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  license: other
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  license_name: bright-data-master-service-agreement
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  license_link: https://brightdata.com/license
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: other
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  license_name: bright-data-master-service-agreement
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  license_link: https://brightdata.com/license
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+ language:
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+ - en
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+ tags:
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+ - travel
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+ - hospitality
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+ - booking
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+ - hotels
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+ - hotel
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+ - pricing‑data
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+ - tabular‑data
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+ pretty_name: 'Booking.com Listings '
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+ size_categories:
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+ - 10K<n<100K
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  ---
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+
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+ # Booking Listings – *Free Cancellation* 🏨✈️
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+
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+ **Booking Listings** is a structured snapshot of accommodation offers worldwide as listed on **Booking.com**.
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+ This subset contains **only properties that offer *free cancellation***, enabling analysts and data scientists to study flexible‑booking behaviour, derive pricing strategies, and build recommendation or revenue‑management systems.
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+
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+ > **Highlights**
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+ >
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+ > * 75 k hotels & apartments across **84 countries**
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+ > * Rich pricing & availability metadata (final vs. original price, tax descriptions, currency, sustainability flags)
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+ > * Guest sentiment — review score & count
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+ > * Property configuration: bedrooms, kitchens, beds, star rating, sustainability level, ***free‑cancellation‑until*** timestamp
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+ > * Scraped **Mar 19 2025** with Bright Data Web Scraper
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+
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+ ---
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+
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+ ## Dataset Summary
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+
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+ | Metric | Value |
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+ | --------------- | ------------------------------------------------- |
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+ | Records | ≈ 75 000 (filtered free‑cancellation subset) |
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+ | Columns | 36 |
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+ | Time range | Check‑in/out dates centred on **19 Mar 2025** |
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+
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+ ## Supported Tasks
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+
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+ * **Travel recommendation & personalisation** – rank properties by flexibility, price trends, amenities.
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+ * **Dynamic pricing / revenue management** – benchmark competitors that allow free cancellation to fine‑tune rates.
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+ * **Market research & trend analysis** – assess demand elasticity towards cancellation policies in different regions.
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+ * **Real‑estate & investment insights** – locate high‑rated, sustainable, or luxury properties with lenient policies.
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+
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+ ## Languages
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+
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+ All textual fields are in **English**. Currency codes follow ISO‑4217.
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+
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+ ---
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ Each row represents a single property returned by a user search (one check‑in/out pair). Below is a truncated example (JSON Lines):
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+
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+ ```json
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+ {
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+ "url": "https://www.booking.com/hotel/au/the-westin-perth.html?...",
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+ "location": "Perth",
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+ "check_in": "2025-03-19T00:00:00Z",
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+ "check_out": "2025-03-20T00:00:00Z",
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+ "adults": 1,
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+ "rooms": 1,
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+ "id": 3052882,
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+ "title": "The Westin Perth",
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+ "city": "Perth",
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+ "review_score": 8.8,
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+ "review_count": 1250,
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+ "image": "https://cf.bstatic.com/xdata/images/hotel/...jpg",
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+ "final_price": 47249,
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+ "original_price": 47249,
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+ "currency": "JPY",
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+ "free_cancellation": true,
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+ "free_cancellation_until": "2025-03-18T16:00:00Z",
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+ "hotel_rank": 77,
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+ "star_rating": null,
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+ "tags": null,
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+ ...
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+ | Column | Type | Description |
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+ | ------------------------- | -------------------- | --------------------------------------------------- |
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+ | `url` | string (URL) | Direct link to the property listing. |
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+ | `location` | string | General destination (city/area) of the property. |
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+ | `check_in` | datetime | Requested check‑in date. |
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+ | `check_out` | datetime | Requested check‑out date. |
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+ | `adults` | int | Number of adults in the query. |
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+ | `children` | int \| null | Number of children (if provided). |
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+ | `rooms` | int | Rooms requested. |
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+ | `id` | string | Booking.com property identifier. |
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+ | `title` | string | Property name. |
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+ | `address` | string | Street address. |
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+ | `city` | string | City name (may differ from `location`). |
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+ | `review_score` | float | Average guest rating (0‑10). |
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+ | `review_count` | int | Number of reviews. |
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+ | `image` | string (URL \| null) | Thumbnail of main image. |
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+ | `final_price` | float | Price returned by search (includes taxes). |
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+ | `original_price` | float | Original price before discounts. |
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+ | `currency` | string | ISO‑4217 currency code. |
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+ | `tax_description` | string \| null | Additional taxes/fees description. |
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+ | `nb_bedrooms` | int | Number of bedrooms. |
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+ | `nb_all_beds` | int | Total beds available. |
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+ | `full_location` | string | Normalised “City, Country” location. |
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+ | `free_cancellation` | bool | *Always `true`* in this subset. |
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+ | `free_cancellation_until` | datetime \| null | Deadline for free cancellation. |
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+ | `property_sustainability` | JSON | Sustainability metadata + facility codes. |
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+ | `hotel_rank` | int | Position in Booking search results. |
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+ | `searched_country` | string | 2‑letter country code of the search. |
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+ | `map_coordinates` | struct | `{ "lat": float, "lon": float }` (may be null). |
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+ | `listing_country` | string | Country where property is located. |
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+ | `total_listings_found` | int | Total search results for query. |
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+ | `star_rating` | int \| null | 1‑5 stars. |
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+ | `tags` | string \| null | Booking‑generated tags (e.g. "Travel Sustainable"). |
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+ | nb_livingrooms | int | Number of living rooms in the property. |
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+ | nb_kitchens | int | Number of kitchens in the property. |
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+ | no_prepayment | bool | Indicates if prepayment is not required. |
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+
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+ Nested object keys:
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+
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+ full_location → description, main_distance, display_location, beach_distance, nearby_beach_names
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+
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+ property_sustainability → is_sustainable, level_id, facilities
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+
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+ ---
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+
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+ ## Data Splits
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+
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+ | Split | Rows | Description |
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+ | ------- | ----- | ------------------------------- |
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+ | `train` | 0 | *not applicable* |
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+ | `test` | 0 | *not applicable* |
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+ | `all` | ≈ 75k | Complete snapshot (single CSV). |
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+
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+ This dataset is delivered as **one CSV file** (`booking_listings.csv`).
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+
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+ ---
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+
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+ ## Usage Example
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset(
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+ "BrightData/booking_listings",
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+ data_files="booking_listings.csv",
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+ split="train",
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+ )
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+ print(ds[0]["title"], ds[0]["free_cancellation_until"])
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+ ```
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+
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+ ---
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+
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+ ## Source & Methodology
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+
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+ Data was collected on **19 Mar 2025** using the **Bright Data Infrastructure** and publicly available Booking.com search results.
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+ For this subset, we retained only listings where the *free cancellation* flag was **`true`**.
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+
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+ ---
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+
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+ ## Citation
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+
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+ If you use this dataset in your work, please cite it as:
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+
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+ ```bibtex
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+ @dataset{booking_listings_free_cancel_2025,
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+ author = {Bright Data},
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+ title = {Booking Listings – Free Cancellation Subset},
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+ year = {2025},
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+ publisher = {Hugging Face},
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+ url = {https://huggingface.co/datasets/BrightData/Booking-Listings},
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+ note = {Scraped via Bright Data on 2025‑03‑19}
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+ }
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+ ```
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+
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+ ---
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+
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+ ## Maintainers
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+
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+ **Bright Data**
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+ [@Bright Data](https://github.com/luminati-io)
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+
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+ Have questions or need a refreshed dump? Open an issue or reach out! 📨