1. Perfume Data: This data consists of odors of 20 different perfumes. Data was obtained by using a handheld odor meter (OMX-GR sensor) per second for 28 seconds period.
2. User Knowledge Modeling: It is the real dataset about the students' knowledge status about the subject of Electrical DC Machines. The dataset had been obtained from Ph.D. Thesis.
3. AAAI 2013 Accepted Papers: This data set compromises the metadata for the 2013 AAAI conference's accepted papers (main track only), including paper titles, abstracts, and keywords of varying granularity.
4. ICMLA 2014 Accepted Papers Data Set: This data set compromises the metadata for the 2014 ICMLA conference's accepted papers, including ID, paper titles, author's keywords, abstracts and sessions in which they were exposed.
5. Dishonest Internet users Dataset: The dataset was used to test an architecture based on a trust model capable to cope with the evaluation of the trustworthiness of users interacting in pervasive environments.
6. AAAI 2014 Accepted Papers: This data set compromises the metadata for the 2014 AAAI conference's accepted papers, including paper titles, authors, abstracts, and keywords of varying granularity.
7. BuddyMove Data Set: User interest information extracted from user reviews published in holidayiq.com about various types of point of interests in South India
8. seeds: Measurements of geometrical properties of kernels belonging to three different varieties of wheat. A soft X-ray technique and GRAINS package were used to construct all seven, real-valued attributes.
9. Wholesale customers: The data set refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories