Abstract: A secure inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels, as well as a consumer profile data store holding consumer-product purchase event information for each channel. The system also includes a channel manager user interface via which the system will receive a consumer identifier from a channel manager user for a first channel, identify products that are in an inventory of the first channel, and use the consumer profile data to generate recommendations for products in the inventory. At least some of the consumers, and at least some of the products, will be associated with multiple channels. The system maintains security and privacy of information so that only aggregate supplier information is shared across channels, and no personally identifiable consumer information is shared with anyone who is not authorized to access the information.

Abstract: An inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels. The system also includes a channel manager user interface via which the system will receive data for a new product listing. The system will automatically populate the new product listing with additional data for the new product. The system will save the new product listing in association with a channel and channel-specific information for the channel. Then, when a user views the new product information, the system will ensure that the system only views channel-specific information that is associated with the product if the user is subscribed to that channel.

Abstract: A secure inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels, as well as a consumer profile data store holding consumer-product purchase event information for each channel. The system also includes a channel manager user interface via which the system will receive a consumer identifier from a channel manager user for a first channel, identify products that are in an inventory of the first channel, and use the consumer profile data to generate recommendations for products in the inventory. At least some of the consumers, and at least some of the products, will be associated with multiple channels. The system maintains security and privacy of information so that only aggregate supplier information is shared across channels, and no personally identifiable consumer information is shared with anyone who is not authorized to access the information.

Abstract: A secure inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels, as well as a consumer profile data store holding consumer-product purchase event information for each channel. The system also includes a channel manager user interface via which the system will receive a consumer identifier from a channel manager user for a first channel, identify products that are in an inventory of the first channel, and use the consumer profile data to generate recommendations for products in the inventory. At least some of the consumers, and at least some of the products, will be associated with multiple channels. The system maintains security and privacy of information so that only aggregate supplier information is shared across channels, and no personally identifiable consumer information is shared with anyone who is not authorized to access the information.

Abstract: A secure inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels, as well as a consumer profile data store holding consumer-product purchase event information for each channel. The system also includes a channel manager user interface via which the system will receive a consumer identifier from a channel manager user for a first channel, identify products that are in an inventory of the first channel, and use the consumer profile data to generate recommendations for products in the inventory. At least some of the consumers, and at least some of the products, will be associated with multiple channels. The system maintains security and privacy of information so that only aggregate supplier information is shared across channels, and no personally identifiable consumer information is shared with anyone who is not authorized to access the information.

Abstract: A secure inventory management system includes a product information data store that holds inventory information for products that are associated with one or more channels, as well as a consumer profile data store holding consumer-product purchase event information for each channel. The system also includes a channel manager user interface via which the system will receive a consumer identifier from a channel manager user for a first channel, identify products that are in an inventory of the first channel, and use the consumer profile data to generate recommendations for products in the inventory. At least some of the consumers, and at least some of the products, will be associated with multiple channels. The system maintains security and privacy of information so that only aggregate supplier information is shared across channels, and no personally identifiable consumer information is shared with anyone who is not authorized to access the information.

Abstract: A personal taste assessment system recommends a consumable or other item. The system accesses a preference model for the representing associations between a person's ratings of items and a set of item characteristics. The system uses the preference model and an item database that contains characteristic values for a group of items to identify a candidate item having characteristics that correspond to traits that the person found to be appealing, and which may be chemically sensed. The system then causes an electronic device to output an identification of the candidate item.

Abstract: A personal taste assessment system recommends a consumable or other item. The system develops a preference model for the representing associations between a person's ratings of items and a set of item characteristics. The system uses the preference model and an item database that contains characteristic values for a group of items to identify a candidate item having characteristics that correspond to traits that the person found to be appealing. The system then causes an electronic device to output an identification of the candidate item.

Abstract: A personal taste assessment system recommends and predicts a person's preference for a consumable or other item. The system accesses a user profile for a person. The user profile includes a preference model representing associations between the person's ratings of items and a set of item characteristics. The system also accesses a database of characteristic values for a group of items, uses the identifying information to identify a candidate item having characteristic values whose properties match characteristics associated with the rated items that the person found to be appealing, and processes the characteristic values of the candidate item with the user profile to generate a predicted rating as a prediction of how the person would rate the identified candidate item. The system then causes an electronic device to output an identification of the candidate item and the predicted rating.

Abstract: This document describes a method and system for recommending items, such as beverages, that members of a group are likely to find appealing. When group members are identified, the system may identify one or more preference models for each member. Each preference model represents a pattern of dependency between characteristics of items that the member has rated and the member's ratings for those items. The system may develop a group preference profile by merging the patterns of dependency for each of the members into a group preference model. Then, when it receives a request for a recommendation for an item, the system uses the group preference profile to select, from a database, a candidate item having characteristics which are likely to appeal to many or all members of the group.

