Hugging Face's logo

Datasets:
recmeapp
/
mobilerec

Dataset card Data Studio Files
xet
Community
mobilerec
File size: 3,049 Bytes 
42a3ee2
 
 
 
 
 
 
 
 
 
d81e7ae
 
 
 
 
 
 
 
 
42a3ee2
 
 
d1a17cd
 
 
 
42a3ee2
 
d81e7ae
42a3ee2
 
d81e7ae
42a3ee2
68f9e21
ea56886
68f9e21
b87754c
 
 
 
 
088d94f
25499d7
 
 
088d94f
25499d7
088d94f
 
 
 
25499d7
088d94f
 
 
 
 
 
 
ea56886
68f9e21
42a3ee2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
 
---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
{}
---

# 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.')
```

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]