Abstract: The present disclosure is directed to systems, methods and devices for replacing a static map image with an interactive map that approximates the geographic area depicted by the static map image. A static image may be inspected and a determination may be made as to whether the static image meets a map identification threshold value. At least one signal associated with the static image may be evaluated and based on that evaluation at least one geo-entity of intent may be identified. The static image may be replaced with a static image corresponding to at least one of the identified geo-entities of intent.

Abstract: The present disclosure is directed to systems, methods and devices for replacing a static map image with an interactive map that approximates the geographic area depicted by the static map image. A static image may be inspected and a determination may be made as to whether the static image meets a map identification threshold value. At least one signal associated with the static image may be evaluated and based on that evaluation at least one geo-entity of intent may be identified. The static image may be replaced with a static image corresponding to at least one of the identified geo-entities of intent.

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

Abstract: Techniques are described for generating an authority value of a first one of a plurality of documents. A first component of the authority value is generated with reference to outbound links associated with the first document. The outbound links enable access to a first subset of the plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents. Each of the second subset of documents represents a potential starting point for a user session. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the first document. The first, second, and third components of the authority value are combined to generate the authority value. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.

Abstract: Aspects of the present invention relate to providing search results on a map view for a multi-entity query. A search query submitted by a user may be received. A tile in a map may be identified based on the search query. Valid query patterns for the search query corresponding to entities on the identified tile may be determined. Potential scores for each of the determined valid query patterns may be calculated. Potential scores for the determined valid query patterns may be ordered. Actual scores for a plurality of the determined valid query patterns may be calculated.

Abstract: A geocoding architecture that generates and associates one or more tile documents with geocoded tiles. When connected entities are defined, the connected entity attributes are collected in a single tile document so that tile-document terms are attributes of all connected entities. These terms later serve as keys that enable search for tiles relevant for a given query. Entity documents are created that are an aggregation of entity attributes. Like the entity document, the tile document serves as an aggregator for all the geospatial entities within a pre-determined surface area. Search is then performed on the content of tile and entity documents.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

Abstract: Content is proactively presented to a user, to enable the user to more efficiently access such content. A user context is correlated to content that is likely to be subsequently accessed. One such a correlation is specific to a given user, while another such correlation is general to a collection, or class, of users. Correlations between a current user context and content subsequently accessed are based on historical data and are defined in terms of mathematical functions or semantic relationships. Such correlations are then utilized to identify content that is likely to be subsequently accessed, and such content is proactively presented to a user. A user interface provides a defined area within which proactive presentations of content are made, including while the user is utilizing other application programs.

Abstract: Embodiments of the invention relate to methods of presenting personalized search results pages to users, and to search engine systems and servers configured to implement such methods. For example, a method of presenting such a page to a user of a search engine includes steps of computing an engagement index of the user based on the distribution in time of that user's interactions with the search engine then presenting, in response to a query by the user, a personalized search results page to the user.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: An improved system and method for web destination profiling for online population-targeted advertising is provided. A web destination profiler may be provided for generating web destination profiles. Traffic may be analyzed at a particular web destination in order to understand the population visiting the web destination. The analysis of user traffic, including differentiated clickstream data, may be applied for determining known characteristics of a web destination profile. Moreover, unknown characteristics of a web destination profile may be determined using a variety of techniques including inferring characteristics by modeling traffic flow through other web destinations, estimating characteristics from other web destination profiles by predicting traffic flow through other web destinations, propagating characteristics to a web destination profile by smoothing a joint distribution of characteristics of other web destination profiles, and so forth.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Methods and systems for estimating the value of a contextual ad impression are provided. Requests for value-based bids for ad impressions are received from bidders and the value of the ad impression is estimated based primarily upon leveraging sell-side data (user and publisher). The estimation is highly economized through a fast implementation of k-nearest-neighbor (kNN) regression. Embodiments of the present invention further address the cold-start problem or the exploration vs. exploitation requirement by Bayesian (hierarchical) smoothing using a beta prior, and adapt to the temporal dynamics using an autoregressive model to decay importance of certain data.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Various embodiments pertain to techniques for generating advertisement templates for use in various technological environments. In various embodiments, an advertiser can select one or more advertisement templates and provide the specified components to an advertisement service. The advertisement service can bind the components into a selected template for presentation to a user, depending on a number of factors. For example, in some embodiments, the device capabilities can determine the template that is used, while in other embodiments, information regarding a user's previous interaction with the content can be used to determine the template that is used. For example, a user that is seeing an advertisement for a particular product for the first time may be presented one version of the advertisement, while a user that is already a consumer of the product or has already viewed an initial advertisement may be presented with a different version of the advertisement.

Abstract: An improved system and method for web destination profiling for online population-targeted advertising is provided. A web destination profiler may be provided for generating web destination profiles. Traffic may be analyzed at a particular web destination in order to understand the population visiting the web destination. The analysis of user traffic, including differentiated clickstream data, may be applied for determining known characteristics of a web destination profile. Moreover, unknown characteristics of a web destination profile may be determined using a variety of techniques including inferring characteristics by modeling traffic flow through other web destinations, estimating characteristics from other web destination profiles by predicting traffic flow through other web destinations, propagating characteristics to a web destination profile by smoothing a joint distribution of characteristics of other web destination profiles, and so forth.

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.