1. Health News in Twitter: The data was collected in 2015 using Twitter API. This dataset contains health news from more than 15 major health news agencies such as BBC, CNN, and NYT.
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. 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.
4. Burst Header Packet (BHP) flooding attack on Optical Burst Switching (OBS) Network: One of the primary challenges in identifying the risks of the Burst Header Packet (BHP) flood attacks in Optical Burst Switching networks (OBS) is the scarcity of reliable historical data.
5. microblogPCU: MicroblogPCU data is crawled from sina weibo microblog[http://weibo.com/]. This data can be used to study machine learning methods as well as do some social network research.
6. DSRC Vehicle Communications: This set Provides data regarding wireless communications between vehicles and road side units. two separate data sets are provided (normal scenario) and in the presence of attacker (jammer).
7. 3D Road Network (North Jutland, Denmark): 3D road network with highly accurate elevation information (+-20cm) from Denmark used in eco-routing and fuel/Co2-estimation routing algorithms.
8. Multimodal Damage Identification for Humanitarian Computing: 5879 captioned images (image and text) from social media related to damage during natural disasters/wars, and belong to 6 classes: Fires, Floods, Natural landscape, Infrastructural, Human, Non-damage.
9. SMS Spam Collection: The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.