Abstract: A calculation unit (15a) calculates a degree of association between words included in compound word candidates that are each constituted by consecutive words in a document. The calculation unit (15a) calculates the degree of association by using a conditional probability that is a probability of a word that precedes a last word being present in the document under the condition that the last word follows. A selection unit (15b) selects, as a compound word, a compound word candidate whose degree of association thus calculated is higher than a predetermined threshold value. A learning unit (15c) learns a positional relationship between words that include the selected compound word in the document and predetermined tags added to the document. An addition unit (15d) adds the predetermined tags to the document based on the positional relationship between words that include the learned compound word in the document and the predetermined tags added to the document.

Abstract: A vehicle allocation system includes: an automatic driving vehicle; a mobile terminal configured to transmit a vehicle allocation request signal containing at least information on a vehicle allocation place of the automatic driving vehicle; and a server configured to allocate the automatic driving vehicle at the vehicle allocation place in response to reception of the vehicle allocation request signal, give a notification to the mobile terminal in response to arrival of the automatic driving vehicle from the vehicle allocation place within a predetermined distance range, and permit usage of the automatic driving vehicle when a user of the mobile terminal is authenticated based on authentication information transmitted from the mobile terminal in response to the notification.

Abstract: A merchant system structures communications among merchants, partners, and customers. The merchant system may include a messaging component that organizes messages so that a manager can quickly navigate and understand the content of incoming messages. The messaging system also may categorize a user's profile so that a user may share profile information established at a first merchant with a second merchant.

Abstract: Systems and methods are provided herein for producing and vending ice in an energy-efficient manner. A system for producing and vending ice comprises: an ice-making device configured to manufacture ice; a reservoir coupled to the ice-making device and configured to store the manufactured ice manufactured; and a control circuit communicatively coupled to the ice-making device, the control circuit configured to: determine a beginning ice inventory at a first time; determine a predicted ice demand for a first period, wherein the predicted ice demand is a function of at least a historical factor, a weather factor, a customer social event factor, and a public social event factor; determine an ice manufacturing quantity based on the beginning ice inventory, the predicted ice demand, and a manufacturing capacity of the ice-making device; and cause the ice-making device to produce an amount of ice consistent with the determined ice manufacturing quantity.

Abstract: A power management system includes a plurality of power adjustment resources electrically connected to a microgrid. The plurality of power adjustment resources include a plurality of EVSEs, each of EVSEs including a parking space. When any one of a plurality of power feeding vehicles is parked in the parking space, an EVSE enables power feeding from a vehicle parked in the parking space to the microgrid. A CEMS server manages the parking space. When a balance of power supply and demand in the microgrid is in an overdemand state, the CEMS server allocates the parking space to a power feeding vehicle that responds to a request for power feeding to the microgrid, of the plurality of power feeding vehicles.

Abstract: A method (200) for determining future resource requirements in a given location, the method comprising the steps of obtaining (110) transaction data, the transaction data indicative of past resource use at a given location. At least one model may be trained (120) based on a set of parameters by determining (121) a distribution associated with the transaction data; and generating (122) a kernel based on the distribution and the set parameters, the kernel being arranged to output an estimated distribution. The kernel is refined (123) and validated (124) based on a comparison between the distribution and the estimated distribution. A density map is then generated (125) based on the at least one trained model. The density map is then sent (130) to a control system for determining future resource requirements in the given location.

Abstract: An example method of dynamically distributing messaging resources in a software as a service (SaaS) platform includes: receiving, by a processing device, from a first tenant associated with a first tenant set of a plurality of tenant sets, a request to forward a first message to a recipient within a specified destination; identifying, among a plurality of queues associated with the plurality of tenant sets, a subset of queues associated with the first tenant; queuing the first message into a first queue of the subset of queues associated with the first tenant; assigning, to each queue of the plurality of queues, a score reflecting a respective tenant portion of a messaging resource quota associated with the specified destination; retrieving a second message from a queue associated with a highest score; and forwarding the second message to a messaging gateway associated with the specified destination.

Abstract: A method, computer program, and computer system are provided for load forecasting. Datasets corresponding to source machine learning models and a target domain base model are identified. A set of forecasting models corresponding to the identified datasets are learned. An ensemble model is determined from the learned set of forecasting models based on gradient boosting. An available resource is allocated based on the ensemble model.

