| | --- |
| | license: cc-by-sa-4.0 |
| | task_categories: |
| | - text-classification |
| | - zero-shot-classification |
| | - feature-extraction |
| | language: |
| | - en |
| | pretty_name: j |
| | size_categories: |
| | - 10M<n<100M |
| | --- |
| | |
| | # Dataset Card for 13M+ Website Domains with Industry Labels |
| |
|
| | This dataset contains over **12 million website domain URLs** mapped to their associated **industry categories**. |
| | It is useful for **domain classification, industry prediction, NLP preprocessing, clustering, and machine learning research**. |
| |
|
| | This dataset card has been generated based on the [Hugging Face dataset card template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). |
| |
|
| | --- |
| |
|
| | ## Dataset Details |
| |
|
| | ### Dataset Description |
| |
|
| | - **Curated by:** Satyam Mishra |
| | - **Funded by [optional]:** None |
| | - **Shared by:** [Kaggle DOI](https://doi.org/10.34740/kaggle/dsv/9734207) |
| | - **Language(s) (NLP):** URLs (not language-specific, but linked industries are primarily English labels) |
| | - **License:** Research and educational use only |
| |
|
| | The dataset has **two columns**: |
| | - `website`: Domain URL (cleaned, no DNS tags) |
| | - `industry`: Associated industry or category (with ~5% null values) |
| |
|
| | --- |
| |
|
| | ### Dataset Sources |
| |
|
| | - **Repository:** [Kaggle Dataset](https://www.kaggle.com/dsv/9734207) |
| | - **Paper [optional]:** N/A |
| | - **Demo [optional]:** N/A |
| |
|
| | --- |
| |
|
| | ## Uses |
| |
|
| | ### Direct Use |
| | This dataset can be used for: |
| | - Training and evaluating **domain → industry classifiers** |
| | - **NLP preprocessing** for URL/domain-related models |
| | - **Business intelligence** (e.g., mapping company presence across industries) |
| | - **Clustering & categorization** of domains |
| |
|
| | ### Out-of-Scope Use |
| | - Misuse for phishing detection or malicious targeting of industries |
| | - Commercial exploitation of the dataset beyond research/educational purposes |
| | - Inference of sensitive or personal data (none exists in the dataset) |
| |
|
| | --- |
| |
|
| | ## Dataset Structure |
| |
|
| | The dataset consists of a single table with **13,642,052 rows** and two fields: |
| |
|
| | - **website**: Cleaned domain URL |
| | - **industry**: Associated industry or category (nullable, ~5% missing values) |
| |
|
| | Example: |
| |
|
| | ```json |
| | { |
| | "website": "example.com", |
| | "industry": "Technology" |
| | } |
| | ``` |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| | The motivation was to create one of the largest open datasets mapping **web domains to industries** for advancing research in **web classification, NLP, and ML-driven categorization**. |
| |
|
| | ### Source Data |
| |
|
| | #### Data Collection and Processing |
| | - **Scraping** — Website URLs were collected from publicly available internet sources. |
| | - **Cleaning** — DNS tags and non-relevant parts were removed. |
| | - **Industry Mapping** — Mapped via metadata, keywords, and context. |
| | - **Final Dataset** — Consolidated into two columns (`website`, `industry`). |
| |
|
| | #### Who are the source data producers? |
| | - The data comes from **publicly available websites**. |
| | - No private or proprietary datasets were used. |
| |
|
| | ### Annotations [optional] |
| |
|
| | #### Annotation Process |
| | - Industries were mapped using **rule-based and contextual matching techniques**. |
| |
|
| | #### Who are the annotators? |
| | - The dataset was created and curated by the **author (Satyam Mishra)**. |
| |
|
| | #### Personal and Sensitive Information |
| | - No personal, sensitive, or private data is included. |
| | - Dataset consists only of **publicly available domains and general industry categories**. |
| |
|
| | --- |
| |
|
| | ## Bias, Risks, and Limitations |
| |
|
| | - ~5% missing values in the `industry` column. |
| | - Some industries may be **ambiguous or mislabeled** due to heuristic mapping. |
| | - Domains without clear metadata may not have precise industry labels. |
| |
|
| | ### Recommendations |
| | - Users should **clean and validate industries** before downstream ML tasks. |
| | - Consider re-labeling ambiguous or null industry entries with custom classification. |
| | - Dataset is best suited for **research and educational purposes**. |
| |
|
| |
|
| | ## Citation |
| |
|
| | If you use this dataset, please cite: |
| |
|
| | ### BibTeX: |
| | ``` |
| | @misc{satyam_mishra_2024, |
| | title={12M+ Website Domains with Industry Labels}, |
| | url={https://www.kaggle.com/dsv/9734207}, |
| | DOI={10.34740/KAGGLE/DSV/9734207}, |
| | publisher={Kaggle}, |
| | author={Satyam Mishra}, |
| | year={2024} |
| | } |
| | ``` |
| |
|
| | ### APA: |
| | Mishra, S. (2024). 12M+ Website Domains with Industry Labels. Kaggle. https://doi.org/10.34740/kaggle/dsv/9734207 |
| |
|
