Systems and methods are provided for use in identifying recurring local entities for a target region. One exemplary method includes receiving a request for identifying recurring local entities for a target region and accessing data for the target region for multiple accounts. The data is representative of multiple transactions and multiple accounts, with each transaction having an account number associated with a user and a region identifier associated with an entity involved in the transaction. The method also includes determining a local region for each of the accounts included in the data and, for each determined local region that is the same as the target region, identifying one or more recurring entity from the transactions to said accounts having the determined local region. The method then includes compiling a listing of recurring local entities including the identified one or more recurring entities.

Techniques for data evaluation and optimized resource allocation are provided. Usage data is received collected from at least one sensor in a physical location, where the usage data indicates consumption of an item. The usage data is aggregated within a predefined cluster, where the predefined cluster corresponds to a geographic area. Future consumption of the item is predicted based at least in part on evaluating the usage data using one or more cognitive models. A recommended reconfiguration of one or more aspects of production for the item is generated, based on the predicted future consumption.

A system for providing referrals for jobs and services includes a profile association module that identifies relationships between user profiles of a second degree or greater based on first-degree relationships identified by users and a search module configured conduct a search of user profiles based on a query provided by a user. The system includes a messaging module that receives from a user a referral request directed to one or more friends of the user identified by the search module as having a predetermined degree of relationship with another user being among the search results from the search module.

A marketing analytics pipeline that receives transaction-level trend reporting of media IP assets distributed on digital service providers (DSPs), the marketing analytics pipeline including a marketing action analytics hub configured to receive the growth and re-engagement opportunities from an opportunity detection analytics hub or from a marketing platform directly and to identify high growth potential audiences using predictive models of engagement; and a marketing platform configured to interact with the marketing action analytics hub and to create marketing campaigns based around the high growth potential audiences and suggest marketing actions to media IP asset managers and owners to deliver to the high growth potential audiences on appropriate marketing channels via targeted marketing campaigns. The marketing action analytics hub uses a geodemographic and interest-based targeting method of generating descriptions of high growth potential audiences.

A community vulnerability index dashboard includes a data ingestion logic module configured to automatically receive real-time and non-real-time data from a variety of sources including education agencies, law enforcement, health services agencies, healthcare agencies, medical insurance agencies, housing and transportation agencies, childcare licensing agencies, and non-emergency citywide services. The dashboard includes a data processing module that extracts and process the ingested data, and a data analysis logic module that analyzes the processed data to determine values for indicators and an overall vulnerability index value based on the values of the plurality of indicators to provide insight into the lives of residents living in a community on a block group level. The dashboard includes a data presentation dashboard interface to display an interactive choropleth map of the overall vulnerability index and indicator values on a block group level for the community of interest.

Techniques are described for training machine learning (ML) models using one or more electronic lists of items previously used in campaigns and labeled with an engagement rate corresponding to the list. A vocabulary formed from a union of the one or more lists may then be used to generate at least some items of a target recipient list. An engagement rate for the target recipient list may be inferred for the target recipient list. Natural language processing (NLP) techniques may be also be applied to optimize an engagement rate of a target recipient list and/or select content for the list.

Provided is a computer-implemented method for providing real-time offers based on geolocation and merchant category. Transaction data for transaction from a plurality of merchants is received. A subset of merchants is determined based on the physical location of the merchants and the merchant category of the merchants. Real-time market activity data is determined for each of the merchants in the subset of merchants. A real-time offer is initiated based on comparing the market activity data of at least one merchant compared to the market activity data of a first merchant.

Provided is a process including obtaining a set of geographic places of interest, obtaining a set of location identifiers of devices, determining a set of tiles based on the set of geographic places of interest, and determining a subset of the set of location identifiers of devices based on members of the subset of the set of location identifiers. The process also includes determining a subset of the devices based on the subset of the set of location identifiers of devices and determining a set of dwell-based values based on the subset of the set of devices. The process also includes determining a set of threshold-satisfying tiles based on the set of dwell-based values and storing the set of threshold-satisfying tiles in a computer system.

Provided is a process including segmenting a representation into a set of tiles and obtaining a set of geolocations. The process includes, for each tile, determining a respective amount of devices within the respective tile to form a set of weights. The process also includes assigning each tile of a subset of the set of tiles with a set of groups based on the set of weights, building a first map based on the set of groups, and building a second map by traversing the first map. The process also includes determining a first and second subset of devices by traversing the second map, determining whether a second tile is to be assigned to a first or second group based on the first and second subset of devices, assigning the second tile to the first group, and building a region map comprising the set of groups.

A method for automatically generating, in real-time, for display on a display, a simplified network layout from an initial network layout including one or more lines each connecting a plurality of nodes. Graph information is provided indicating vertices representing geographic positions of the nodes and edges representing connections between the nodes. The nodes are repositioned to optimize an objective function based on readability of the simplified network layout. Nodes and edges are discretized using interpolation to align a plurality of the nodes and connect the aligned nodes using simplified k-linear segments, where k-linear segments are parallel to one of k equidistant orientations whose angles are multiples of 180/k degrees, with k larger or equal to two. The simplified network layout is provided for a display.