Abstract: Provided is a system, including: a demand information acquisition unit configured to acquire information indicating power demand in a power network; and a setting unit configured to, based on the power demand, set a usage fee for a parking lot having a power transmission and reception facility for a vehicle having a power supply for driving to transmit and receive power to/from the power network.

Abstract: A system includes a first facility element having a sensor and configured to generate recent performance data associated with a system of a facility, and a monitoring and control element in communication with the first facility element, where the monitoring and control element is configured to identify one or more analogous facility elements analogous to the first facility element, receive the recent performance data for the first facility element, generate projected performance data for the facility element according to historical performance data associated with the facility element and the one or more analogous facility elements, compare the projected performance data to a performance threshold, and override a setting or operating parameter of the first facility element according to a relationship of the projected performance data to the performance threshold and by sending one or more operational adjustment commands to at least one second facility element.

Abstract: Predicting end-of-life support deprecation is described. A system receives an identification of a product, and then identifies support request records associated with the product. The system identifies support information associated with the support request records. A predictive model uses the support information to predict a deprecation for the product. The system outputs the prediction of the deprecation for the product.

Abstract: A “SOUND ID SYSTEM” comprise a Device with a microphone that continuously monitors the surrounding environment. Pre-recorded personalized or unique sound patterns, signatures, and/or key words, and/or their derivatives, are stored in the Device. When such a pre-determined pre-recorded sound pattern, signature, or key words, or their derivatives, are recognized by the Device, a corresponding pre-determined action or action sequence will be sent to the Cloud, or other devices, to execute. Such other devices can attach, co-habitat, and wired/wirelessly connect to the Device, or share some components with the Device. If the Device does not recognize any particular pre-recorded sound pattern, signature or key words, or their derivatives, then the Device will not transmit to disclose to any outside device or other entity, any monitored sound information.

Abstract: A plant treatment platform uses a plant detection model to detect plants as the plant treatment platform travels through a field. The plant treatment platform receives image data from a camera that captures images of plants (e.g., crops or weeds) growing in the field. The plant treatment platform applies pre-processing functions to the image data to prepare the image data for processing by the plant detection model. For example, the plant treatment platform may reformat the image data, adjust the resolution or aspect ratio, or crop the image data. The plant treatment platform applies the plant detection model to the pre-processed image data to generate bounding boxes for the plants. The plant treatment platform then can apply treatment to the plants based on the output of the machine-learned model.

Abstract: A method may include applying, to a content associated with a first supplier, a machine learning model to determine one or more objectives of an enterprise affected by an incident associated with the content. A change in a first risk associated with the first supplier may be detected based on the objectives affected by the incident. In response to detecting the change in the first risk of the first supplier, a cost associated with replacing the first supplier with the second supplier may be determined by applying the machine learning model to analyze a first electronic document associated with the first supplier. If the cost of replacing the first supplier with the second supplier and/or a second risk of the second supplier satisfy one or more thresholds, a second electronic document associated with the second supplier may be generated to address the second risk of the second supplier.

Abstract: Systems and methods directed to managing computer resource allocation by monitoring signals indicating demand for services utilizing computer resources are described. A method includes maintaining, for each first event of first events, historical registration data and respective parameter values of the first event and identifying, for a second event having an open registration status, respective parameter values of the second event, and registration data for the second event. The method includes computing a similarity score between the second event and each first event of the plurality of first events, based on the respective parameter values of the first event and the second event and the registration data of the second event and the historical registration data of the first event, generating, for the second event, a projected number of entities based on determined information and determining a ranking of the second event.

Abstract: An integrated system and method measures building characteristics and user behavior to provide real-time and forecasted utility usages and costs. The system gathers current and historical heating and cooling load data, compares the data with current and historical weather data and a building system set point, and calculates the heating or cooling load needed for the building based on the user's call for heat or cooling and the ambient environmental conditions. The system additionally analyzes individual device usage using usage signatures and user inputted tracking to create a comprehensive real-time and forecast of utility usages with the estimated costs. Through history of selections with usage changes corresponding to user input of individual devices, the system will be able to learn various devices' usage. The system then creates a comprehensive, real-time forecast of utility costs including the foregoing characteristics.

