diff --git a/cornac/models/companion/recom_companion.pyx b/cornac/models/companion/recom_companion.pyx
index 1678a8b1..2246bf4d 100644
--- a/cornac/models/companion/recom_companion.pyx
+++ b/cornac/models/companion/recom_companion.pyx
@@ -1026,7 +1026,7 @@ class Companion(Recommender):
                 np.repeat(range(n_items), n_top_aspects).reshape(
                     n_items, n_top_aspects
                 ),
-                ts3[:, :-1].argsort(axis=1)[::-1][:, :n_top_aspects],
+                ts3[:, :-1].argsort(axis=1)[:, ::-1][:, :n_top_aspects],
             ]
             item_scores = (
                 self.alpha * top_aspect_scores.mean(axis=1) + (1 - self.alpha) * ts3[:, -1]
diff --git a/cornac/models/comparer/recom_comparer_sub.pyx b/cornac/models/comparer/recom_comparer_sub.pyx
index ec1173db..9b2bf661 100644
--- a/cornac/models/comparer/recom_comparer_sub.pyx
+++ b/cornac/models/comparer/recom_comparer_sub.pyx
@@ -769,7 +769,7 @@ class ComparERSub(MTER):
                 np.repeat(range(self.num_items), n_top_aspects).reshape(
                     self.num_items, n_top_aspects
                 ),
-                ts3[:, :-1].argsort(axis=1)[::-1][:, :n_top_aspects],
+                ts3[:, :-1].argsort(axis=1)[:, ::-1][:, :n_top_aspects],
             ]
             known_item_scores = (
                 self.alpha * top_aspect_scores.mean(axis=1) + (1 - self.alpha) * ts3[:, -1]