Abstract: This document describes a method and system for recommending items, such as beverages, that members of a group are likely to find appealing. When group members are identified, the system may identify one or more preference models for each member. Each preference model represents a pattern of dependency between characteristics of items that the member has rated and the member's ratings for those items. The system may develop a group preference profile by merging the patterns of dependency for each of the members into a group preference model. Then, when it receives a request for a recommendation for an item, the system uses the group preference profile to select, from a database, a candidate item having characteristics which are likely to appeal to many or all members of the group.

Abstract: This document describes a method and system for recommending items, such as beverages, that members of a group are likely to find appealing. When group members are identified, the system may identify one or more preference models for each member. Each preference model represents a pattern of dependency between characteristics of items that the member has rated and the member's ratings for those items. The system may develop a group preference profile by merging the patterns of dependency for each of the members into a group preference model. Then, when it receives a request for a recommendation for an item, the system uses the group preference profile to select, from a database, a candidate item having characteristics which are likely to appeal to many or all members of the group.

Abstract: A personal taste assessment system recommends and predicts a person's preference for a consumable or other item. The system accesses a user profile for a person. The user profile includes a preference model representing associations between the person's ratings of items and a set of item characteristics. The system also accesses a database of characteristic values for a group of items, uses the identifying information to identify a candidate item having characteristic values whose properties match characteristics associated with the rated items that the person found to be appealing, and processes the characteristic values of the candidate item with the user profile to generate a predicted rating as a prediction of how the person would rate the identified candidate item. The system then causes an electronic device to output an identification of the candidate item and the predicted rating.

Abstract: A personal taste assessment and prediction system implements a method of predicting a person's preference for an item. The system may receive identifying information about an item of interest, and it may use the identifying information to access a database of characteristic values for various items and identify one or more characteristics of the item of interest. The system will access a user profile and process the retrieved characteristics with a user profile for a person to generate a predicted rating for the item of interest for the person.

Abstract: A personal taste assessment system receives a person's ratings for various rated items, such as wines or other beverages, and it develops a preference model for the person based on the received ratings. When developing the preference model, the system accesses a database of candidate items, wherein each candidate item is associated with at least one trait value. The system retrieves from the database a value for at least one trait for each of the rated items, identifies at least one pattern of dependency between at least one of the retrieved trait values and at least one of the received ratings, and determines a preference model based on the at least one pattern of dependency. The system may use the preference model to develop a preference profile for the person, make recommendations, and/or make predictions as to items that the person and/or a group that includes the person may enjoy.

Abstract: A personal taste assessment and prediction system implements a method of predicting a person's preference for an item. The system may receive identifying information about an item of interest, and it may use the identifying information to access a database of characteristic values for various items and identify one or more characteristics of the item of interest. The system will access a user profile and process the retrieved characteristics with a user profile for a person to generate a predicted rating for the item of interest for the person.

Abstract: This document describes a method and system for recommending items, such as beverages, that members of a group are likely to find appealing. When group members are identified, the system may identify one or more preference models for each member. Each preference model represents a pattern of dependency between characteristics of items that the member has rated and the member's ratings for those items. The system may develop a group preference profile by merging the patterns of dependency for each of the members into a group preference model. Then, when it receives a request for a recommendation for an item, the system uses the group preference profile to select, from a database, a candidate item having characteristics which are likely to appeal to many or all members of the group.

Abstract: A personal taste assessment system receives a person's ratings for various rated items, such as wines or other beverages, and it develops a preference model for the person based on the received ratings. When developing the preference model, the system accesses a database of candidate items, wherein each candidate item is associated with at least one trait value. The system retrieves from the database a value for at least one trait for each of the rated items, identifies at least one pattern of dependency between at least one of the retrieved trait values and at least one of the received ratings, and determines a preference model based on the at least one pattern of dependency. The system may use the preference model to develop a preference profile for the person, make recommendations, and/or make predictions as to items that the person and/or a group that includes the person may enjoy.

Abstract: A personal taste assessment system receives a person's ratings for various rated items, such as wines or other beverages, and it develops a preference model for the person based on the received ratings. When developing the preference model, the system accesses a database of candidate items, wherein each candidate item is associated with at least one trait value. The system retrieves from the database a value for at least one trait for each of the rated items, identifies at least one pattern of dependency between at least one of the retrieved trait values and at least one of the received ratings, and determines a preference model based on the at least one pattern of dependency. The system may use the preference model to develop a preference profile for the person, make recommendations, and/or make predictions as to items that the person and/or a group that includes the person may enjoy.

Abstract: A personal taste assessment system receives a person's ratings for various rated items, such as wines or other beverages, and it develops a preference model for the person based on the received ratings. When developing the preference model, the system accesses a database of candidate items, wherein each candidate item is associated with at least one trait value. The system retrieves from the database a value for at least one trait for each of the rated items, identifies at least one pattern of dependency between at least one of the retrieved trait values and at least one of the received ratings, and determines a preference model based on the at least one pattern of dependency. The system may use the preference model to develop a preference profile for the person, make recommendations, and/or make predictions as to items that the person and/or a group that includes the person may enjoy.