Abstract: A system may include a rental property listing portal and a rental price prediction unit. The rental price prediction unit may additional include an amenity price prediction unit. The rental price prediction unit and the amenity price prediction unit may use one or more mathematical models, such as constrained optimization model and/or a machine learning approach such as a random forest model, to generate a suggested rental price at a given level of portfolio occupancy. The system may also provide risk thresholds to simulate leasing strategies based on market situations, predicting revenue potential and possible vacancy for each strategy. The system may also generate a delist time (time to rent) for a property at a given price. The system and method may be implemented in a multi-family apartment rental system, a storage space rental system, a student accommodation, and single family apartment rental systems.

Abstract: A non-transitory computer-readable medium stores computer-readable instructions executable by a processor of an information processing device communicable with a printer configured to perform printing until a print permission amount reaches a particular threshold. The instructions are configured to, when executed by the processor, cause the information processing device to obtain a first number of sheets that indicates a remaining number of sheets printable according to consumable information, in response to receiving, via a user interface, an instruction to add an additional print permission amount, obtain a second number of sheets that indicates an additional number of sheets printable by the printer according to the additional print permission amount, determine whether the second number of sheets is more than the first number of sheets, and when determining that the second number of sheets is more than the first number of sheets, cause the user interface to provide a notification.

Abstract: Implementations relate to crop yield prediction at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that capture a first geographic area and are acquired over a first predetermined time interval while the first geographic area includes a particular crop. A first plurality of other data points may also be obtained that influence a ground truth crop yield of the first geographic area after the first predetermined time interval. The first plurality of other data points may be grouped into temporal chunks corresponding temporally with respective images of the first temporal sequence. The first temporal sequence and the temporal chunks of the first plurality of other data points may be applied, e.g., iteratively, as input across a machine learning model to estimate a crop yield of the first geographic area at the end of the first predetermined time interval.

Abstract: A building energy system includes equipment operable to consume, store, or generate one or more resources, a utility connection configured to obtain, from a utility provider, a first resource subject to a load-following-block rate structure and provide the first resource to the equipment, and a controller. The controller provides an objective function indicating a total value of purchasing the first resource from the utility provider over a plurality of time steps. The objective function includes a first term representing a load-following-block of the first resource from the utility provider as being sourced from a first supplier at a fixed rate and a second term representing a remainder of the first resource from the utility provider as being sourced from a second supplier at a variable rate. The controller controls the equipment based on a result of an optimization of the objective function.

Abstract: A system including: a processor; and a memory storing computer program code that controls the processor to: collect real-time business process metrics; collect real-time cluster metrics for a plurality of application clusters indicative of a required allotment of infrastructure resources for a given business process level; estimate a predicted future business process level; based on the estimated predicted future business process level and the real-time cluster metrics, predict a future infrastructure resource requirement of each of the plurality of application clusters; compare the predicted future infrastructure resource requirement of each of the plurality of application clusters to a current dedication of each of the plurality of application clusters; automatically adjust, in real-time and based on the comparison, respective allotments of infrastructure resources for each of the plurality of application clusters; receive an actual business process; and process the business process across the plurality of

Abstract: An infrastructure management subsystem receives a selection of a planned configuration of the computing infrastructure and a baseline demand that includes a current usage of computing resources of the computing infrastructure. The infrastructure management subsystem determines an anticipated turbulence. The anticipated turbulence includes a quantitative indication of anticipated fluctuations in future infrastructure demand as a function of time. The infrastructure management subsystem determines an effective turbulence for the planned infrastructure configuration. The effective turbulence includes a quantitative indication of anticipated fluctuations in future infrastructure availability. The infrastructure management subsystem determines a configuration score corresponding to an extent to which the anticipated fluctuations in the effective turbulence destructively interfere with the anticipated fluctuations in the anticipated turbulence.

Abstract: The disclosed embodiments provide a system for predicting hiring priorities. During operation, the system determines hiring features characterizing hiring activity by a company for a set of titles. Next, the system applies a first machine learning model to the hiring features to produce a first set of scores representing future hiring volumes and applies a second machine learning model to the hiring features to produce a second set of scores representing future hiring growth. The system then generates a first ranking of the titles by the first set of scores and a second ranking of the titles by the second set of scores. Finally, the system outputs at least a portion of the first ranking as a prediction of future hiring volumes by the company and at least a portion of the second ranking as a prediction of future hiring growth by the company.

