Abstract: A system and method for content generation and targeting using machine learning are provided. In example embodiments, a probability that a user will visit a webpage based on historical data is calculated. A probability that the user will engage with a particular content category based on past user engagement is calculated. In response to the probability of the user engaging with the particular content category being equal to or greater than a first threshold, the content is generated. Further, in response to the probability of the user not visiting a webpage meeting or exceeding a second threshold, the generated content is sent to the user.

Abstract: Example methods disclosed herein include accessing a query requesting a metric associated with a number of unique members of an audience of media over an aggregate monitoring interval corresponding to a plurality of component monitoring intervals. Disclosed example methods also include determining respective aggregate interval probability distributions modeling likelihoods of respective monitored individuals being exposed to the media during the aggregate monitoring interval, a first one of the aggregate interval probability distributions for a first one of the monitored individuals being determined by combining parameters of respective component interval probability distributions modeling likelihoods of the first one of the monitored individuals being exposed to the media during respective ones of the component monitoring intervals.

Abstract: Disclosed is a method for determining tactical actions for protecting a reference entity with respect to a plurality of entities in a battlefield environment, the method including: segmenting the battlefield environment into a plurality of layers; associating actable deterrent systems with each layer; obtaining data representative of the probability, for each deterrent system, that the considered deterrent system deters an entity in the associated layer; providing, for each entity, the level of threat of the entity; and computing a cost function for determining the deterrent systems to be engaged by the reference entity for rendering extremal the cost function, the cost function being a function depending from the provided level of threat and the obtained data.

Abstract: The disclosed embodiments relate to a technique for training a prognostic pattern-recognition system to detect incipient anomalies that arise during execution of a computer system. During operation, the system gathers and stores telemetry data obtained from n sensors in the computer system during operation of the computer system. Next, the system uses the telemetry data gathered from the n sensors to train a baseline model for the prognostic pattern-recognition system. The prognostic pattern-recognition system then uses the baseline model in a surveillance mode to detect incipient anomalies that arise during execution of the computer system. The system also uses the stored telemetry data to train a set of additional models, wherein each additional model is trained to operate with one or more missing sensors. Finally, the system stores the additional models to be used in place of the baseline model when one or more sensors fail in the computer system.

Abstract: An online system obtains a set of resolved impressions based on historical data about multiple publishers. A set of features is then extracted, for each resolved impression, based on a comparison of historical data about the first publisher and the second publisher. The online system performs training of a machine-learned model based on the set of features. Data about a plurality of new impressions are input into the trained machine-learned model to obtain an output of the trained machine-learned model. A reach overlap metric and unique reach metric can be computed based on the output of the trained machine-learned model.

Abstract: A server of a transportation network determines characteristics of trips provided to users, as well as the usage of the services by users. Using the determined characteristics, the server trains a model that, for a given set of trips for a user, estimates a degree of likely user dissatisfaction with the trips. Based on the estimated degree of user dissatisfaction, the system can estimate user dissatisfaction in real time, directly after completion of a trip, and can take remedial actions should the user be estimated to be likely dissatisfied.

Abstract: Systems, methods, and non-transitory computer-readable media can generate layered training data for determining embeddings for entities that are accessible through the social networking system, wherein the layered training data includes layers of data that are organized by a hierarchy, and wherein each layer of data corresponds to entities of a same type. A respective embedding for each entity in a set of entities can be determined, wherein the embeddings are trained iteratively using each layer of data in the layered training data. One or more candidate entities that are related to a first entity can be determined based at least in part on the respective embeddings for the candidate entities and the first entity. At least a first candidate entity from the one or more candidate entities can be provided as a recommendation to a user that formed a connection with the first entity.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method as described herein are directed to a Personalized Article Engine that generates respective prediction models for each article in a plurality of candidate articles in a social network system. The Personalized. Article Engine generates a respective article score according to each article's prediction model and at least one feature of a target member account. The Personalized Article Engine generates a plurality of output scores based on combining each respective article score with a corresponding article's global model score. The Personalized Article Engine ranks the output scores to identify a subset of candidate articles relevant to the target member account.

