Fix Session Popular model (#575)

PreferredAI · Dec 30, 2023 · b69a235 · b69a235
1 parent eabdd2d
commit b69a235
Show file tree

Hide file tree

Showing 5 changed files with 14 additions and 2 deletions.
diff --git a/README.md b/README.md
@@ -196,6 +196,7 @@ The recommender models supported by Cornac are listed below. Why don't you join
 |      | [Most Popular (MostPop)](cornac/models/most_pop), [paper](https://arxiv.org/ftp/arxiv/papers/1205/1205.2618.pdf) | N/A | [bpr_netflix.py](examples/bpr_netflix.py)
 |      | [Non-negative Matrix Factorization (NMF)](cornac/models/nmf), [paper](http://papers.nips.cc/paper/1861-algorithms-for-non-negative-matrix-factorization.pdf) | N/A | [nmf_exp.py](examples/nmf_example.py)
 |      | [Probabilistic Matrix Factorization (PMF)](cornac/models/pmf), [paper](https://papers.nips.cc/paper/3208-probabilistic-matrix-factorization.pdf) | N/A | [pmf_ratio.py](examples/pmf_ratio.py)
+|      | [Session Popular (SPop)](cornac/models/spop), [paper](https://arxiv.org/pdf/1511.06939.pdf) | N/A | [spop_yoochoose.py](examples/spop_yoochoose.py)
 |      | [Singular Value Decomposition (SVD)](cornac/models/svd), [paper](https://people.engr.tamu.edu/huangrh/Spring16/papers_course/matrix_factorization.pdf) | N/A | [svd_exp.py](examples/svd_example.py)
 |      | [Social Recommendation using PMF (SoRec)](cornac/models/sorec), [paper](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.304.2464&rep=rep1&type=pdf) | N/A | [sorec_filmtrust.py](examples/sorec_filmtrust.py)
 |      | [User K-Nearest-Neighbors (UserKNN)](cornac/models/knn), [paper](https://arxiv.org/pdf/1301.7363.pdf) | N/A | [knn_movielens.py](examples/knn_movielens.py)

diff --git a/cornac/models/spop/recom_spop.py b/cornac/models/spop/recom_spop.py
@@ -48,7 +48,7 @@ def fit(self, train_set, val_set=None):
         return self
 
     def score(self, user_idx, history_items, **kwargs):
-        item_scores = np.ones(self.total_items, dtype=np.float32)
+        item_scores = np.zeros(self.total_items, dtype=np.float32)
         max_item_freq = max(self.item_freq.values()) if len(self.item_freq) > 0 else 1
         for iid, freq in self.item_freq.items():
             item_scores[iid] = freq / max_item_freq

diff --git a/docs/source/api_ref/models.rst b/docs/source/api_ref/models.rst
@@ -259,6 +259,11 @@ Probabilitic Matrix Factorization (PMF)
 .. automodule:: cornac.models.pmf.recom_pmf
    :members:
 
+Session Popular (SPop)
+----------------------
+.. automodule:: cornac.models.spop.recom_spop
+   :members:
+
 Singular Value Decomposition (SVD)
 ----------------------------------
 .. automodule:: cornac.models.svd.recom_svd

diff --git a/examples/README.md b/examples/README.md
@@ -108,6 +108,12 @@
 
 ----
 
+## Next-Item Algorithms
+
+[spop_yoochoose.py](spop_yoochoose.py) - Next-item recommendation based on item popularity.
+
+----
+
 ## Next-Basket Algorithms
 
 [gp_top_tafeng.py](gp_top_tafeng.py) - Next-basket recommendation model that merely uses item top frequency.

diff --git a/examples/spop_yoochoose.py b/examples/spop_yoochoose.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-"""Example of a next-basket recommendation model that merely uses item top frequency"""
+"""Example of a next-item recommendation model based on item popularity"""
 
 import cornac
 from cornac.datasets import yoochoose