Xad, Inc.

Pravesh Katyal

Huitao Luo

Can Liang

Shashi Seth

Hari Venkatesan

Yilin Chen

Saravana Ravindran

Yi Jia

Prakash Muttineni

Al Rashid

Akshay Tilak

Shanshan Tuo

Guoxin Li

Sunil Kumar

Crystal Shi

Vimpy Batra

Richard Chiou

The present disclosure provides novel techniques to segment mobile entities based signals from mobile devices associated with these mobile entities. In certain embodiments, a first set of mobile entities and a second set of mobile entities are determined based at least on first and second predefined constraints. A feature set related to a mobile segment is also identified, the feature set including a plurality of features. A plurality of feature gains corresponding, respectively, to the plurality of features are then determined, and a set of mobile entities are add to the mobile segment based at least one the plurality of feature gains, and for each particular feature of the plurality of features, frequency of events associated with each of the set of mobile entities and having the particular feature.

System and method for segmenting mobile entities based on detected mobile events

A system for processing information requests associated with mobile devices comprises an evaluation module configured to determine at least one performance measure for each of a plurality of information documents using at least data in one or both of a requests database and events database. The at least one performance measure includes at least one of an impression-based performance measure, a click/call-based performance measure, and an off-line site-visit-based performance measure. The system further comprises an information server configured to select a first information document for transmitting to a first mobile device to fulfill a first request. The information server includes a volume control unit configured to derive an off-line site visit projection in response to the first document being selected based at least in part on an off-line site-visit-based performance measure and having been impressed on the first mobile device, and to adjust a budget associated with the first document using the off-line site visit projection.

Using on-line and off-line projections to control information delivery to mobile devices

A system coupled to a packet-based network is configured to generate geo-blocks for location-based information services. Each of the geo-blocks corresponds to a geographical region within a geographical area and has at least one border defined by a real-world object. The system is configured to obtain geo data related to real-world objects including transportation routes and natural boundaries in the geographical area, partition the geographical area into initial geo-blocks using the geo data, process a plurality of information requests with respect to at least some of the initial geo-blocks and with respect to initial geo-fences associated with a plurality of points of interests (POIs) to generate entries in one or more databases, and machine train a mobile device location prediction model based on the entries in the one or more databases.

Systems and methods for mobile device location prediction

The present disclosure provides novel techniques to segment mobile entities based on signals from mobile devices associated with these mobile entities. In certain embodiments, a data file is built for each mobile entity to transform originally extremely high dimensional raw data derived from mobile devices communicating with a network into structured data characterizing associated mobile entities. The data files are structured for filtering and searching with respect to features associated with the signals from mobile devices, including location and non-location features. The data files are used to determine feature gains corresponding respectively to features related to a mobile segment. The features include first features of a first type and second features of a second type. The feature gains are used, among other things, to rank mobile entities for the mobile segment, with feature gains corresponding to the first features given a larger weight than feature gains corresponding to the second features.

System and method for segmenting mobile entities based on mobile device signals

A system coupled to a packet-based network is configured to generate geo-blocks for location-based information services. Each of the geo-blocks corresponds to a geographical region within a geographical area and has at least one border defined by a real-world object. The system is configured to obtain geo data related to real-world objects including transportation routes and natural boundaries in the geographical area, partition the geographical area into initial geo-blocks using the geo data, process a plurality of information requests with respect to at least some of the initial geo-blocks and with respect to initial geo-fences associated with a plurality of points of interests (POIs) to generate entries in one or more databases, and enrich at least some of the initial geo-block with block-level meta data derived from the entries in the one or more databases to form enriched geo-blocks that are highly indicative of location dependent attributes such as intention and demographics.