Abstract: A data annotation apparatus for machine learning is provided, which includes a stimulus generation portion, a biometrics reading portion, and a data integration portion. The stimulus generation portion is configured to generate, and present to an agent, at least one stimulus based on a first data from a first machine learning dataset. The biometrics reading portion is configured to measure at least one response of the agent to the at least one stimulus, and to generate biometrics data based on the at least one response. The data integration portion is configured to integrate the biometrics data, data of the at least one stimulus, and data of the first machine learning dataset to thereby obtain a second machine learning dataset. The data annotation apparatus can result in an improved data labeling and an enhanced machine learning.

Abstract: Machine-learning methods and apparatus are provided to solve blind source separation problems with an unknown number of sources and having a signal propagation model with features such as wave-like propagation, medium-dependent velocity, attenuation, diffusion, and/or advection, between sources and sensors. In exemplary embodiments, multiple trials of non-negative matrix factorization are performed for a fixed number of sources, with selection criteria applied to determine successful trials. A semi-supervised clustering procedure is applied to trial results, and the clustering results are evaluated for robustness using measures for reconstruction quality and cluster separation. The number of sources is determined by comparing these measures for different trial numbers of sources. Source locations and parameters of the signal propagation model can also be determined.

Abstract: Computer-based models can be developed, deployed, and managed in an automated manner. For example, a model building tool can be selected based on the model building tool being compatible with one or more parameters. A first machine-learning model can be generated using the model building tool and trained using a training dataset. The first machine-learning model can then be used to perform a task. Thereafter, a new model-building tool can be selected based on the new model-building tool being compatible with the one or more parameters. A second machine-learning model can be generated using the new model-building tool and trained using the training dataset. The accuracy of the first machine-learning model can be compared to the accuracy of the second machine-learning model. Based on the second machine-learning model being more accurate, the second machine-learning model can be used to perform the particular task rather than the first machine-learning model.

Abstract: Under one aspect, a computer-implemented method includes receiving a query at a query interface about whether a computer file comprises malicious code. It is determined, using at least one machine learning sub model corresponding to a type of the computer file, whether the computer file comprises malicious code. Data characterizing the determination are provided to the query interface. Generating the sub model includes receiving computer files at a collection interface. Multiple sub populations of the computer files are generated based on respective types of the computer files, and random training and testing sets are generated from each of the sub populations. At least one sub model for each random training set is generated.

Abstract: A method operative at an identity provider enforces a digital rights management (DRM) scheme associated with a piece of content. The identity provider is an entity that participates in a “federation” with one or more other entities including, for example, an service provider (e.g., a content provider), a DRM privileges provider, and a DRM policy provider. In one embodiment, the method begins by having the identity provider obtain and evaluate against a DRM policy a set of DRM privileges associated with the end user requesting access to the piece of content. Based on the evaluation, the identity provider generates a single sign on (SSO) message that includes a reference to the set of DRM privileges. The message is then forward to the service provider entity, which provides the end user a response.

Abstract: A system is disclosed for determining a real-time probability iteratively throughout a period of time. The system conducts an upgrade analysis by determining that an expected marginal seat revenue for a sale of an additional coach seat is greater than an expected marginal seat revenue for a sale of an additional first class seat.

Abstract: A method and system for addressing NP hard problems that more efficiently generates partial solution sets with more easily identifiable, locally optimized solutions. The invented method increases the quantity of n factors that might effectively be considered in developing incomplete solution sets for NP hard problems. The invented method broadens the capacity of computer technology to address NP hard problems where solutions would be practically impossible to generate. A plurality of assets are assigned by designating lower valued assets to lower ranked requests. When all assets of a lower type are assigned, the remaining unassigned requests are allocated to unassigned assets of the next higher type. When all assets of the highest type are classified, selected assets may be then reassigned to insure that higher valued requests are assigned to assets, permitting lower valued requests to (a.) be assigned to lower valued assets; or (b.) be unassigned and thereby denied.

