City of San Diego Administrative Social/Manpower Programs Sports Club/Manager/Promoter
9449 Friars Rd, San Diego, CA 92108
Kevin Haley Chief Financial Officer
The Pennsylvania State University College/University · General Hospital College/University · Physical Fitness Facility College/University · Univeristy · Medical Doctor's Office College/University · Accounting/Auditing/Bookkeeping College/University · Medical Doctor's Office · Health Practitioner's Office
Kevin C. Haley - Austin TX, US Robert A. Luenberger - Palo Alto CA, US
Assignee:
AOL Advertising, Inc. - Baltimore MD
International Classification:
G06Q 30/00
US Classification:
705 141
Abstract:
Systems and methods relate to frequency of advertisement viewing on the Internet, and more specifically to controlling advertisement viewings by a person during an advertising cycle. A probability of return for a customer is evaluated and an advertisement is shown to the customer based on a function of at least the probability of return and a value for the return. Once the customer has seen the advertisement a target number of times, the customer is no longer shown the advertisement.
Systems And Methods For Providing A Reverse Frequency Cap In Advertisement Viewing
Kevin C. Haley - Austin TX, US Robert A. Luenberger - Palo Alto CA, US
Assignee:
AOL Advertising Inc. - New York NY
International Classification:
G06Q 30/00
US Classification:
705 141
Abstract:
Systems and methods relate to frequency of advertisement viewing on the Internet, and more specifically to controlling advertisement viewings by a person during an advertising cycle. A probability of return for a customer is evaluated and an advertisement is shown to the customer based on a function of at least the probability of return and a value for the return. Once the customer has seen the advertisement a target number of times, the customer is no longer shown the advertisement.
Dennis Paul MICHALOPOULOS - Austin TX, US Kevin Coates HALEY - The Hills TX, US Scott Andrew FERBER - Bethesda MD, US
International Classification:
G06Q 30/02
US Classification:
705 1466, 705 1449
Abstract:
A computer system and method for list-based advertisement serving are provided. In at least one embodiment, a computer system or method may comprise creating advertisement lists before runtime based on list generation data, wherein each of the advertisement lists is associated with a respective target audience definition. The computer system or method may also comprise allocating advertisements among the advertisement lists before runtime, based on the list generation data, to cause each advertisement list to include a prioritized sequence of advertisements.
Method And System For Forecasting Performance Of Persistent User Accounts
- Baltimore MD, US Kevin Coates HALEY - The Hills TX, US Aleck Howard Schleider - Reisterstown MD, US
International Classification:
G06Q 30/02
Abstract:
The present teaching relates to method, system, and medium for obtaining consumption data. A first request is received to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, each account is represented by a persistent identifier that links multiple identifiers associated with one or more devices, or platforms on which content is consumed in at least one media type. Information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account is retrieved, and a data set of the account is provided based on information retrieved with respect to each of the linked multiple identifiers. The data set is presented in one representation upon a request for information about the account and retrieved data sets are provided in response to the first request, for forecasting performance of audience clusters.
Method And System For Persistent Account Generation And Profiling
- Baltimore MD, US Kevin Coates HALEY - The Hills TX, US Aleck Howard Schleider - Reisterstown MD, US
International Classification:
G06Q 30/02
Abstract:
The present teaching relates to method, system, and medium for profiling accounts. A plurality of identifiers are obtained, wherein each of the plurality of identifiers is associated with one of a device operated by a user and a platform on which the user consumes content in one or more media types. An account corresponding to the user is created, wherein the account represents the user across devices, platforms, and/or media types. A persistent identifier is generated for the account, wherein the persistent identifier links the plurality of identifiers. Consumption data related to the account with the persistent identifier is obtained. The consumption data is gathered from sources associated with the plurality of identifiers across different devices, platforms, or media types, and the account is profiled based on the obtained consumption data.
Method And System For Optimized Content Item Allocation
- Baltimore MD, US Kevin Coates HALEY - The Hills TX, US
International Classification:
G06Q 30/02 G06F 17/30
Abstract:
The present teaching relates to method, system, and medium for allocating advertisements. An advertisement associated with first criteria is received. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is associated with second criteria and ordered audience clusters that are previously generated for the advertisement exposure opportunity. A predicted performance of each of the ordered audience clusters associated with each of the plurality of advertisement exposure opportunities is obtained, wherein the predicted performance is estimated with respect to the first criteria. At least one audience cluster is identified that is associated with one or more advertisement exposure opportunities based on the first and second criteria as well as the predicted performance associated with the ordered audience clusters of the plurality of advertisement exposure opportunities. The advertisement is allocated to the at least one audience cluster.
Method And System For Forecasting Performance Of Audience Clusters
- Baltimore MD, US Kevin Coates Haley - The Hills TX, US
International Classification:
G06Q 30/02 G06F 17/30 G06N 5/02
Abstract:
The present teaching relates to method, system, and medium for predicting performance of an audience cluster. First information related to a plurality of users in the audience cluster is received. A plurality of advertisements are received that are previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria. Second information related to events involving the plurality of users with respect to the plurality of advertisements is obtained and performance of the audience cluster associated with the advertisement exposure opportunity is predicted based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria. The predicted performance of the audience cluster is used for ordering a plurality of audience clusters associated with the advertisement exposure opportunity.
Method And System For Generating Audience Clusters
- Baltimore MD, US Kevin Coates HALEY - The Hills TX, US
International Classification:
G06Q 30/02 G06F 17/30
Abstract:
The present teaching relates to method, system, and medium for determining audience clusters to be assigned to an advertisement exposure opportunity. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is to be used for placing an advertisement. For each of the plurality of advertisement exposure opportunities, a plurality of audience clusters are generated based on at least one criterion associated with the advertisement exposure opportunity. The plurality of audience clusters are ranked based on at least one ranking criterion, and ordered audience clusters are generated based on the ranking. The ordered audience clusters associated with the plurality of advertisement exposure opportunities in response to an event are updated, wherein the ordered audience clusters for each of the plurality of advertisement exposure opportunities are generated prior to receiving a request for placing the advertisement.
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