Systems and methods for predicting mobile device locations using processed mobile device signals

The present disclosure provides novel techniques to derive characteristic of mobile entities based signals from mobile devices associated with these mobile entities. In certain embodiments, a data file is built for each mobile entity to transform originally extremely high dimensional raw data derived from mobile devices communicating with a network into structured data characterizing associated mobile entities. The data file are structured for filtering and searching with respect to location and non-location features. A plurality of filters for a behavioral segment are applied to the data files of a large number of mobile entities. The plurality of filters including a preset hard constraint (HC) filter, a preset soft constraint (SC) filter, and an extended constraint (EC) filter built using location features in data files that have passed through the HC filter and/or the SC filter. In further embodiments, a search index and a search query for a search engine are generated for the behavioral segment based on the filtered data files, and the search query is run against the search index through the data files that have passed the HC filter to search for more data files to add to the segment.

A system coupled to a packet-based network is configured to predict the locations of one or more mobile devices communicating with the packet-based network. The system comprises a request processor configured to detect location events associated with mobile devices communicating with the packet-based network, each location event corresponding to a time stamp and identifying a geo-place in a geo database. The system further comprises an off-line prediction subsystem configured to train a plurality of off-line prediction models and an on-line prediction model using various historical location events. The off-line prediction subsystem is further configured to generate off-line prediction results corresponding to the off-line prediction models. The system further comprises an on-line prediction subsystem configured to construct a feature vector using the off-line prediction results and recently detected location events in response to a request received in real-time, and to generate on-line prediction results by applying the on-line prediction model to the feature vector.

System and method for real-time prediction of mobile device locations

System and method for characterizing mobile entities based on mobile device signals

A system coupled to a packet-based network is configured to generate geo-blocks for location-based information services. Each of the geo-blocks corresponds to a geographical region within a geographical area and has at least one border defined by a real-world object. The system is configured to obtain geo data related to real-world objects including transportation routes and natural boundaries in the geographical area, partition the geographical area into initial geo-blocks using the geo data, process a plurality of information requests with respect to at least some of the initial geo-blocks and with respect to initial geo-fences associated with a plurality of points of interests (POIs) to generate entries in one or more databases, and enrich at least some of the initial geo-block with block-level meta data extracted from the entries in the one or more databases to form enriched geo-blocks that are highly indicative of location dependent attributes such as intention and demographics.

Systems and methods for creating and using geo-blocks for location-based information service

The present disclosure provides methods and systems that utilize mobile device location events and machine learning and generate predicative classification/regression model for lookalike prediction. Location related features, together with other user level information, are extracted, transformed and used as model feature input, and a client specified list of mobile devices or their associated users are used as prediction target. This system makes efficient use of different types of location events and thus offers improved scale and performance. It also enjoys many benefits offered by a machine learning platform, such as automatic adaptation to different lists of seed lists, addition of new features and changes in data statistical properties.

Systems and methods for predicting lookalike mobile devices

A system coupled to a packet-based network is configured to generate geo-blocks based on geo data related to real-world objects including transportation routes and natural boundaries in a geographical area such that each of the geo-blocks corresponds to a geographical region within the geographical area and has at least one border defined by a real-world object. The system is further configured to determine a performance measure with respect to a point of interest (POI) for each of a set of geo-blocks, and to select one or more geo-blocks each having a performance measure above a threshold from the set of geo-blocks to form a geo-fence for the POI. The threshold is adjustable based on a pacing status of an information campaign associated with the POI.

Systems and methods for using geo-blocks and geo-fences to discover lookalike mobile devices

Systems and methods for real-time prediction of mobile device locations

A system coupled to a packet-based network is configured to predict the locations of mobile devices that have communicated with the packet-based network. The system includes a request processor configured to detect location events associated with mobile devices communicating with the packet-based network, each location event corresponding to a time stamp and identifying a geo-place in a geo database. The geo-places include geo-blocks and geo-fences. The system further comprises a location prediction subsystem configured to construct first feature space using first location events and second feature space using second location events, and to extract a set of labels from third location events. The location prediction subsystem is further configured to train a prediction model using the first feature space and the set of labels, and to apply the prediction model to the second feature space to obtain prediction results.

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Mountain View, CA, United States of America

Pravesh Katyal