refactor code

PreferredAI · Sep 12, 2024 · 9f7a283 · 9f7a283
1 parent 3fcc247
commit 9f7a283
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/cornac/models/companion/recom_companion.pyx b/cornac/models/companion/recom_companion.pyx
@@ -125,8 +125,10 @@ class Companion(Recommender):
 
     References
     ----------
-    Trung-Hoang Le and Hady W. Lauw. 2024 \
-    Learning to Rank Aspects and Opinions for Comparative Explanations.
+    Trung-Hoang Le and Hady W. Lauw. 2024. \
+    Learning to Rank Aspects and Opinions for Comparative Explanations. \
+    Machine Learning (Special Issue for ACML 2024). \
+    https://lthoang.com/assets/publications/mlj24.pdf
     """
     def __init__(
         self,
@@ -137,7 +139,6 @@ class Companion(Recommender):
         n_aspect_factors=8,
         n_opinion_factors=8,
         n_bpr_samples=1000,
-        n_sentiment_samples=1000,
         n_aspect_ranking_samples=1000,
         n_opinion_ranking_samples=1000,
         n_element_samples=50,
@@ -170,7 +171,6 @@ class Companion(Recommender):
         self.n_aspect_factors = n_aspect_factors
         self.n_opinion_factors = n_opinion_factors
         self.n_bpr_samples = n_bpr_samples
-        self.n_sentiment_samples = n_sentiment_samples
         self.n_aspect_ranking_samples = n_aspect_ranking_samples
         self.n_opinion_ranking_samples = n_opinion_ranking_samples
         self.n_element_samples = n_element_samples

diff --git a/examples/README.md b/examples/README.md
@@ -48,6 +48,8 @@
 
 [cdr_example.py](cdr_example.py) - Collaborative Deep Ranking (CDR) with CiteULike dataset.
 
+[companion_example.py](companion_example.py) - Comparative Aspects and Opinions Ranking for Recommendation Explanations (Companion) with Amazon Toy and Games dataset.
+
 [conv_mf_example.py](conv_mf_example.py) - Convolutional Matrix Factorization (ConvMF) with MovieLens dataset.
 
 [ctr_example_citeulike.py](ctr_example_citeulike.py) - Collaborative Topic Regression (CTR) with CiteULike dataset.
@@ -66,8 +68,6 @@
 
 [mter_example.py](mter_example.py) - Multi-Task Explainable Recommendation (MTER) with Amazon Toy and Games dataset.
 
-[companion_example.py](companion_example.py) - Comparative Aspects and Opinions Ranking for Recommendation Explanations (Companion) with Amazon Toy and Games dataset.
-
 ### Image
 
 [causalrec_clothing.py](causalrec_clothing.py) - CausalRec with Clothing dataset.