1. CNAE-9: This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a
subset of 9 categories
2. Amazon Commerce reviews set: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
3. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
4. TTC-3600: Benchmark dataset for Turkish text categorization: The TTC-3600 data set is a collection of Turkish news and articles including categorized 3,600 documents from 6 well-known portals in Turkey. It has 4 different forms in ARFF Weka format.
5. Opinion Corpus for Lebanese Arabic Reviews (OCLAR): Opinion Corpus for Lebanese Arabic Reviews (OCLAR) corpus is utilizable for Arabic sentiment classification on services’ reviews, including hotels, restaurants, shops, and others.
6. DeliciousMIL: A Data Set for Multi-Label Multi-Instance Learning with Instance Labels: This dataset includes 1) 12234 documents (8251 training, 3983 test) extracted from DeliciousT140 dataset, 2) class labels for all documents, 3) labels for a subset of sentences of the test documents.
7. YouTube Multiview Video Games Dataset: This dataset contains about 120k instances, each described by 13 feature types, with class information, specially useful for exploring multiview topics (cotraining, ensembles, clustering,..).