Abstract: Examples described may enable rearrangement of pallets of items in a warehouse to an optimal layout. An example method includes receiving real-time item information including pallet locations in a warehouse and real-time inventory of items arranged on the pallets; determining a likelihood of demand for future access to the pallets based on a pallet relocation history and item receiving/shipment expectations; based on the real-time item information and the likelihood of demand, determining an optimal controlled-access dense grid layout in which distances of the pallets from a center of the layout are related to the likelihood of demand; receiving real-time robotics information and using the real-time robotics information to determine an amount of time to rearrange the pallets to the optimal layout; and, based on the amount of time to rearrange the pallets being less than a threshold, causing the robotic devices to rearrange the pallets to the optimal layout.

Abstract: Examples described may enable consolidating pallets of items in a warehouse. An example method includes receiving real-time item information including pallet locations in a warehouse and inventory of items arranged on the pallets; based on the real-time item information, identifying a set of pallets of which at least one pallet includes less than a threshold quantity of a type of item; receiving real-time robotics information and determining, based on the real-time item and robotics information, an amount of time to condense the items on the set of pallets into a single pallet and a quantity of pallets that will become empty as a result of condensing the items; and, based on the amount of time being less than a threshold time and the quantity of pallets exceeding a threshold quantity of pallets, causing robotic devices to condense the items into the single pallet.

Abstract: A system for tracking, assigning, and issuing equipment to security agency personnel (e.g., officers, administration, command, armorer). An armorer is assigned the task of tracking, assigning, and issuing equipment. Equipment may be assigned to a particular individual officer. The equipment provided to and used by officers may capture (e.g. gather, produce) information (e.g. audiovisual information, data logs, recordings). Equipment may provide information to the armorer via near field communication (NFC) circuits. The information captured may be used alone or in combination with other information received and stored by an evidence management system. The information captured by equipment assigned to a particular individual may be associated with that individual. An armorer may use information supplied by equipment, evidence management system, officers, or other sources to assist in the assignment process.

Abstract: Disclosed are various embodiments of a food safety management system, including a web portal for management and reporting and a handheld computing device for checklist completion. A checklist of tasks to be performed in a food service establishment is obtained and displayed on a touchscreen of the handheld computing device. Confirmation is obtained on the touchscreen whether a task has been completed. An identifier at a location in the food service establishment is inputted to verify that a task has been completed. Temperature and humidity readings are obtained from one or more stationary sensors monitoring a food storage environment. Task completion data, temperature data, and humidity data are sent to a server.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for updating business model mappings. A computer receives a plurality of business models and a plurality of model mappings, wherein the plurality of model mappings show how elements of one of the plurality of business models relates to another element of another of the plurality of business models. The computer determines that information contained within at least one of the plurality of business models has been changed and determines how the changed information contained within the at least one of the plurality of business models affects at least one model mapping of the plurality of model mappings. The computer updates the model mapping to reflect the updated, changed, or altered information of the at least one of the plurality of business models.

Abstract: A computer implemented product development method characterized in an algorithmic formulation of an optimization problem within a multidimensional solution space and a following software-technical optimization which is in the sense of a control loop permanently adjusting the running development process in direction of a calculated optimum is provided. Therefore a three-dimensional solution space with a purpose dimension, an architecture dimension and a strategy dimension have to be established, market needs strategic imperatives, architecture and for each dimension quality criteria have to be stored and after that the three dimensions have to be balanced according to its fulfillment of the quality criteria after each phase of the development. The advantage is a higher efficiency in development due to a more holistic approach which is better reflecting the interdependencies within a real production development process.

Abstract: In one example, an enterprise news service may leverage knowledge of existing collaborative relationships between workers to pre-populate news sources for the news feed of a worker. The enterprise news service may determine an enterprise relationship describing a relationship within an enterprise between a worker and a colleague. The enterprise news service may associate the colleague with a news source set based on the enterprise relationship. The enterprise news service may receive a news item from the colleague. The enterprise news service may post the news item to a news feed of the worker based on the enterprise relationship.

Abstract: Systems and methods for creating volume/market weighted average price benchmark indexes for perishable agricultural products. At least one user device constructed and configured in network-based communication with an analytics platform. The analytics platform collects, analyzes, validates and normalizes data elements for the perishable agricultural products in real time, thereby generating processed data. The analytics platform calculates a benchmark price for a perishable agricultural product weighted by traded volumes based on the processed data and location data. The at least one user device is operable to receive and display the benchmark price.

Abstract: A demand response management system which may be implemented with demand response logic. The system may be used by utilities, independent system operators, intermediaries and others to manage operations of demand response programs relative to customers, clients, participants, and users of outputs from the utilities, independent system operators, and the like. Demand response logic of the demand response management system may provide demand signal propagation and generation from demand response events.

Abstract: An aspect provides a method, at a handheld portable information handling device with a touch screen display, communicating to a hospital transport management system information sufficient to authenticate the user of the handheld portable information handling device; obtaining information from the hospital transport management system relevant to the user of the handheld portable information handling device; displaying the information from the hospital transport management system in a manner that is related to the workflow of the user of the handheld portable information handling device; and communicating to the hospital transport management system information about the workflow of the user of the handheld portable information handling device; and communicating to the hospital transport management system information about the workflow of the user of the handheld portable information handling device. Other aspects are described and claimed.

Abstract: Systems, methods, and software can be used to improve efficiency of a cargo shipping system. In some aspect, a cargo transportation unit (CTU) status notification is received from a cargo tracking device coupled with a CTU. The CTU status notification indicates a load status of the CTU. The CTU is determined to be ready for shipment based on the CTU status notification. Availability information associated with each of a plurality of drivers is received. A payment associated with each of the plurality of drivers is determined. A driver is selected from the plurality of drivers based at least in part on the availability information and the payment for the driver. A delivery request is sent to the selected driver.

Abstract: A system and method for visualizing parking enforcement officer movement in real time with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: The present invention extends to methods, systems, and computer program products for optimizing selection of battery electric vehicles to perform delivery tasks. Within a group of battery electric vehicles (“BEVs”), a BEV is selected to perform a delivery task based on battery charge status. The BEV can be selected based on one or more of: proximity to a requested pick up location, battery state-of-charge (“SOC”), charging station proximity to a requested delivery location, and charging station port availability (e.g., wait time to access a charging port). BEV selection can be optimized such that a BEV arrives at a charging station with optimal remaining SOC. Thus, the distance to charging stations can be optimized while meeting the needs of customer requests to get a delivery from a pickup location to delivery location. In some aspects, autonomous vehicle technology is used to operate BEV's.

Abstract: A system tool that provides dispatchers in power grid control centers with a capability to manage changes. Included is a user interface and a plurality of scheduler engines. Each scheduler engine is configured to look ahead at different time frames to forecast system conditions and alter generation patterns within the different time frames. A comprehensive operating plan holds schedules generated by the plurality of scheduler engines. A relational database is coupled to the comprehensive operating plan. Input data is initially received from the relational database for each scheduling engine, and thereafter the relational database receives data from the scheduling engines relative to forecast system conditions.

Abstract: A transport facilitation system can receive current location data from driver devices of drivers operating throughout a given region. The system can further receive a pick-up request from a user device of a requesting user within the given region, the pick-up request including pick-up location data. The system can determine a plurality of candidate drivers to service the pick-up request based, at least in part, on the pick-up location data and current location data of the candidate drivers. The system can predict a future location for each of the candidate drivers and select a first driver from the candidate drivers to service the pick-up request based on the predicted future locations. The system may then transmit a transport invitation to the first driver to service the pick-up request.

