Add application features

.gitattributes

@@ -54,3 +54,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
 myket.csv filter=lfs diff=lfs merge=lfs -text
+app_info.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -4,6 +4,11 @@ task_categories:
   - graph-ml
 size_categories:
   - 100K<n<1M
+configs:
+- config_name: main_data
+  data_files: "myket.csv"
+- config_name: package_name_features
+  data_files: "app_info.csv"
 ---
 # Myket Android Application Install Dataset
 
@@ -17,7 +22,10 @@ We further subsampled and cleaned the data to focus on application download inte
 
 ## Data Structure
 
-The dataset follows the same format as the datasets used in the "[JODIE: Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks](https://github.com/claws-lab/jodie)" (ACM SIGKDD 2019) project. However, this data does not contain state labels and interaction features, resulting in associated columns being all zero.
+The dataset has two main files.
+
+- `myket.csv`: This file contains the interaction information and follows the same format as the datasets used in the "[JODIE: Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks](https://github.com/claws-lab/jodie)" (ACM SIGKDD 2019) project. However, this data does not contain state labels and interaction features, resulting in associated columns being all zero.
+- `app_info_sample.csv`: This file comprises features associated with applications present in the sample. For each individual application, information such as the approximate number of installs, average rating, count of ratings, and category are included. These features provide insights into the applications present in the dataset.
 
 ## Dataset Details
 

app_info.csv

@@ -0,0 +1,3 @@
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+oid sha256:0c0730cbc739e1fc5c740e69c074b8c4e729f9eb6611ba53d3b374ba45a87c30
+size 522357