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--- |
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license: cc |
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task_categories: |
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- text-classification |
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language: |
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- uk |
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size_categories: |
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- 100K<n<1M |
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--- |
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The dataset is relevant to Ukrainian reviews in three different domains: |
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1) Hotels. |
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2) Reustarants. |
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3) Products. |
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The dataset is comrpised of several .csv files, which one can found useful: |
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1) processed_data.csv - the processed dataset itself. |
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2) train_val_test_indices.csv - csv file with train/val/test indices. The split was stratified w.r.t dataset name (hotels, reustarants, products) and rating. |
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3) bad_ids.csv - csv file with ids of bad samples marked using model filtering approach, only ids of those samples for which difference between actual and predicted rating is bigger than 2 points are maintained in this file. |
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The data is scrapped from Tripadvisor (https://www.tripadvisor.com/) and Rozetka (https://rozetka.com.ua/). |
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The dataset was initially used for extraction of key-phrases relevant to one of rating categories, based on trained machine learning model (future article link will be here). |
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Dataset is processed to include two additional columns: one with lemmatized tokens and another one with POS tags. Both lemmatization and POS tagging are done using pymorphy2 (https://pymorphy2.readthedocs.io/en/stable/) library. |
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The words are tokenized using a specific regex tokenizer to account for usage of apostroph. |
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Those reviews which weren't in Ukrainian were translated to it using Microsoft translator and re-checked manually afterwards. |
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