6.4 Item-influence approaches are compared on the USER-BASED kNN CF algorithm. 106 6.5 Item-influence approaches are compared on the ITEM-BASED knn CF algorithm. 107 7.1In stems it is not necessary to be familiar with an item to be able to 7.2 Miced initiative preference elicitation techniques may be necessary if the retail site has many different types of items 119 7. 3 New user signup simulation procedure 7.4 Showing how familiar the movies are to the users as the movies are "presented in batches according to each of the item influence measures we study here .. 124 7.5 Recommendation accuracy results from the offine simulations using various item influence measures on the UsER-BASED kNN CF algorithm 7.6 Recommendation accuracy results from the offine simulations using various item influence measures on the ITEM-BASED knn CF algorithm 126 7.7 Average survey responses 8. 1 The value legend demonstrating how much value an orientation of smiley-faces indicates 8.2 A part of a sample screenshot from a user in the Similar Group experimental 8.3 The Sun Simi itern- influence measure is compared against other measures on the ITEM-BASEd knn Cf algorithm 46 8.4 User actions may not be a reflection of their self reports 48 8.5 Interaction plots between the number of smilies on a movie and experimental conditions 150 Reproduced with permission of the copyright owner. Further reproduction prohibited without permissionReproduced with permission of the copyright owner. Further reproduction prohibited without permission