1. UNIX User Data: This file contains 9 sets of sanitized user data drawn from the command histories of 8 UNIX computer users at Purdue over the course of up to 2 years.
2. OpinRank Review Dataset: This data set contains user reviews of cars and and hotels collected from Tripadvisor (~259,000
reviews) and Edmunds (~42,230 reviews).
3. Opinosis Opinion ⁄ Review: This dataset contains sentences extracted from user reviews on a given topic. Example topics are “performance of Toyota Camry” and “sound quality of ipod nano”.
4. DBWorld e-mails: It contains 64 e-mails which I have manually collected from DBWorld mailing list. They are classified in: 'announces of conferences' and 'everything else'.
5. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
6. Mturk User-Perceived Clusters over Images: This dataset was collected by Shan-Hung Wu and DataLab members at NTHU, Taiwan. There're 325 user-perceived clusters from 100 users and their corresponding descriptions.
7. Labeled Text Forum Threads Dataset: The dataset is a collection of text forum threads with class labels reflects the reply quality to the Initial-Post, 3 for complete relevant, 2 for partially relevant, and 1 for irrelevant
8. Syskill and Webert Web Page Ratings: This database contains HTML source of web pages plus the ratings of a single user on these web pages. Web pages are on four seperate subjects (Bands- recording artists; Goats; Sheep; and BioMedical)
9. Paper Reviews: This sentiment analysis data set contains scientific paper reviews from an international conference on computing and informatics. The task is to predict the orientation or the evaluation of a review.
10. Dresses_Attribute_Sales: This dataset contain Attributes of dresses and their recommendations according to their sales.Sales are monitor on the basis of alternate days.
11. 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.
12. Miskolc IIS Hybrid IPS: The dataset was created for the comparison and evaluation of hybrid indoor positioning methods. The dataset presented contains data from W-LAN and Bluetooth interfaces, and Magnetometer.
13. YouTube Spam Collection: It is a public set of comments collected for spam research. It has five datasets composed by 1,956 real messages extracted from five videos that were among the 10 most viewed on the collection period.
14. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
15. 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.
16. 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.
17. KDC-4007 dataset Collection: KDC-4007 dataset Collection is the Kurdish Documents Classification text used in categories regarding Kurdish Sorani news and articles.
18. SML2010: This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data.
19. SMS Spam Collection: The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.
20. Detect Malware Types: Provide a short description of your data set (less than 200 characters).
21. Youtube cookery channels viewers comments in Hinglish: The datasets are taken from top 2 Indian cooking channel named Nisha Madhulika channel and Kabita’s Kitchen channel.
The data set is in Hinglish Language.
22. 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).
23. NIPS Conference Papers 1987-2015: This data set contains the distribution of words in the full text of the NIPS conference papers published from 1987 to 2015.
24. 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.
25. Roman Urdu Data Set: Roman Urdu (the scripting style for Urdu language) is one of the limited resource languages.A data corpus comprising of more than 20000 records was collected.
26. 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.
27. News Popularity in Multiple Social Media Platforms: Large data set of news items and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn.
28. Victorian Era Authorship Attribution: To create the largest authorship attribution dataset, we extracted works of 50 well-known authors. To have a non-exhaustive learning, in training there are 45 authors whereas, in the testing, it's 50
29. 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,..).
30. 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.
31. 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.
32. YouTube Comedy Slam Preference Data: This dataset provides user vote data on which video from a pair of videos is funnier collected on YouTube Comedy Slam. The task is to automatically predict this preference based on video metadata.