get probabilities
+            prob_values /= sum(prob_values)
+            top_indices = matutils.argsort(prob_values, topn=topn, reverse=True)
+            return [(self.wv.index2word[index1], prob_values[index1]) for index1 in top_indices]   #returning the most probable output words with their probabilities
+
     def init_sims(self, replace=False):
         """
         init_sims() resides in KeyedVectors because it deals with syn0 mainly, but because syn1 is not an attribute