Abstract: An advertiser specifies a conversion-based bid for a conversion event associated with an ad. If a conversion event occurs for the ad, an effective conversion-based bid can be adjusted by a risk premium associated with the ad. An account associated with the advertiser can be debited based upon the adjusted effective conversion-based bid.

Abstract: An advertiser specifies a conversion-based bid for a conversion event associated with an ad. If a conversion event occurs for the ad, an effective conversion-based bid can be adjusted by a risk premium associated with the ad. An account associated with the advertiser can be debited based upon the adjusted effective conversion-based bid.

Abstract: Methods, systems, and apparatus, including computer program products, that can include receiving from an advertiser a request for billing based on a first measure of services, determining from quality data related to the advertiser whether the first measure of services can be converted with sufficient confidence to a second measure of services, providing services according to the first measure of services, monitoring stability data indicative of the stability of the relationship between the first measure of services and the second measure of services, and automatically switching from one to another mode of determining a price to be charged the customer for services provided.

Abstract: Methods, systems, and apparatus, including computer program products, that can include receiving from an advertiser a request for billing based on a first measure of services, determining from quality data related to the advertiser whether the first measure of services can be converted with sufficient confidence to a second measure of services, providing services according to the first measure of services, monitoring stability data indicative of the stability of the relationship between the first measure of services and the second measure of services, and automatically switching from one to another mode of determining a price to be charged the customer for services provided.

Abstract: Methods, systems, and apparatus, including computer program products, for determining a probability that a traffic conversion of a content item associated with a content source (e.g., website) will occur based on past traffic patterns for that content source. A traffic conversion defines, for example, minimum traffic interactions of one or more associated user sessions with a content source. The minimum traffic interactions can be based on, for example, the duration of the one or more user sessions on the content source, or a quantity of pages associated with the content source navigated in the one or more associated user sessions.

Abstract: A learning model is built on a combination of advertiser, publisher and user data. The learning model can be applied to all advertisers in an advertising system. The learning model provides predicted conversion rates for a given advertisement (“ad”) appearing on different publisher networks. A predicted conversion rate represents the probability that a click on a given ad appearing on a given publisher will lead to a conversion. The predicted conversion rates are used to generate a multiplier. The multiplier is used to automatically adjust the advertiser's bid (e.g., maximum cost-per-click (CPC)) for the given ad prior to an auction for the ad. Adjusting the advertiser's bid equalizes a cost-per-conversion among the publishers for the ad.

Abstract: Systems, methods, and computer programs encoded on a computer-readable storage medium for allocating a minimum number of impressions to a content item in order to satisfy a delivery goal for the content item during a certain period of time are described. In some implementations, a satisfaction index (SI) for each content item can be used. The SI is a metric that reflects the degree to which a content selection service is on pace to meet a delivery goal for a content item within some period. The SI can be used to compare the number of impressions that have been allocated to the content item thus far in a period to the delivery or allocation goal for the content item in the period. A content selection service may determine scores for impression allocations based on both an estimate of value and the SI for a candidate content item in order to balance the goals of meeting delivery goals and optimizing impression inventory value.

Abstract: A predicted performance metric of a candidate advertisement in an advertising slot can be received and compared to a baseline predicted performance metric for the candidate advertisement. A target bid associated with the candidate advertisement can be adjusted based upon the comparison, and the adjusted bid can be submitted to an auction for the advertising slot.

Abstract: A learning model is built on a combination of advertiser, publisher and user data. The learning model can be applied to all advertisers in an advertising system. The learning model provides predicted conversion rates for a given advertisement (“ad”) appearing on different publisher networks. A predicted conversion rate represents the probability that a click on a given ad appearing on a given publisher will lead to a conversion. The predicted conversion rates are used to generate a multiplier. The multiplier is used to automatically adjust the advertiser's bid (e.g., maximum cost-per-click (CPC)) for the given ad prior to an auction for the ad. Adjusting the advertiser's bid equalizes a cost-per-conversion among the publishers for the ad.

Abstract: An advertiser specifies a conversion-based bid for a conversion event associated with an ad. If a conversion event occurs for the ad, an effective conversion-based bid can be adjusted by a risk premium associated with the ad. An account associated with the advertiser can be debited based upon the adjusted effective conversion-based bid.

