Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Systems, methods, and apparatus are disclosed for identifying and analyzing online advertising performance data. Systems may receive data records that include data events characterizing interactions between users and online advertisement campaigns. The online advertising data records may include timestamp data characterizing creation dates for data events. The systems may generate intermediate data objects by partitioning at least some of the online advertising data records based on a first plurality of temporal data categories representing different units of time. Each intermediate data object may be associated with a temporal data category of the first plurality of temporal data categories. The systems may generate performance data objects by partitioning the intermediate data objects based on a second plurality of temporal data categories that are different than the first temporal data categories.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing recommendations are presented. Consistent with some embodiments, the method may include accessing a selection of queries executed on a database of items. The selection of queries may be used to retrieve a plurality of items from the database. The plurality of items may be grouped into one of multiple clusters based on similarities between items. The method may further include receiving a recommendation request related to an item corresponding to a first cluster of the multiple clusters. A recommendation may be generated using a related item selected from the first cluster.

Abstract: Systems, methods, and devices are disclosed herein for spend control in online advertising. Systems include a first plurality of advertisement servers included in a first data center, and a second plurality of advertisement servers included in a second data center. Systems include a performance data aggregator configured to receive performance data characterizing bids placed by the first plurality of advertisement servers and the second plurality of advertisement servers. Systems include a spend control analyzer configured to generate spend control data objects based on an estimate of bidding activity associated with the first data center and bidding activity associated with the second data center. Spend control data objects are capable of configuring advertisement servers to perform advertisement operations within determined budgetary constraints.

Abstract: Systems, methods, and devices are disclosed herein for spend control in online advertising. Systems include a first plurality of advertisement servers included in a first data center, and a second plurality of advertisement servers included in a second data center. Systems include a performance data aggregator configured to receive performance data characterizing bids placed by the first plurality of advertisement servers and the second plurality of advertisement servers. Systems include a spend control analyzer configured to generate spend control data objects based on an estimate of bidding activity associated with the first data center and bidding activity associated with the second data center. Spend control data objects are capable of configuring advertisement servers to perform advertisement operations within determined budgetary constraints.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Systems, methods, and apparatus are disclosed for identifying and analyzing online advertising performance data. Systems may receive data records that include data events characterizing interactions between users and online advertisement campaigns. The online advertising data records may include timestamp data characterizing creation dates for data events. The systems may generate intermediate data objects by partitioning at least some of the online advertising data records based on a first plurality of temporal data categories representing different units of time. Each intermediate data object may be associated with a temporal data category of the first plurality of temporal data categories. The systems may generate performance data objects by partitioning the intermediate data objects based on a second plurality of temporal data categories that are different than the first temporal data categories.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing recommendations are presented. Consistent with some embodiments, the method may include accessing a selection of queries executed on a database of items. The selection of queries may be used to retrieve a plurality of items from the database. The plurality of items may be grouped into one of multiple clusters based on similarities between items. The method may further include receiving a recommendation request related to an item corresponding to a first cluster of the multiple clusters. A recommendation may be generated using a related item selected from the first cluster.

Abstract: A data management apparatus for digital advertising includes a data integration processor for collecting and storing data from providers, resolving heterogeneity of the data at schema and data levels, and performing validity checks of the data; an analytics processor for receiving validated data from the data integration processor and providing to users custom, nesting-aware, SQL-like query language and a library of data mining methods, machine learning models, and analytical user profiles (AUP); and an activation processor for encapsulating complex computations performed in real-time, segment evaluation, and online user classification using runtime user profiles (RUP).

Abstract: The present invention provides a method and system for optimizing search result rankings through use of a game interface. The method and system includes providing a game interface to at least two users, the game interface comprising at least one search query and at least two search result sets. The method and system further includes detecting the selection of one of the two search result sets by the users based on competition criteria and updating ranking data in response to the selection of one of the two search results. The method and system further includes selecting ranking data associated with a given query, determining an optimum ranking based on aggregating the selected ranking data, and storing the optimum ranking.

Abstract: The present invention provides a method and system for optimizing search result rankings through use of a game interface. The method and system includes providing a game interface to at least two users, the game interface comprising at least one search query and at least two search result sets. The method and system further includes detecting the selection of one of the two search result sets by the users based on competition criteria and updating ranking data in response to the selection of one of the two search results.

Abstract: The present invention provides a method and system for optimizing search result rankings through use of a game interface. The method and system includes providing a game interface to at least two users, the game interface comprising at least one search query and at least two search result sets. The method and system further includes detecting the selection of one of the two search result sets by the users based on competition criteria and updating ranking data in response to the selection of one of the two search results. The method and system further includes selecting ranking data associated with a given query, determining an optimum ranking based on aggregating the selected ranking data, and storing the optimum ranking.

Abstract: The present invention provides a method and system for optimizing search result rankings through use of a game interface. The method and system includes providing a game interface to at least two users, the game interface comprising at least one search query and at least two search result sets. The method and system further includes detecting the selection of one of the two search result sets by the users based on competition criteria and updating ranking data in response to the selection of one of the two search results. The method and system further includes selecting ranking data associated with a given query, determining an optimum ranking based on aggregating the selected ranking data, and storing the optimum ranking.

Abstract: Disclosed are apparatus and methods for facilitating search queries via a computer network. In certain embodiments, each search term that a user inputs for a search query causes a rich set of contextual information having one or more parameters or facets to be presented to the user to further enhance and refine the search query. The context facets can pertain to the search term itself or contextual information that is associated with search results objects that have been previously associated with such search term. Additionally, the user can be queried for a facet to be associated with the search term. The user can then input parameter values or choose selection option (e.g., numbers, strings, links, etc.) for each facet, and search results can then be provided based on such facet parameter values or selection option input.

Abstract: Disclosed are apparatus and methods for providing next click information regarding search results. In certain embodiments, as objects (such as web pages, images, videos, audio files) are searched and clicked, click information is retained. Next click information with respect to specific objects can then be determined. This next click information can then be provided to an object search initiator so that such next click information is presented along with search result objects, for example, during a search query.