Abstract: A method of generating a business process model includes receiving a description of a select business process in electronic form, processing the description of the select business process at the computerized system using a natural language processing algorithm to parse business activities from the description, searching a business concept repository using a search engine for existing business concept models related to each business activity parsed from the description, and displaying each existing business concept model resulting from the searching in a graphical representation for manipulation by a process designer using a business concept manipulation tool to form a specific business process model for the select business process. The select business process is associated with a domain-specific business type. A computerized system for designing and modeling business processes for use in business process management is also provided.

Abstract: A device may communicate with a client device to provide, via a user interface of the client device, a set of prompts regarding an entity. The device may detect one or more user interactions with the user interface associated with indicating a set of responses to the set of prompts. The device may process data identifying the set of responses to the set of prompts to generate a set of scores for a set of recommendations based on processing the data identifying the set of responses to the set of prompts. The device may determine a ranking of the set of recommendations based on the set of scores. The device may select one or the set of recommendations based on the ranking. The device may communicate with the client device to provide information associated with the set of recommendations based on selecting the set of recommendations.

Abstract: Multi-variable assessment systems and methods that evaluate and predict entrepreneurial behavior are provided herein.

Abstract: A computer system, method, and computer-readable product for providing data for career advice, such as job or education recommendations, from automated review and analysis of career-related data for an individual, which is at least initially obtained from documents, such as resumes and writing samples. For a designated individual, career-related data is obtained from the documents and an initial personality estimate is created for the designated individual based upon, at least, the obtained career-related data. One or more latent factor models for known career-personality matches are then gathered from a database and a questionnaire is provided to the individual to gather further information and augment the personality estimate. The created personality estimate is integrated with the latent factor model(s) to create career advice data.

Abstract: A system and method for motivating parking enforcement officer performance with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: A method for tracking procedures performed on personal protection equipment (PPE) and actions of individuals includes the following steps. An article of PPE configured with a smart tag is provided to an individual prior to performance of a task. After the individual performs the task, the article of PPE is processed. Information is retrieved from the smart tag during at least one of: before, during and after processing the article of PPE. After the performance of the task, the individual's data is read and the individual enters into a designated area.

Abstract: An approach is provided for rearranging assignments of workers to teams in an agile environment. Project requirements are collected and skills of workers are determined. Based on the project requirements and the skills, an initial arrangement of assignments of the workers to the teams is generated. During project execution, data from sensors worker locations and content of communications among the workers are obtained. The data from the sensors identifies workers who are sitting on chairs. Based on the data from the sensors, worker locations, and the content of the communications, a weighted graph is generated that represents the workers, strengths of relationships among the workers, and strengths of relationships between the workers and the teams. Based on the weighted graph, an optimal rearrangement of the assignments of the workers to the teams is automatically and dynamically generated. The optimal rearrangement specifies a match between the skills and the project requirements.

Abstract: Systems and methods for allocating tickets are described. When ticket is received, system looks for suitable agents for allocating the ticket. The system computes plurality of agents scores corresponding to plurality of agents. Based on the agent-scores, first-set of agents are identified. System further identifies second-set of agents from the first-set of agents based on some dynamic parameters like physical and emotional state of the agents, and further, ranks the second-set of agents. Now system makes an attempt to allocate the ticket to first best agent having highest rank. If the first best agent is available, system allocates the ticket. However, if the first best agent is unavailable, system looks for next best agent. If again the next best agent is unavailable, the system re-allocates current active ticket being handled by the next best agent to another next best agent and allocates the ticket to the next best agent.

Abstract: An information processing method includes: detecting, by a computer, an execution, by a worker, of a first task not included in a first task flow or a second task that is a task included in the first task flow and is other than a task assigned to the worker; receiving input of the first task or the second task; reflecting a change based on the first task or the second task in the first task flow; and storing difference information on a difference from the first task flow based on reflection of the change in a memory in association with the worker.

