Datasets:

Modalities:
Text
Formats:
parquet
ArXiv:
Libraries:
Datasets
pandas
License:
File size: 2,071 Bytes
1718739
 
4868580
 
 
 
 
 
 
 
 
 
 
 
 
 
e20e858
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1718739
 
 
 
 
 
 
 
 
 
 
 
 
 
4868580
 
 
 
e20e858
 
 
 
1718739
 
 
 
045607f
 
 
1718739
045607f
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
dataset_info:
- config_name: Books
  features:
  - name: title
    dtype: string
  - name: description
    dtype: string
  - name: asin
    dtype: string
  splits:
  - name: full
    num_bytes: 740843.1838136007
    num_examples: 839
  download_size: 619821
  dataset_size: 740843.1838136007
- config_name: CDs_and_Vinyl
  features:
  - name: title
    dtype: string
  - name: description
    dtype: string
  - name: asin
    dtype: string
  splits:
  - name: full
    num_bytes: 2625826.775842011
    num_examples: 3801
  download_size: 2515295
  dataset_size: 2625826.775842011
- config_name: Movies_and_TV
  features:
  - name: title
    dtype: string
  - name: description
    dtype: string
  - name: asin
    dtype: string
  splits:
  - name: full
    num_bytes: 3532557.899069776
    num_examples: 4832
  download_size: 3038812
  dataset_size: 3532557.899069776
configs:
- config_name: Books
  data_files:
  - split: full
    path: Books/full-*
- config_name: CDs_and_Vinyl
  data_files:
  - split: full
    path: CDs_and_Vinyl/full-*
- config_name: Movies_and_TV
  data_files:
  - split: full
    path: Movies_and_TV/full-*
license: cc-by-nc-4.0 # Assuming a CC-BY-NC-4.0 license based on common practice.  Verify!
task_categories:
- text-generation
---

# Difference-aware Personalized Learning (DPL) Dataset

This dataset is derived from Amazon Reviews'23 and processed for use in the Difference-aware Personalized Learning (DPL) method, as described in the paper:

[Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalization](https://arxiv.org/abs/2503.02450)

The dataset comprises product reviews categorized into three config names: Books, CDs_and_Vinyl, and Movies_and_TV.  Each review includes the `title`, `description`, and `asin`.


**Code:**  The code for processing the original Amazon Reviews'23 dataset into this format can be found here: [Github Link](https://github.com/username/repository_name) (Replace with actual github link).


**Data Structure:** (Keep the existing data structure description here)