Abstract: Various aspects described herein are directed to different techniques for enabling ad server systems to dynamically determine minimum floor prices for individual incoming impressions, in which the determination of the minimum floor value for a given incoming impression may be based upon the value(s) of specifically identified impression parameters associated with that particular impression. Additional aspects are directed to various feedback techniques for measuring the effectiveness of the various Entity-based and/or Segment-based floors, and for dynamically adjusting various floor computation parameter values based on measured floor metrics and heuristics.

Abstract: Various aspects described herein are directed to different techniques for enabling ad server systems to dynamically determine minimum floor prices for individual incoming impressions, in which the determination of the minimum floor value for a given incoming impression may be based upon the value(s) of specifically identified impression parameters associated with that particular impression. Additional aspects are directed to various feedback techniques for measuring the effectiveness of the various Entity-based and/or Segment-based floors, and for dynamically adjusting various floor computation parameter values based on measured floor metrics and heuristics.

Abstract: Various aspects described herein are directed to different techniques for enabling ad server systems to dynamically determine minimum floor prices for individual incoming impressions, in which the determination of the minimum floor value for a given incoming impression may be based upon the value(s) of specifically identified impression parameters associated with that particular impression. Additional aspects are directed to various feedback techniques for measuring the effectiveness of the various Entity-based and/or Segment-based floors, and for dynamically adjusting various floor computation parameter values based on measured floor metrics and heuristics.

Abstract: Various aspects described herein are directed to different techniques for enabling ad server systems to dynamically determine minimum floor prices for individual incoming impressions, in which the determination of the minimum floor value for a given incoming impression may be based upon the value(s) of specifically identified impression parameters associated with that particular impression. Additional aspects are directed to various feedback techniques for measuring the effectiveness of the various Entity-based and/or Segment-based floors, and for dynamically adjusting various floor computation parameter values based on measured floor metrics and heuristics.

Abstract: Various aspects described herein are directed to different techniques for enabling ad server systems to dynamically determine minimum floor prices for individual incoming impressions, in which the determination of the minimum floor value for a given incoming impression may be based upon the value(s) of specifically identified impression parameters associated with that particular impression. Additional aspects are directed to various feedback techniques for measuring the effectiveness of the various Entity-based and/or Segment-based floors, and for dynamically adjusting various floor computation parameter values based on measured floor metrics and heuristics.

Abstract: A system is described for generating query suggestions using a network of users and advertisers. The system may include a memory, an interface, and a processor. The memory may store a data representing a network comprising query items linked to advertisement items via link items, wherein each link item comprises a weight representing the strength of the relationship between each query item and advertisement item, a search query item, and a relevance value for each query item. The processor may be operatively connected to the memory and the interface and may identify the data representing the network and receive a search query item. The processor may calculate a relevance value for each additional query item in the network based on its relationship to the received search query item. The processor may then suggest the query items with the highest relevance values to the user via the interface.

Abstract: A system is described for generating query suggestions by integrating valuable query suggestions with experimental query suggestions using a network of users and advertisers. The system may include a memory, an interface, and a processor. The memory may store a historical dataset, a plurality of query suggestions, a plurality of query suggestion values, a query exploit set, a query explore set, and a data describing a network. The processor may identify the plurality of query suggestions in the historical dataset and generate data describing the network based on the historical dataset. The processor may calculate the query suggestion value for each query suggestion and may rank the query suggestions based on the query suggestion values. The processor may generate an exploit set comprising the top ranked query suggestions and an explore set comprising the remainder. The processor may suggest the query suggestions in the exploit set and the explore set.

Abstract: A system is described for optimizing the performance of online advertisements using a network of users and advertisers. The system may include a memory, an interface, and a processor. The memory may store a data representing a network comprised of queries linked to advertisements, a search query, a relevance value for each query, and a predicted weight for each advertisement. The interface may communicate with a plurality of users. The processor may be operatively connected to the memory and interface and may identify the network, and receive a query from a user, wherein the query exists in the network. The processor may calculate relevance values for the queries and use the queries with the highest relevance values to calculate a weight for each advertisement, the weight representing the relevance of the advertisement to the search query. The processor may then serve the advertisements with the highest weights to the user.