Abstract: A method and system for generating a selection alert are disclosed. The method includes receiving an input identifying a client user at a server, retrieving information related to a project for the client based on the input, and retrieving information related to a plurality of pro users based on the project information. The method also includes selecting one of the pro users from a pro user database, where the selection is based both on a professional characteristic parameter of the pro user and on a personal characteristic parameter of the pro user, generating a selection alert indicating the selection of the pro user, and sending the selection alert to the client user device from the server.

Abstract: A system and method for providing conditional autonomous messaging to parking enforcement officers with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: A system and method for coordinating parking enforcement officer patrol in real time with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and ongoing activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: Methods and apparatuses are described for efficient resource management using mobile devices and wearable devices. A server determines an event causing unavailability of a center in a distributed network. The server determines an expected demand for service from the distributed network during an upcoming time period and identifies a mobile device and a wearable device associated with each staff member assigned to work at one of the plurality of centers that is available. The server retrieves location data from the mobile device and biometric data from the wearable device. The server identifies staff members capable of working and initiates a communication to the mobile device associated with each staff member capable of working. The server receives a response from the mobile device indicating whether the staff member has accepted and determines whether the expected demand from the distributed network during the upcoming time period is satisfied.

Abstract: Systems and methods for verifying and monitoring employees are provided. Employees call-in to the system at scheduled times. If an employee misses a scheduled call-in, an alert can be generated. An employer notification process can generate the alert, notifying a supervisor of the employee's missed call. The alert can include the employee's name, the location of the employee, and the time he/she was supposed to call. Such systems and methods can be used to verify that a worker is at the proper location at the proper time and awake and alert during the entire time period that he/she is supposed to be working.

Abstract: Embodiments of the present invention are directed to a computer-implemented machine-learning method and system for automatically creating and updating tasks by reading signals from external data sources and understanding what users are doing. Embodiments of the present invention are directed to a computer-implemented machine-learning method and system for automatically completing tasks by reading signals from external sources and understanding when an existing task has been executed. Tasks created are representable and explainable in a human readable format that can be shown to users and used to automatically fill productivity applications including but not limited to task managers, to-do lists, project management, time trackers, and daily planners. Tasks created are representable in a way that can be interpreted by a machine such as a computer system or an artificial intelligence so that external systems can be delegated or connected to the system.

Abstract: Some embodiments of the invention provide systems and methods for analyzing the deployment of employees in a restaurant. For example, some embodiments are directed to determining whether an employee who has vacated his/her assigned station has acted appropriately in doing so, and if not, causing the employee to be redirected to his/her assigned station. Determining whether an employee acted appropriately in leaving his/her assigned station may involve analyzing video recordings of the restaurant at or around the time the employee left his/her station, operational data describing events occurring in the restaurant at or around the time the employee left his/her station, and/or other information, which may supply valuable context in determining whether or not the employee acted properly. If the employee acted improperly, he/she may be redirected to his/her assigned station, using automated, semi-automated and/or manual techniques.

Abstract: A system and method for facilitating parking enforcement officer performance in real time with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: A system and method for monitoring parking enforcement officer performance with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: A system and method for managing coverage of parking enforcement for a neighborhood with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.

Abstract: A system and method for facilitating parking enforcement officer dispatching in real time with the aid of a digital computer is provided. A time-based active representational model of the city is created by fusing sensory data collected from various sources around a city with numerical data gleaned from historical and on-going activities, including parking regulation citation and warning numbers, resource allocations, and so on. The model can be used to form quantitative predictions of expected violations, revenue stream, and so forth, that can then be used as recommendations as to where to enforce and when, so as to maximize the utilization of the limited resources represented by the officers on the street. Moreover, the performance of the officers can be weighed against expectations of performance postulated from the quantitative predictions.