Abstract: Described is a poll-based system that provides an on-line and mobile network of users and products, goods and services that are determined through polling each of the users. The system compares, in real-time, the current user's polling responses to identify which most similarly match the answered questions to that of the user. As the user progressively answers questions, the system updates the matching and presentation other users and of products, goods and services. Thus, as the user answers polling questions, the selected answers are compared against the selected descriptions of other products, goods and services, or general questions, to generate a likelihood of match between the users, and also each of the products, goods and services. The profiles of products, goods and services that have a likelihood of match within a predetermined threshold are then presented, including links within the profile for specific purchases.

Abstract: Systems and methods for a product driven approach to technology provisioning, operations, and billing are provided. Some embodiments provide an Information Technology (IT) business architecture built around the product driven methodology. This architecture can be designed to optimize the demand side provisioning of technology products to meet business intent and the execution of supply side assembly and implementation lifecycle. A technology model can be used that recursively decomposes services and products into various components. As a result, the technology model allows for effective and efficient provisioning, pricing, and impact assessment of the organization's technology to thereby drive the efficiency of scale and the automation of the provisioning, the finance, and the operation businesses.

Abstract: A method, computer program product, and a system where a processor(s) determines generates a cognitive user profile representing patterns of usage of each of a plurality of users of the transportation resource sharing system, a cognitive resource profile for each resource of the plurality of resources, a cognitive route profile for each route traversed by at least one resource of the plurality of resources, and a cognitive station profile for each station of the plurality of stations. The processor(s) assigns one or more specific resources of the plurality of resources to one or more specific users of the plurality of users and the one or more specific resources of the plurality of resources to one or more specific stations of the plurality of stations.

Abstract: A merchant system structures communications among merchants, partners, and customers. The merchant system may include a messaging component that organizes messages so that a manager can quickly navigate and understand the content of incoming messages. The messaging system also may categorize a user's profile so that a user may share profile information established at a first merchant with a second merchant.

Abstract: In an example embodiment, a method determines a container containing one or more items associated with one or more item types, the container located at a current position in a storage facility; determines one or more order likelihoods of the one or more item types contained in the container; determines a container utilization likelihood of the container based on the one or more order likelihoods of the one or more item types contained in the container; determines an optimal position for the container in the storage facility based on the container utilization likelihood of the container, the optimal position being different from the current position of the container; and instructing an automated guided vehicle (AGV) to transport the container from the current position of the container to the optimal position of the container in the storage facility.

Abstract: Event-based replenishment simulation for an enterprise supply chain is described. On a per item, per node, per epoch basis, the simulation may generate a stream of action events based on forecasted demand, supply chain logic, and policy inputs that are applied to a current-run state of the supply chain in order to yield a stream of observation events. Requested metrics may be received, and the observation events may then be transformed to predict values for the metrics as output of the simulation. The simulation may be repeated for a given epoch using discrete demand values from a demand distribution, for a plurality of epochs, and/or across a plurality of items at a plurality of nodes. Resultantly, the simulation output can be used for predicting a future run-state of the supply chain across items and nodes.

Abstract: In some implementations, a device may receive data identifying products and encoded data identifying smart tags of the products. The device may map the data and the encoded data to generate encoded product data. The device may receive encoded data provided by smart tags of products received by a store. The device may receive images of the products. The device may compare the encoded data and the encoded product data to identify a set of the products received by the store. The device may correlate the images with the set of the products. The device may process the correlated data to identify locations of the set of the products in the store. The device may generate an instruction to relocate a product to a new location and may provide the instruction to a device, associated with the store, to cause the product to be relocated to the new location.

Abstract: A computer implemented method for optimizing a delivery or settlement process for a plurality of portfolios of a plurality of participants. Data records indicative of obligations between the plurality of participants are identified. A weighted directed graph data structure is generated that comprises vertex data records representing the plurality of participants and edge data records representing the obligations between the participants. All paths of edge data records where a vertex data record is reachable from itself in the weighted directed graph data structure are identified. The data records indicative of obligations between the plurality of participants are altered based on the identified paths.

Abstract: A system and method for adaptive advertisement management for the serving of vehicle description pages and an automated customer engagement thereof. The system is a cloud-based network containing a campaign database, an analytics database, an adaptive advertisement management, a short message service server with automated response capabilities, and user mobile and compute devices that transmit a vehicle description page associated with an advertisement campaign embedded with a communication initiator for display on a customer computing device. Taken together or in part, said system optimizes advertising campaigns across multiple platforms, provides strong analytics for all advertising types while allowing users to engage with advertising quickly and in a real-time automated fashion.