Abstract: A system is described for generating query suggestions by integrating valuable query suggestions with experimental query suggestions using a network of users and advertisers. The system may include a memory, an interface, and a processor. The memory may store a historical dataset, a plurality of query suggestions, a plurality of query suggestion values, a query exploit set, a query explore set, and a data describing a network. The processor may identify the plurality of query suggestions in the historical dataset and generate data describing the network based on the historical dataset. The processor may calculate the query suggestion value for each query suggestion and may rank the query suggestions based on the query suggestion values. The processor may generate an exploit set comprising the top ranked query suggestions and an explore set comprising the remainder. The processor may suggest the query suggestions in the exploit set and the explore set.

Abstract: A system is described for determining the quality of query suggestions using a network of users and advertisers. The system may include a memory and a processor. The memory may store a historical dataset, a residual value, a query-advertisement link value, a query suggestion value, and a data representing a network. The network may comprise a plurality of query items linked to a plurality of advertisement items via a plurality of query-advertisement link items. The processor may generate data representing the network and may identify a query-advertisement link item in the network. The processor may calculate the residual value of the query suggestion system represented by the match type of the query-advertisement link item. The processor may calculate the query-advertisement link value. The processor may add the residual value to the query-advertisement link value to determine a query suggestion value and may store the query suggestion value in the memory.

Abstract: A system is described for generating query suggestions using a network of users and advertisers. The system may include a memory, an interface, and a processor. The memory may store a data representing a network comprising query items linked to advertisement items via link items, wherein each link item comprises a weight representing the strength of the relationship between each query item and advertisement item, a search query item, and a relevance value for each query item. The processor may be operatively connected to the memory and the interface and may identify the data representing the network and receive a search query item. The processor may calculate a relevance value for each additional query item in the network based on its relationship to the received search query item. The processor may then suggest the query items with the highest relevance values to the user via the interface.

Abstract: A system is described for determining the quality of query suggestion systems using a network of users and advertisers. The system may include a memory and a processor. The memory may store data representing a plurality of query suggestion systems, a historical dataset, a plurality of residual values, and a data representing a network. The network may comprise a plurality of query items representing queries linked to a plurality of advertisement items representing advertisements via a plurality of query-advertisement link items. The processor may retrieve the historical dataset and generate the data representing the network. The processor may calculate the residual values for each query suggestion system in the plurality of query suggestion systems. The residual value may represent a value attributable to the query suggestions generated by a given query suggestion system. The processor may store the residual value of each query suggestion in the memory.

Abstract: A system is described for building a data structure representing a network of advertisers and users. The system may include a memory and a processor. The memory may be operatively connected to the processor and may store a historical dataset comprising of a plurality of query items and advertisement items, a plurality of query-advertisement link items, a weight, a data structure and a condition. The processor may identify the historical dataset, and link the query items to the advertisement items to generate query-advertisement link items. The processor may determine the weight of each query-advertisement link item and may store the query-advertisement link items and the weight in the data structure if the query-advertisement link item satisfies the condition.

Abstract: An impression graph is generated comprising keywords as nodes on a first side of the impression graph and advertisement listing as nodes on a second side of the impression graph, an impression relationship between a given keyword and a given advertisement listing represented by an impression edge connection. A click graph is also generated comprising keywords as nodes on a first side of the click graph and advertisement listing as nodes on a second side of the click graph, a relationship between a given keyword and a given advertisement listing represented by a click edge connection. A mapping function is applied to calculate one or more weights for a given edge in the impression graph and the click graph and the one or more edge weights, the impression graph and the click graph are transformed into a unified bipartite graph.