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README.md
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pretty_name: IAB categorization Dataset
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pretty_name: IAB categorization Dataset
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size_categories:
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# Article and Category Dataset
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## Overview
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This dataset contains a collection of articles, primarily news articles, along with their respective IAB (Interactive Advertising Bureau) categories. It can be a valuable resource for various natural language processing (NLP) tasks, including text classification, text generation, and more.
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## Dataset Information
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- **Number of Samples:** 871,909
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- **Number of Categories:** 26
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### Column Information
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- **text:** The text of the article.
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- **target:** The IAB category label corresponding to the article.
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## IAB Categories
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The Interactive Advertising Bureau (IAB) categories are a standardized taxonomy used in the advertising industry to categorize digital advertising content. These categories help advertisers and marketers target their audience more effectively. Each category is represented by a label or code that indicates the content's topic or theme.
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## Potential Use Cases
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- **Text Classification:** Use this dataset to train and evaluate text classification models to predict IAB categories for articles.
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- **Text Generation:** Utilize the articles in this dataset as a source for text generation tasks, such as generating news headlines or summaries.
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- **Topic Modeling:** Explore the dataset to discover underlying topics and themes in the articles.
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- **Information Retrieval:** Build search engines or recommendation systems that use article content and categories to retrieve relevant articles for users.
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## Data Format
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The dataset is provided in a standard tabular format with two columns: "text" and "target". You can easily load and manipulate the data using popular data manipulation libraries such as pandas in Python.
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## License
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This dataset is available under the [Apache 2.0 License](LICENSE.md). Please review the license before using the dataset for any purpose.
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