HYBRID RECOMMENDER SYSTEMS SURVEY AND EXPERIMENTS system, the agreement between a user's past ratings and the recommendations of ach technique are used to select the technique to employ for the next recom- witching hybrids introduce additional complexity into the recommendation pro- cess since the switching criteria must be determined, and this introduces another level of parameterization. However, the benefit is that the system can be sensitive to the strengths and weaknesses of its constituent recommenders 33. MIXED Where it is practical to make large number of recommendations simultaneously, it may be possible to use amixed hybrid, where recommendations from more than one technique are presented together. The PTV system(Smyth Cotter 2000)uses this approach to assemble a recommended program of television viewing. It uses content-based techniques based on textual descriptions of Tv shows and collabor ative information about the preferences of other users. Recommendations from the two techniques are combined together in the final suggested program The mixed hybrid avoids the ' new item' start-up problem: the content-based component can be relied on to recommend new shows on the basis of their descriptions even if they have not been rated by anyone, It does not get around the 'new user'start-up problem, since both the content and collaborative methods need some data about user preferences to get off the ground, but if such a system is integrated into a digital television, it can track what shows are watched (and for how long)and build its profiles accordingly. Like the fallback hybrid, this tech nique has the desirable 'niche-finding, property in that it can bring in new items that a strict focus on content would eliminate The Ptv case is somewhat unusual because it is using recommendation to assemble a composite entity, the viewing schedule. Because many recommendations are needed to fill out such a schedule, it can afford to use suggestions from as man sources as possible. Where conflicts occur, some type of arbitration between method is required-in PTv, content-based recommendation take precedence over collab orative responses. Other implementations of the mixed hybrid, ProfBuilder (Wasfi 99)and PickAFlick(Burke et al., 1997; Burke, 2000), present multiple recommen dation sources side-by-side. Usually, recommendation requires ranking of items or selection of a single best recommendation, at which point some kind of combination technique must be employed 3.4. FEATURE COMBINATION Another way to achieve the content/ colla borative merger is to treat collaborative use conle on as simply additional feature data associated with each example and nt-based techniques over this augmented data set. For example, Basu, Hirsh and Cohen (1998)report on experiments in which the inductive rule learner Reproduced with permission of the copyright owner. Further reproduction prohibited without permissionReproduced with permission of the copyright owner. Further reproduction prohibited without permission