Abstract: A system and a method for regulating charging and discharging of an energy storage device as part of an electrical power distribution network is described. The invention is a smart control algorithm for a bi-directional switch in which an energy storage device, such as a battery set, is charged when electricity prices are low and discharged when electricity prices are high. The invention uses two different types of pricing data: forecasted price data and real-time price data. The forecasted price data is used to set a threshold. When the real-time price data of electricity exceeds this threshold, the energy storage device is set to discharge and send power to the grid. Otherwise the energy storage device is set to charge. The threshold is set periodically, typically in 30 minute to several hour intervals to capture the latest data.

Abstract: The disclosure relates to a quantile probabilistic short-term power load ensemble forecasting method. The method includes: dividing historical power load data of a power system into a first data set and a second data set; performing bootstrap sampling on the first data set to generate multiple training data sets; training a neural network quantile regression model, a random forest quantile regression model and a gradient boosting regression tree regression model for the each training data set to obtain quantile forecasting models; establishing an optimization model with an objective function for minimizing the quantile loss for the second data set, and determining a weight for each of the quantile regression models, to calculate a power load ensemble forecasting model for predicting the power load in the power system.

Abstract: A data engine may establish and maintain dynamic item subsets of items received from the item-tracking platforms. Users may define and customize the dynamic item subsets using a client application. The data engine may determine aggregated data about the dynamic item subsets for presentation in a graphical user interface of a client application executing on or otherwise accessible by the client devices.

Abstract: A system that provides for management of resource interaction equipment fulfillment via a gateway apparatus that uses Application Programming Interface (API) services to connect and integrate with the various systems deployed by the equipment providers, such that, all data communication between the managing entity and the equipment providers is orchestrated through the gateway apparatus to track the occurrence of events associated with resource interaction equipment fulfillment. Additionally, a distributed trust computing network is implemented in which each of the equipment providers serve as a decentralized node in the distributed trust computing network capable of converging on a data block to verify the validity of the equipment fulfillment process event stored in the block.

Abstract: Disclosed are various embodiments for self-service integration and feature testing. In one embodiment, a test mode service receives a request to test an integration of a third-party system with a production system. The test mode service enables at least one plugin to test at least one function of the production system. The test mode service executes at least one function using the plugin(s) and data provided by the integration of the third-party system. The test mode service then reports a result of how the production system performs the function(s) associated with the plugin(s) using test data.

Abstract: The present supply chain management system has an e-commerce subsystem having a product inventory database comprising product SKU and pricing data and an e-commerce frontend interfacing the product inventory database for receiving retailer e-commerce orders. The system also has an order management subsystem having an aggregation controller for aggregating the retailer e-commerce orders into supply orders, an aggregation optimizer for optimizing the supply orders; and an order dispatch controller for dispatching the supply orders to suppliers. The system also has an electronic warehouse infrastructure having a pick grid controller having product tracking electronic scanning devices, the pick grid controller configured for generating pick grid instructions for pick-to-zero product placement from supplier pallets received for the supply orders to order pallets configured according to the retailer e-commerce orders.

Abstract: Aspects of the present disclosure provide techniques for integration scoring. Embodiments include importing a set of values from a data source to an electronic data system and assigning each value of the set of values to an import variable of a set of import variables in the electronic data system. Embodiments include displaying in a user interface a value for each import variable in the set of import variables in the electronic data system and receiving, via the user interface, one or more corrections to one or more import variables in the set of import variables. Embodiments include determining a weight corresponding to each import variable for which a correction was received. Embodiments include determining an integration score based on the one or more corrections and the weight corresponding to each import variable in the set of import variables for which a correction was received via the user interface.

Abstract: A method for determining management zones within an agricultural field, the method includes selecting a plurality of remotely sensed images of the agricultural field wherein the plurality of remotely sensed images represent a plurality of growing seasons, each of the plurality of remotely sensed images having a vegetation index associated therewith, generating a refined average image from the plurality of remotely sensed images of the agricultural field, and applying a classification method to define management zones associated with the refined average image.

Abstract: A system and method are disclosed for a supply chain planner to generate a distributional demand forecast for slow-moving inventory in a supply chain. The distributional demand forecast model takes into account explanatory variables and historical sales data to address seasonality and special events and permits sharing of demand information across different stores and stock-keeping units. The supply chain planner performs inference on the explanatory variables and historical sales data to generate process parameters and latent variables. Other embodiments are also disclosed.

