|
--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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- split: eval |
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path: data/eval-* |
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dataset_info: |
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features: |
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- name: Product Name |
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dtype: string |
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- name: Category |
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dtype: string |
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- name: Description |
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dtype: string |
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- name: Selling Price |
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dtype: string |
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- name: Product Specification |
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dtype: string |
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- name: Image |
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dtype: string |
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splits: |
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- name: train |
|
num_bytes: 12542887 |
|
num_examples: 23993 |
|
- name: test |
|
num_bytes: 3499375 |
|
num_examples: 6665 |
|
- name: eval |
|
num_bytes: 1376174 |
|
num_examples: 2666 |
|
download_size: 6391314 |
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dataset_size: 17418436 |
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license: apache-2.0 |
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task_categories: |
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- image-classification |
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- image-to-text |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
|
|
|
--- |
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## Dataset Creation and Processing Overview |
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This dataset underwent a comprehensive process of loading, cleaning, processing, and preparing, incorporating a range of data manipulation and NLP techniques to optimize its utility for machine learning models, particularly in natural language processing. |
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### Data Loading and Initial Cleaning |
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- **Source**: Loaded from the Hugging Face dataset repository [bprateek/amazon_product_description](https://huggingface.co/datasets/bprateek/amazon_product_description). |
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- **Conversion to Pandas DataFrame**: For ease of data manipulation. |
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- **Null Value Removal**: Rows with null values in the 'About Product' column were discarded. |
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### Data Cleaning and NLP Processing |
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- **Sentence Extraction**: 'About Product' descriptions were split into sentences, identifying common phrases. |
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- **Emoji and Special Character Removal**: A regex function removed these elements from the product descriptions. |
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- **Common Phrase Elimination**: A function was used to strip common phrases from each product description. |
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- **Improving Writing Standards**: Adjusted capitalization, punctuation, and replaced '&' with 'and' for better readability and formalization. |
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### Sentence Similarity Analysis |
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- **Model Application**: The pre-trained Sentence Transformer model 'all-MiniLM-L6-v2' was used. |
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- **Sentence Comparison**: Identified the most similar sentence to each product name within the cleaned product descriptions. |
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### Dataset Refinement |
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- **Column Selection**: Retained relevant columns for final dataset. |
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- **Image URL Processing**: Split multiple image URLs into individual URLs, removing specific unwanted URLs. |
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### Image Validation |
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- **Image URL Validation**: Implemented a function to verify the validity of each image URL. |
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- **Filtering Valid Images**: Retained only rows with valid image URLs. |
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### Dataset Splitting for Machine Learning |
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- **Creation of Train, Test, and Eval Sets**: Used scikit-learn's `train_test_split` for dataset division. |
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For further details or to contribute to enhancing the dataset card, please refer to the [Hugging Face Dataset Card Contribution Guide](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards). |
