A computer-implemented method, comprising: at an electronic device with one or more processors and memory: identifying a first plurality of data items from a plurality of data models, wherein: each data model of the plurality of data models is associated with a model confidence value; and each data item of the first plurality of data items is previously selected by a user; obtaining a plurality of item confidence values based on a comparison of the model confidence values, wherein each data item of the first plurality of data items is associated with an item confidence value of the plurality of item confidence values, wherein the plurality of item confidence values indicate relevance of respective data items to current context information, and wherein obtaining the plurality of item confidence values based on the comparison of the model confidence values comprises: identifying a subset of the first plurality of data items, wherein the subset corresponds to a plurality of data items received from a first data model, wherein the subset is associated with a respective plurality of item confidence values, and wherein the first data model is associated with a first model confidence value; and in accordance with a determination that the first model confidence value exceeds a model confidence threshold, increasing a weight of the respective plurality of item confidence values, wherein the obtained plurality of item confidence values includes the weighted plurality of item confidence values; identifying a second plurality of data items from the first plurality of data items, each data item of the second plurality of data items associated with an item confidence value exceeding a predetermined threshold value; identifying a display size of each data item of the second plurality of data items; selecting an arrangement of the second plurality of data items based on the identified display sizes; and displaying the selected arrangement of the second plurality of data items. identifying a first plurality of data items from a plurality of data models, wherein: each data model of the plurality of data models is associated with a model confidence value; and each data item of the first plurality of data items is previously selected by a user; each data model of the plurality of data models is associated with a model confidence value; and each data item of the first plurality of data items is previously selected by a user; obtaining a plurality of item confidence values based on a comparison of the model confidence values, wherein each data item of the first plurality of data items is associated with an item confidence value of the plurality of item confidence values, wherein the plurality of item confidence values indicate relevance of respective data items to current context information, and wherein obtaining the plurality of item confidence values based on the comparison of the model confidence values comprises: identifying a subset of the first plurality of data items, wherein the subset corresponds to a plurality of data items received from a first data model, wherein the subset is associated with a respective plurality of item confidence values, and wherein the first data model is associated with a first model confidence value; and in accordance with a determination that the first model confidence value exceeds a model confidence threshold, increasing a weight of the respective plurality of item confidence values, wherein the obtained plurality of item confidence values includes the weighted plurality of item confidence values; identifying a subset of the first plurality of data items, wherein the subset corresponds to a plurality of data items received from a first data model, wherein the subset is associated with a respective plurality of item confidence values, and wherein the first data model is associated with a first model confidence value; and in accordance with a determination that the first model confidence value exceeds a model confidence threshold, increasing a weight of the respective plurality of item confidence values, wherein the obtained plurality of item confidence values includes the weighted plurality of item confidence values; identifying a second plurality of data items from the first plurality of data items, each data item of the second plurality of data items associated with an item confidence value exceeding a predetermined threshold value; identifying a display size of each data item of the second plurality of data items; selecting an arrangement of the second plurality of data items based on the identified display sizes; and displaying the selected arrangement of the second plurality of data items.