Abstract: Systems and methods to select recipes for a customer. A request for at least one recipe is received for a customer. A plurality of questions are dynamically presented to the customer. This dynamic presentation of questions includes: selecting a next question from a dynamic-question-selection data structure based on a previous question presented to the customer and a previous answer received from the customer; presenting the next question to the customer; and receiving a next answer to the next question from the customer. A plurality of recipe attributes associated with the plurality of questions presented to the customer are identified. A group of initial recipes are selected from a plurality of recipes for the customer based on the plurality of recipe attributes. The at least one recipe for the customer is selected from the group of initial recipes and provided to the customer.

Abstract: Systems and methods to dynamically modify recipes for customers based actions while previously preparing other recipes. A first recipe is presented to a customer and images of the customer preparing the first recipe are captured. The images are analyzed to determine an action of the customer. A recipe characteristic associated with the action is determined based on the analysis of the images. A second recipe later selected for the customer, wherein the second recipe includes the determined recipe characteristic. The second recipe is modified to include a modification to the determined recipe characteristic based on the action of the customer when preparing the first recipe, and the modified second recipe is presented to the customer.

Abstract: Systems and methods to predict and optimize automated recipe selection and item delivery for a customer. A server uses an artificial intelligence model to selects a plurality of predicted recipes for a customer based on customer preferences. Different types of constraints are obtained for the customer to generate a plurality of sets of recipes from the predicted recipes and to optimize those sets of recipes for the customer. A specific set of recipes is selected for the customer based on the optimization, and the filling of the order is initiated for the customer with items associated with the selected set of recipes.

Abstract: Systems and methods to predict and optimize automated recipe selection and item delivery for a customer. An item-selection server selects a plurality of predicted recipes based on customer preferences and order history. Hard and soft constraints are obtained to perform the optimization of the predicted recipes. The hard constraints define parameters that cannot be violated by a recipe or set of recipes, and soft constraints define parameters that expresses a tradeoff value associated with a recipe or set of recipes. Optimization includes selecting multiple sets of predicted recipes based on the hard constraints and scoring each recipe set based on the soft constraints, item inventory, and customer preferences. A specific set of recipes is selected for the order based on the scores, and the filling of the order is initiated for the customer with items associated with the selected set of recipes.

Abstract: Embodiments are disclosed that relate to exposing metadata relationships through filter interplay. One embodiment provides a method comprising filtering a collection of items according to a first and a second metadata category to form an original subset of items that comprise metadata values for each of the categories. The method further comprises displaying a first and a second interactive filter view illustrating the original subset arranged according to their respective metadata values. The method further comprises receiving user input modifying an original range of metadata values of the first metadata category to form a modified range, determining a modified subset of items that comprise metadata values of the first metadata category falling within the modified range and that also comprise metadata values of the second metadata category, and modifying the second interactive filter view to illustrate the modified subset.

Abstract: Architecture for comparing images by building an initial map from the average color and an inserted blackened area. Accordingly, a map can be built that is more information-rich and smaller, thereby making the system more efficient. The architecture employs a Kohonen neural network (or self-organizing map (SOM)) by guiding the learning of the SOM using characteristics of the images such as average color and a central area. A strong component of the average color of the image and the central area at the approximate center of the image are added to the uninitialized SOM, which allows related colors to converge toward the central area of the image. When input, the SOM organizes the color content of the image on a map, which can be used to compare the image with other images.

Abstract: Embodiments are disclosed that relate to exposing metadata relationships through filter interplay. One embodiment provides a method comprising filtering a collection of items according to a first and a second metadata category to form an original subset of items that comprise metadata values for each of the categories. The method further comprises displaying a first and a second interactive filter view illustrating the original subset arranged according to their respective metadata values. The method further comprises receiving user input modifying an original range of metadata values of the first metadata category to form a modified range, determining a modified subset of items that comprise metadata values of the first metadata category falling within the modified range and that also comprise metadata values of the second metadata category, and modifying the second interactive filter view to illustrate the modified subset.

Abstract: Embodiments related to the display of filtered data via a frequency distribution are disclosed. One embodiment provides filtering a collection based on a category to create a subset of the collection, wherein the subset comprises one or more items each having metadata corresponding to the category and a value associated with the metadata. The method further includes ranking the subset based on the values associated with the metadata, determining lower and upper endpoints of the values, determining a range of the subset, and sending to a display a user interface object comprising a frequency distribution and a slider object indicating a selected portion of the range. The method further includes sending to a results portion of the display one or more items of the subset having values associated with the metadata which fall within the selected portion of the range.

Abstract: Methods, apparati, and computer-readable media for matching patterns of symbols within computer systems. A method embodiment of the present invention comprises composing (11) a pattern matching expression; and embedding (12) a function using storage means within the expression to form a character matching string. The expression may be a regular expression. The character matching string is compared (13) against a target string. The target string may be one that is suspected to contain malicious computer code.

Abstract: Architecture for comparing images by building an initial map from the average color and an inserted blackened area. Accordingly, a map can be built that is more information-rich and smaller, thereby making the system more efficient. The architecture employs a Kohonen neural network (or self-organizing map (SOM)) by guiding the learning of the SOM using characteristics of the images such as average color and a central area. A strong component of the average color of the image and the central area at the approximate center of the image are added to the uninitialized SOM, which allows related colors to converge toward the central area of the image. When input, the SOM organizes the color content of the image on a map, which can be used to compare the image with other images.

Abstract: This invention is a luggage construction allowing luggage to be slid, rather than the carried or dragged, up and down stairs. The essence of this invention is the combination of a super extendable/angleable pull handle, fixable in the angled position, with a smooth sliding surface on the stair resting face of the luggage body. The handle, super extended and locked in the angled position, is capable of being gripped comfortably by the user at hip level as the bag is being slid up the stairs. The smooth sliding surface removes protrusions from the bag face which slides along the points of the stairs. A brake device is added to prevent the bag from sliding out of control if it is accidentally released by the user.