Abstract: Targeting parameters are generated for a media buy plan for advertisements to be displayed in conjunction with presenting web pages, based on a history of search events. Key phrases are received relative to a subject of the advertisements to be displayed. The received key phrases are provided as proposed key phrases to determine, from search events indicative of historical data of uses of a search service, a first subportion of search events for queries of the search service with the proposed key phrases and a second subportion of search events for queries of the search service not with the proposed key phrases. Classification processing is applied to determine potential targeting parameters associated with the first subportion and with the second subportion to identify potential targeting parameters that, statistically, contribute to membership in the first sub-population and in the second sub-population, respectively.

Abstract: Systems and methods for behavioral modeling to optimize shopping cart conversion are discussed. For example, a method can include identifying a user interacting with a networked system, accessing user profile data associated with the user, tracking user activity associated with the user, accessing a behavioral model, applying the behavioral model, and determining a shopping cart optimization. The behavioral model can be generated from historical data detailing interactions with the networked system. The behavioral model can be applied to the user profiled data and the user activity data to assist in selection of a shopping cart optimization.

Abstract: A computer-implemented method, which comprises the following: aggregating a plurality of records in accordance with an aggregation specification, wherein the records are part of a dimensionally-modeled fact collection; graphically representing the records in un-aggregated form; graphically representing the records in aggregated form; and causing the graphical representation of the records to be switched between aggregated form and un-aggregated form based on a user indication.

Abstract: Methods, systems, and apparatuses for determining parking availability are described. A sensor system is configured to monitor a plurality of parking spaces. The sensor system includes at least one sensor element that generates a sensor data output signal. A parking availability determiner receives the sensor data output signal and generates parking availability information. The parking availability determiner is configured to determine from the received sensor data output signal at least one parking space of the plurality of parking spaces that is occupied, and to include an indication in the parking availability information that the determined at least one parking space is occupied. If one or more further parking space are included in the plurality of parking spaces other than the determined at least one parking space, an indication is included in the parking availability information that the further parking spaces are available for parking.

Abstract: An unsupervised classification approach is improved by imposing some order into the treatment of the records and their attributes, which otherwise would be treated as random variables. A method is provided to identify particular attributes that are most associated with the “good” records within each of the plurality of groups of records within a data set. Based on a supervised scoring method, the records of the data set are processed to indicate their measure of “goodness”. There are various ways by which the records can be processed to indicate a bias during unsupervised clustering processing.

Abstract: A portion of data records of a full input data set are imported into memory of a computer system for processing by an executing application. The full input data set includes data records of a dimensionally-modeled fact collection. An amount of the data of the full input set to import is determined based on an amount of available memory of the computer system. The sampling characteristics for sampling the full input data set are determined based on the amount of the data that can be imported and on characteristics of the full input data set and application involved. The full input data set is then sampled and a portion of the records are imported into the memory of the computer system for processing. The sampling characteristics are determined such that analysis as a result of processing by the executing application of the sampled portion of the records imported is representative of the analysis that could otherwise be carried out on the full input data set, with a calculable statistical relevance.

Abstract: Records representing items in a dimensionally-modeled fact collection are assigned to bins. A count-based portion of a user interface receives user bin assignment specification of the records based on user-specified counts of records. Actual counts for bin assignment are determined by constraining records having a same data value at a specified particular dimension to be within the same bin. A user-observable indication of the determined actual counts is provided. The user interface may include a value-based portion. The value-based portion of the user interface may be operated to receive user indication of bin assignment specification of records based on user-specified at least one value at the particular dimension. Determining actual counts includes reconciling the user indication of bin assignment specification in the count-based portion with the user indication of bin assignment specification in the value-based portion.

Abstract: A computer-implemented method, which comprises the following: receiving a graphical selection of a subset of data points from a set of data points, each data point representing at least one record of a dimensionally-modeled fact collection; and exporting information associated with the selected subset of data points.

Abstract: Systems and methods for determining search terms for sponsored Internet searches are disclosed. A digital Internet ad is served to a plurality of Internet users. Search terms used by the plurality of Internet users served the digital Internet ad may be determined. A number of times each of the plurality of Internet users served the digital Internet ad selects the digital Internet ad is determined. A search term recommendation module determines a correlation level between each search term and the digital Internet ad. At least one of the search terms is recommended for a sponsored Internet search based on the determined correlation levels.

Abstract: Methods, systems, and apparatuses for determining parking availability are described. A sensor system is configured to monitor a plurality of parking spaces. The sensor system includes at least one sensor element that generates a sensor data output signal. A parking availability determiner receives the sensor data output signal and generates parking availability information. The parking availability determiner is configured to determine from the received sensor data output signal at least one parking space of the plurality of parking spaces that is occupied, and to include an indication in the parking availability information that the determined at least one parking space is occupied. If one or more further parking space are included in the plurality of parking spaces other than the determined at least one parking space, an indication is included in the parking availability information that the further parking spaces are available for parking.

