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README.md
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path: data/test-*
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- split: test
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path: data/test-*
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---
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## Dataset Summary
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**SID Clustering (SIDClustring)** is a Persian (Farsi) dataset created for the **Clustering** task, specifically focusing on grouping academic articles. It is part of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard). The dataset was constructed from scientific articles available on **SID (Scientific Information Database – sid.ir)**, categorized into 8 distinct domains reflecting academic disciplines.
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* **Language(s):** Persian (Farsi)
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* **Task(s):** Clustering (Document Clustering, Topic Modeling)
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* **Source:** Crawled from the SID academic publication platform
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* **Part of FaMTEB:** Yes
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## Supported Tasks and Leaderboards
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This dataset is designed to assess the ability of embedding models to perform document clustering—grouping articles into logical scientific categories. Results can be viewed on the [Persian MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard), under the Clustering task.
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## Construction
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1. Articles were collected by crawling the **sid.ir** platform.
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2. For each article:
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- The **title** and **abstract** were extracted.
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- These were concatenated using two newline characters (`\n\n`) to form the document input.
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3. Each document was assigned to one of 8 predefined SID categories.
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4. The resulting dataset serves as a benchmark for evaluating unsupervised clustering performance.
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## Data Splits
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* **Train:** 8,712 samples
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* **Development (Dev):** 0 samples
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* **Test:** 3,735 samples
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