XJTUSL/ShiJiJiaYuanDataset

User Profile Dataset (Anonymized)

Dataset Description

A collection of 10,748 anonymized user profiles from a matchmaking/dating platform. Each record contains demographic attributes, lifestyle habits, and preferences. The dataset has been de-identified to satisfy k-anonymity (k >= 5).

Note on the dataset viewer For privacy reasons, two attributes — Age and Marital Status — are intentionally hidden from the dataset viewer preview. They are not deleted from the dataset itself: a complete 24-column file is provided at full/train.parquet and can be downloaded directly (see the Loading the full dataset section below).

Files in this repository

Path	Columns	Purpose
data/train.parquet	22	Default config; what the dataset viewer renders and what load_dataset(...) returns by default. Excludes Age and Marital Status.
full/train.parquet	24	Complete data including Age and Marital Status. Not registered as a viewer config — must be downloaded explicitly.
anonymize.py	—	Script used to generate the anonymized data.

Fields

Field	Type	Description	In viewer
Gender	Categorical	male / female	yes
Age	Range (5-yr or 10-yr bins)	e.g., "55-59", "60-69"	hidden
Marital Status	Categorical	Divorce, Widow, Never married, etc.	hidden
Location	Province/Region	Generalized to province or region level	yes
Educational Qualifications	Categorical	Bachelor, Associate, Technical secondary school, etc.	yes
Height	Range (5cm or 10cm bins)	e.g., "160-164cm", "170-179cm"	yes
Car Purchase Situation	Categorical	Purchased / Not yet purchased / Not disclosed	yes
Monthly Salary	Range	e.g., "2000-5000 RMB", "5000-10000 RMB"	yes
House Purchase Situation	Categorical	Purchased house / Not disclosed	yes
Constellation	Categorical	Zodiac sign	yes
Nation	Categorical	Ethnic group	yes
Blood Group	Categorical	A/B/O/AB-type	yes
Smoking Habits	Categorical	Smoking frequency/attitude	yes
Drinking Habits	Categorical	Drinking frequency	yes
Exercise Habits	Categorical	Exercise frequency	yes
Daily Schedule	Categorical	Sleep/wake routine	yes
Housework Level	Categorical	Housework involvement	yes
Pet Liking Level	Categorical	Attitude toward pets	yes
Industry	Categorical	Employment sector	yes
Company Type	Categorical	Type of employer	yes
Hometown	Province/Region	Generalized to province or region level	yes
About Children	Categorical	Preference regarding children	yes
Living With Parents	Categorical	Attitude toward living with parents	yes
Ranking At Home	Categorical	Birth order	yes

Privacy & Anonymization

This dataset has been de-identified using the following techniques:

1. ID Removal: Original user IDs have been removed and records shuffled randomly.
2. Quasi-identifier Generalization (multi-pass):
   • Age: exact age -> 5-year bins (10-year for harder-to-anonymize records)
   • Height: exact cm -> 5cm bins (10cm for harder cases)
   • Location/Hometown: city-level -> province-level (region-level for harder cases)
3. k-Anonymity Guarantee: Every combination of (Gender, Age, Location, Height) appears in at least 5 records (k >= 5).
4. Record Suppression: 321 records (2.9%) that could not satisfy k >= 5 even after maximum generalization were removed.
5. Terminology Normalization: "secrecy" values replaced with "Not disclosed".
6. Viewer Hiding: Age and Marital Status are excluded from the default viewer config to reduce surface-level exposure of these sensitive attributes; they remain available in full/train.parquet.

Limitations & Ethical Considerations

• This dataset originates from a real matchmaking platform. Despite anonymization, users should NOT attempt re-identification.
• The demographic distribution skews toward ages 50-65, reflecting the source platform's user base.
• Gender distribution is imbalanced (~83% female).
• This dataset is released for research purposes only (e.g., recommendation systems, demographic analysis). Commercial use for profiling individuals is prohibited.
• The anonymization satisfies k-anonymity but NOT l-diversity or t-closeness. Sensitive attributes (salary, marital status) may not be uniformly distributed within equivalence classes.

Usage

Default (22 columns, matches the viewer)

from datasets import load_dataset

dataset = load_dataset("tsiiiing/ShiJiJiaYuanDataset")
print(dataset["train"][0])
# Does NOT include `Age` or `Marital Status`.

Loading the full dataset (all 24 columns)

The complete file is stored at full/train.parquet and is not part of the default config. Load it explicitly:

from huggingface_hub import hf_hub_download
import pandas as pd

path = hf_hub_download(
    repo_id="tsiiiing/ShiJiJiaYuanDataset",
    filename="full/train.parquet",
    repo_type="dataset",
)
df = pd.read_parquet(path)  # 24 columns, includes Age and Marital Status

Or via the datasets library by pointing at the file directly:

from datasets import load_dataset

dataset = load_dataset(
    "parquet",
    data_files="hf://datasets/tsiiiing/ShiJiJiaYuanDataset/full/train.parquet",
)

Or via the CLI:

hf download tsiiiing/ShiJiJiaYuanDataset --type dataset --include "full/*"

Citation

If you use this dataset, please cite:

@dataset{ShiJiJiaYuanDataset,
  title={What you like, what I am: Online dating recommendation via matching individual preferences with features},
  year={2022},
  note={k-anonymized matchmaking platform user profiles}
}