Abstract: Methods, systems, and apparatuses for mapping parking locations and for selecting parking are described. A search for parking resources proximate to a destination geographic location is performed. Parking information is generated based on the results of the search. The parking information may be displayed on a map of the destination geographical location. A map of the destination geographical location may be displayed with the parking information. A user may be enabled to select a parking location indicated on the map. The user may reserve the selected parking location if the selected parking location is determined to be reservable. Travel directions (e.g., for walking) from the selected parking location to the destination geographic location may be generated, and may be indicated on the map.

Abstract: Targeting parameters are generated for a media buy plan for advertisements to be displayed in conjunction with presenting web pages, based on a history of search events. Key phrases are received relative to a subject of the advertisements to be displayed. The received key phrases are provided as proposed key phrases to determine, from search events indicative of historical data of uses of a search service, a first subportion of search events for queries of the search service with the proposed key phrases and a second subportion of search events for queries of the search service not with the proposed key phrases. Classification processing is applied to determine potential targeting parameters associated with the first subportion and with the second subportion to identify potential targeting parameters that, statistically, contribute to membership in the first sub-population and in the second sub-population, respectively.

Abstract: Records representing items in a dimensionally-modeled fact collection are assigned to bins. A count-based portion of a user interface receives user bin assignment specification of the records based on user-specified counts of records. Actual counts for bin assignment are determined by constraining records having a same data value at a specified particular dimension to be within the same bin. A user-observable indication of the determined actual counts is provided. The user interface may include a value-based portion. The value-based portion of the user interface may be operated to receive user indication of bin assignment specification of records based on user-specified at least one value at the particular dimension. Determining actual counts includes reconciling the user indication of bin assignment specification in the count-based portion with the user indication of bin assignment specification in the value-based portion.

Abstract: A computer-implemented method, which comprises the following: receiving a graphical selection of a subset of data points from a set of data points, each data point representing at least one record of a dimensionally-modeled fact collection; and exporting information associated with the selected subset of data points.

Abstract: A computer-implemented method, which comprises the following: aggregating a plurality of records in accordance with an aggregation specification, wherein the records are part of a dimensionally-modeled fact collection; graphically representing the records in un-aggregated form; graphically representing the records in aggregated form; and causing the graphical representation of the records to be switched between aggregated form and un-aggregated form based on a user indication.

Abstract: A technique of operating a user interface that enables the user to graphically manipulate records of a dimensionally-modeled fact collection, which comprises the following: receiving a graphical selection of a subset from a set of data points, each data point representing at least one record of the dimensionally-modeled fact collection; receiving a graphical manipulation of the selected subset of data points; defining at least one data group using the selected subset of data points and based on the graphical manipulation, wherein each data group comprises between 0 to n records represented by the selected subset of data points, wherein n is the total number of data points in the set of data points; and graphically representing the at least one data group. Alternatively, the technique comprises the following: performing an operation on at least one data group as described above; and graphically representing a result of the operation.

Abstract: A portion of data records of a full input data set are imported into memory of a computer system for processing by an executing application. The full input data set includes data records of a dimensionally-modeled fact collection. An amount of the data of the full input set to import is determined based on an amount of available memory of the computer system. The sampling characteristics for sampling the full input data set are determined based on the amount of the data that can be imported and on characteristics of the full input data set and application involved. The full input data set is then sampled and a portion of the records are imported into the memory of the computer system for processing. The sampling characteristics are determined such that analysis as a result of processing by the executing application of the sampled portion of the records imported is representative of the analysis that could otherwise be carried out on the full input data set, with a calculable statistical relevance.

Abstract: A method for selecting at least one target customer attribute from a plurality of customer attributes, wherein each customer attribute represents a unique customer characteristic is provided. The plurality of customer attributes is presented for selection. A selection of at least one target customer attribute selected from the plurality of customer attributes is received. For each cluster of a plurality of clusters, indicated the statistic of customers belonging to that cluster who possess each and every one of the at least one target customer attribute. The plurality of clusters comprises a plurality of customers and each customer of the plurality of customers belongs to at least one cluster of the plurality of clusters.

Abstract: An unsupervised classification approach is improved by imposing some order into the treatment of the records and their attributes, which otherwise would be treated as random variables. A method is provided to identify particular attributes that are most associated with the “good” records within each of the plurality of groups of records within a data set. Based on a supervised scoring method, the records of the data set are processed to indicate their measure of “goodness”. There are various ways by which the records can be processed to indicate a bias during unsupervised clustering processing.