Motivating and Supporting User Interaction with Recommender Systems 435 Figure 5 shows the browsing page for reviews. A rating service analog to the one described in section 3. 1 is available on the level of reviews. By means of this a first impression of the quality of certain reviews can be assessed without reading them. Reviews can be browsed and sorted by different criteria: reviewer, date, average ratings of the three user groups respectively, user group of the reviewer, and target group. By means of this service more detailed information about the content, the quality and the adequacy of a document for certain tasks (like preparation for an examination) can be assessed, even if the full text of the document is not available online Inspection of this information on the other hand takes significantly longer than with the previously described systems. When searching the full text of all reviews for keywords, it can be used as a user generated indexing of the library catalog. At 2007-03-19 26 reviews(see figure 3) and 11 ratings of reviews are online. The reasons behind these numbers are discussed in the following sections 4 Mechanism Design Problems,, and solutions Motivating users to write reviews or rate documents in a digital library is a game of(static) mechanism design, a special class of games of incomplete in formation. See e.g. Game Theory"by Fudenberg and Tirole [4 pp for an introduction. By determining the structure of the digital library and e corresponding recommender services the operator of the library chooses the mechanism that maximizes his desired outcome. Here, the players are all library sers and the desired outcome is a large number of high quality(implicit and explicit)recommendations. The following mechanism design problems are most dominant in the described applications Free-riding. Observing recommendations is highly valued, but due to transac tion costs few users actually are willing to produce them Bias. Conscious or unconscious prejudice. E. g. a book author favors his product to the ones of competitors Credibility. Are recommendations mixed with sales promotion or advertise- ments? Privacy vs. recognition of good cooperation. To laud users with exemp- ry cooperation you need their allowance to recognize them Positive/Negative feedback effects. The first good or bad recommendation may lead to further good or bad recommendations respectively(path Economies of scale. The more contributing users(and thus recommendations) a system has, the more useful it is and thereby attracting even more users. o solve these problems a suited incentive systems has to be implemented Recommendations are no standard consumer goods thus needing a special user motivation approach 2. Motivation can be intrinsic or extrinsic. Extrinsic mo- tivation is generated e. g by payments or public commendation. Compensations not only fulfill the purpose of inducing effort on the existing user group butMotivating and Supporting User Interaction with Recommender Systems 435 Figure 5 shows the browsing page for reviews. A rating service analog to the one described in section 3.1 is available on the level of reviews. By means of this a first impression of the quality of certain reviews can be assessed without reading them. Reviews can be browsed and sorted by different criteria: reviewer, date, average ratings of the three user groups respectively, user group of the reviewer, and target group. By means of this service more detailed information about the content, the quality and the adequacy of a document for certain tasks (like preparation for an examination) can be assessed, even if the full text of the document is not available online. Inspection of this information on the other hand takes significantly longer than with the previously described systems. When searching the full text of all reviews for keywords, it can be used as a user generated indexing of the library catalog. At 2007-03-19 26 reviews (see figure 3) and 11 ratings of reviews are online. The reasons behind these numbers are discussed in the following sections. 4 Mechanism Design Problems . . . and Solutions Motivating users to write reviews or rate documents in a digital library is a game of (static) mechanism design, a special class of games of incomplete in￾formation. See e. g. “Game Theory” by Fudenberg and Tirole [4] pp. 243–318 for an introduction. By determining the structure of the digital library and the corresponding recommender services the operator of the library chooses the mechanism that maximizes his desired outcome. Here, the players are all library users and the desired outcome is a large number of high quality (implicit and explicit) recommendations. The following mechanism design problems are most dominant in the described applications: Free-riding. Observing recommendations is highly valued, but due to transac￾tion costs few users actually are willing to produce them. Bias. Conscious or unconscious prejudice. E.g. a book author favors his product to the ones of competitors. Credibility. Are recommendations mixed with sales promotion or advertise￾ments? Privacy vs. recognition of good cooperation. To laud users with exemp￾lary cooperation you need their allowance to recognize them. Positive/Negative feedback effects. The first good or bad recommendation may lead to further good or bad recommendations respectively (path dependency). Economies of scale. The more contributing users (and thus recommendations) a system has, the more useful it is and thereby attracting even more users. To solve these problems a suited incentive systems has to be implemented. Recommendations are no standard consumer goods thus needing a special user motivation approach [2]. Motivation can be intrinsic or extrinsic. Extrinsic mo￾tivation is generated e.g. by payments or public commendation. Compensations not only fulfill the purpose of inducing effort on the existing user group but