A system, non-transitory computer-readable medium, and method are provided. The system comprises at least one processor and memory storing instructions which when executed by the at least one processor configure the at least one processor to perform the method. The non-transitory computer-readable medium has instructions thereon, which when executed by a processor, perform the method. The method comprises providing a demand-side user interface offering at least one rental property, determining a bid price for user to offer for the at least one rental property, and matching the user with the rental property.

A method and system are disclosed which calculates a consistency score for a political figure based on social media, speeches, news articles, or other information sources, as well as the political figure's voting record. The method and system determine the political representatives for a user based on the user's geographical location, and present information on various political figures to the user. The method and system are also capable of providing communication between multiple users, as well as between users and political figures. The method and system also allow for users to send physical letters to political figures, and for political figures to send messages to users.

The present invention discloses a method for identifying and quantifying populations exposed to environmental hazards across a geographic region. The environmental hazards include radiation, pollution and communicable infectious agent hotspots, such as locations of COVID-19 hotspots. The method of the present invention uses geographic distributions of infected individuals over time to develop robust methods that pinpoint locations of emerging COVID-19 hotspots. The method assays a fraction of infected individuals of a local population and adjacent locations of the infected individuals and detects spatial asymmetries and clustered distributions of infected individuals. The spatial resolution of the assay is increased by assigning infected cases in each county to subdivisions weighted by population census and performing spatial interpolation to pinpoint potential local clusters of infected individuals.

A date generation apparatus 2000 acquires the date information 20 regarding the target product 10 and the rule condition indicating the condition regarding the generation rule 40. The generation rule 40 is a rule for generating a character string 30 to be attached to the target product 10 from the date information 20. The date generation apparatus 2000 acquires the generation rule 40 corresponding to the rule condition. Then, the date generation apparatus 2000 uses the generation rule 40 to generate the character string 30 from the date information 20.

A sensor data forecasting system for urban environment using deep learning model is provided. The system is configured to determine a false value by analyzing a time stamped and indexed sensor data received from a plurality of sensors in a location; determine a category of the false value by analyzing one or more of (a) historical sensor data (b) comparative sensor data between sensors of a first type and (c) comparative sensor data between sensors of the first type and a second type; determine an imputation method based on the category of the false value, wherein the imputation method uses one or more of (1) Kalman filter (2) a nearest neighbor value (3) a statistical analysis of repeating sensor values; impute the false value or determine an erroneous sensor; implement the Kalman filter, forecast sensor data based on the optimum sensor values at each data point by a trained Recurrent Neural Net (RNN) model and perform automation of tasks, using the processor, at the urban infrastructure based on the forecasted sensor data for urban management by generating commands at predetermined events or instances.

A method, system, and computer program product for predicting future transactions may obtain merchant data associated with a merchant; determine a geographic location associated with the merchant based on the merchant data; determine one or more other merchants within a first threshold distance of the geographic location; obtain transaction data associated with the one or more other merchants and the merchant; and predict, based on the transaction data, at least one of a future number of transactions for the merchant in a future time period and a future transaction amount for the merchant in the future time period.

Methods, systems and computer program products for facilitating use of select hyper-local data sets for improved modeling are provided. Aspects include receiving customer data associated with a customer by a workbench platform and determining an accuracy of a customer model using the customer data. For each of a plurality of hyper-local data sets, aspects also include determining an increase in model accuracy based on use of the hyper-local data set and the customer data. Aspects include identifying at least one group of hyper-local data sets of the plurality of hyper-local data sets that result in similar increases in model accuracy. Aspects also include facilitating use of a selected one or more of the hyper-local data sets of the at least one group of hyper-local data sets in generating an improved accuracy customer model.

This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

Customers receive an incentive with use of an installed cellphone app to image an AR-bearing ad. Matches between data from the customer's accounts for each merchant are compared to the data in association with the customer's logical identifier for their cellphone, and particularly with each incidence of a rendering on their display screen of an AR view of a product advertisement containing the AR-triggering symbol to initiate the corresponding AR enhanced view of the ad. In conjunction with chronological time stamping of occurrences, a likelihood is derived that the customer's viewing of the AR enhanced product advertisement influenced the potential customer's subsequent purchase of the corresponding advertised product as evidenced within the potential customer's rich transactional data from the customer's debit and/or credit accounts. The certainty of each match is determined to further initiate the merchant's incentive to the customer which may be the merchant's donation to a community program.

Embodiments discussed herein are directed to systems and methods for processing audio feedback on a business, product or service offered and providing the feedback to an associated company in a way that enables the appropriate actors within the company's organizational hierarchy to analyze and take action with respect to the feedback. Customers or employees can interact with a virtual assistant platform or other voice recognition platform to access a feedback service that enables customers or employees to provide feedback to or have a conversation with any business about their product or service. The feedback service can be accessed at any time using a mobile phone or internet connected speaker device using a digital assistant platform.