Currently, Mahout offers implementations for user-based recommendations, item-based based recommendations, and several variations of matrix factorization.
The use of context and information extracted from social network to support recommendation items is not new.
To find out relevant recommendation items from an educational point of view, a top down perspective can be used to design recommendations, especially for formal learning scenarios.
Self efficacy about the performance of physical activity will be assessed by seven (exercise programme) or eight (exercise recommendation) items based upon the Social Cognitive Theory.
Especially for the item recommendation problem, we should recommend items for a user from all the items.
As for the specific DTSQ items, satisfaction with current treatment (item 1), treatment understanding (item 6), treatment recommendation (item 7) and continuing treatment (item 8), were the most strongly associated with the SF-36 scales.
Most existing content-based recommendation systems, in which items are usually described with keywords, are designed to recommend items according to text contents.
There are two basic entities that drive a recommender system: users who use the recommender system to provide opinions as well as receive recommendations and items that are rated by users.
An eleven-page appendix details recommendations for items to be included in the stimulus bill that Obama proposed in his first weeks in office.
The design of Group ReM which is simple and domain-independent, can easily be extended to make group recommendations on items other than movies.
For example, eBay buyers are expected to benefit from Hunch's predictive ability to generate meaningful, yet often non-obvious, recommendations for items available on eBay based on their specific tastes.
