1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.
1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 7. The method of claim 1 , wherein the selecting and ordering the collection of content items is further based on popularity values associated with the content items, each popularity value indicating a relative measure of a likelihood that the corresponding content item is desired by the user.