Abstract: Methods, systems, and apparatus, including computer program products, for determining a probability that a traffic conversion of a content item associated with a content source (e.g., website) will occur based on past traffic patterns for that content source. A traffic conversion defines, for example, minimum traffic interactions of one or more associated user sessions with a content source. The minimum traffic interactions can be based on, for example, the duration of the one or more user sessions on the content source, or a quantity of pages associated with the content source navigated in the one or more associated user sessions.

Abstract: A predicted performance metric of a candidate advertisement in an advertising slot can be received and compared to a baseline predicted performance metric for the candidate advertisement. A target bid associated with the candidate advertisement can be adjusted based upon the comparison, and the adjusted bid can be submitted to an auction for the advertising slot.

Abstract: Automated methods are provided for the editing and authoring of topic scripts for the dynamic operation of virtual robots. A virtual robot, or BOT, processes natural language input from a user to effect certain actions according to user input. Typically, BOTs are constructed using topic scripts. Topic scripts may comprise example statements that typify the topic in question and patterns that are matched against user input to determine if the topic is activated by the user input.

Abstract: A virtual robot (or BOT) is disclosed that interfaces and automatically interacts with users desiring to be guided or informed about certain aspects or features of the entity with which they are interacting. Several mechanisms are further disclosed that aid the effectiveness of that interaction. Mechanisms to focus the attention of the BOT on certain aspects of the interaction or communication are disclosed. These mechanisms can be made explicitly or can be performed automatically. Mechanisms are disclosed to aid the BOT to automatically learn from its interactions with users to increase the effectiveness of the interaction.

Abstract: An automated interface program designed to interact and communicate with users, is disclosed that defines a list of categories activatable by the program; identifies a set of categories activated by user input; selects another set of categories from the activated categories based upon a metric and thereafter executes actions associated with the selected categories. The metric is a computed value based on conditions located within each category. The metric gives an estimate of the appropriateness of the particular response included in an activated category. This estimate is currently based on the current input and the current state of the automated interface program at the time user input is entered.

Abstract: In an automated interface program designed to interact and communicate with users, said program executing actions when a category among a predefined set of categories is activated, a method is disclosed for automatically verifying the performance of said program, the steps of said method comprising: specifying inputs under which the program should be tested; associating said inputs with conditions within categories in the program, each said condition comprising at least one response which could be given if said condition is satisfied; executing said program under at least one said input; determining whether the associated condition is satisfied upon said input; and determining whether the response associated with said condition is given upon said input. In another aspect of the present invention, the test inputs are embedded within the script itself, and specifically, within categories that can be automatically listed upon compilation of the script.

Abstract: A virtual robot (or BOT) is disclosed that interfaces and automatically interacts with users desiring to be guided or informed about certain aspects or features of the entity with which they are interacting. Several mechanisms are further disclosed that aid the effectiveness of that interaction. Mechanisms to focus the attention of the BOT on certain aspects of the interaction or communication are disclosed. These mechanisms can be made explicitly or can be performed automatically. Mechanisms are disclosed to aid the BOT to automatically learn from its interactions with users to increase the effectiveness of the interaction.

Abstract: In an automated interface program designed to interact and communicate with users, said program executing actions when a category among a predefined set of categories is activated, a method is disclosed for automatically verifying the performance of said program, the steps of said method comprising: specifying inputs under which the program should be tested; associating said inputs with conditions within categories in the program, each said condition comprising at least one response which could be given if said condition is satisfied; executing said program under at least one said input; determining whether the associated condition is satisfied upon said input; and determining whether the response associated with said condition is given upon said input. In another aspect of the present invention, the test inputs are embedded within the script itself, and specifically, within categories that can be automatically listed upon compilation of the script.

Abstract: A virtual robot (or BOT) is disclosed that interfaces and automatically interacts with users desiring to be guided or informed about certain aspects or features of the entity with which they are interacting. Several mechanisms are further disclosed that aid the effectiveness of that interaction. Mechanisms to focus the attention of the BOT on certain aspects of the interaction or communication are disclosed. These mechanisms can be made explicitly or can be performed automatically. Mechanisms are disclosed to aid the BOT to automatically learn from its interactions with users to increase the effectiveness of the interaction.

Abstract: In an automated interface program designed to interact and communicate with users, said program executing actions when a category among a predefined set of categories is activated, a method is disclosed for interpreting the context of a user input, the steps of said method comprising: associating subjects with categories; maintaining a list of the subjects associated with the most recently activated category; testing conditions in categories such that the condition is true if the comprises at least one subject in common with said list of subjects; and activating a set of categories, said set comprising those categories whose conditions are satisfied based on the list of subjects.