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Dataset Card for Dataset Name
Dataset Description
- Homepage:
- https://github.com/mhmaqbool/mobilerec
- Repository:
- https://github.com/mhmaqbool/mobilerec
- Paper:
- MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation
- Point of Contact:
- M.H. Maqbool (hasan.khowaja@gmail.com)
- Abubakar Siddique (abubakar.ucr@gmail.com)
Dataset Summary
MobileRec is a large-scale app recommendation dataset. There are 19.3 million user\item interactions. This is a 5-core dataset. User\item interactions are sorted in ascending chronological order. There are 0.7 million users who have had at least five distinct interactions. There are 10173 apps in total.
Supported Tasks and Leaderboards
Sequential Recommendation
Languages
English
How to use the dataset?
from datasets import load_dataset
import pandas as pd
# load the dataset and meta_data
mbr_data = load_dataset('recmeapp/mobilerec', data_dir='interactions')
mbr_meta = load_dataset('recmeapp/mobilerec', data_dir='app_meta')
# Save dataset to .csv file for creating pandas dataframe
mbr_data['train'].to_csv('./mbr_data.csv')
# Convert to pandas dataframe
mobilerec_df = pd.read_csv('./mbr_data.csv')
# How many interactions are there in the MobileRec dataset?
print(f'There are {len(mobilerec_df)} interactions in mobilerec dataset.')
# How many unique app_packages (apps or items) are there?
print(f'There are {len(mobilerec_df["app_package"].unique())} unique apps in mobilerec dataset.')
# How many unique users are there in the mobilerec dataset?
print(f'There are {len(mobilerec_df["uid"].unique())} unique users in mobilerec dataset.')
# How many categoris are there?
print(f'There are {len(mobilerec_df["app_category"].unique())} unique categories in mobilerec dataset.')
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Dataset Structure
Data Instances
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Data Fields
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Data Splits
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Dataset Creation
Curation Rationale
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Source Data
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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