Abstract: A system for initiating a completed lading request includes a computing device configured to obtain a lading request from a client device, wherein the lading request comprises a communication detail datum, determine an logical route, wherein determining the logical route further comprises receiving a conveyor indicator, identifying a spot signature as a function of the conveyor indicator, training a route machine-learning mode using a route training data correlating the spot signature to the lading request, and determining the logical route as a function of the spot signature and the lading request using the trained route machine-learning model, and initiate the completed lading request, wherein initiating the lading request further comprises receiving an acknowledgment element, and initiating the completed lading request as a function of the acknowledgement element, and initiating the completed lading request as a function of the acknowledgement element.

Abstract: Systems and methods in accordance with embodiments of the invention impalement adaptive electric vehicle (EV) charging. One embodiment includes one or more electric vehicle supply equipment (EVSE); an adaptive EV charging platform, including a processor; a memory containing: an adaptive EV charging application; a plurality of EV charging parameters. In addition, the processor is configured by the adaptive EV charging application to: collect the plurality of EV charging parameters from one or more EVSEs, simulate EV charging control routines and push out updated EV charging control routines to the one or more EVSEs. Additionally, the adaptive EV charging platform is configured to control charging of EVs based upon the plurality of EV charging parameters collected from at least one EVSE.

Abstract: A floral arrangement customization system allows a user to modify characteristics of each stem or groups of stems within a template to create a customized floral arrangement. The user can also modify characteristics about the arrangement such as its style, shape, or color scheme. Information about the customized floral arrangement is transmitted to an order fulfiller who can assemble the floral arrangement exactly according to the customized design.

Abstract: A method for controlling a plant includes using a neural network modeling technique to calculate a neural network prediction based on plant input data, using a second modeling technique to calculate a second prediction based on the plant input data, and determining whether to use (1) the neural network prediction without the second prediction, (2) the second prediction without the neural network prediction, or (3) both the neural network prediction and the second prediction by comparing a location of the plant input data in a multi-dimensional modeling space to one or more thresholds. The method includes generating a combined prediction using one or both of the neural network prediction and the second prediction in accordance with a result of the determining and controlling the plant using the combined prediction.

Abstract: One example of computerized inventory redistribution control includes, for each location inventory record in a set of location inventory records, calculating a quantity change that will bring a current item quantity to a different item quantity for the location inventory record. Determining a cost of a minimum-cost redistribution among the physical locations to effect the quantity changes. Determining a scaling factor that maximizes total revenue when the quantity changes are scaled by the scaling factor after deducting the cost scaled by the scaling factor. Generating transfer instructions for a redistribution of the item by scaling the transfer quantities of the minimum-cost redistribution by the scaling factor. Transmitting each transfer instruction to a computing device associated with a physical location indicated in the transfer instruction.

Abstract: A customer in a computing resource provider environment, running an application on a VM instance, uses role credentials to request access to one or more web services. The request is forwarded to an enclave associated with the VM instance such that the enclave digitally signs the request and access to the one or more web services is provided.

Abstract: A computer-implemented method includes determining a current state and a current context of an environment in which an automated agent runs to execute a contingent plan. The state indicates that one or more fluents of a plurality of fluents are true, and the plurality of fluents are associated with a contingent problem solved by the contingent plan. The context describes values corresponding to the one or more fluents. An action is performed with respect to at least a subset of the context. A nondeterministic effect of the action on the environment is evaluated, using a computer processor. The state is updated based on the nondeterministic effect. The context is updated based on the nondeterministic effect.

Abstract: A method of correlating probability assertions and resource allocations includes receiving a first probability assertion and a first resource allocation from a first client device; receiving a second probability assertion and a second resource allocation from a second client device; correlating the first probability assertion with the second probability assertion by matching characteristics of the first probability assertion with characteristics of the second probability assertion; and creating a peer-to-peer match between the first request on the second request from the client devices.

Abstract: Systems, methods, and computer-readable media are disclosed for identifying customers having associated opportunities for improved growth and/or profitability with respect to product or service offerings and determining investment solutions that enhance the probability that the customers transition to the higher growth/profitability opportunities. Prior customer transactions are segmented based on segmentation criteria and used to generate a transaction graph. The nodes of the transaction graph represent the segmented transactions and client transaction paths between the nodes represent potential customer life-cycle trajectories. The transaction graph can be used to identify high-value penetration opportunities.