Abstract: Information can be provided in a convenient manner to help a user decide what events to attend. The information can include information regarding a popularity of the events. The popularity of the events can be based upon the number of people expected to attend, the number of the user's friends expected to attend, and/or the number of people fitting user-defined criteria who are expected to attend. The events for a user-specified time period can be shown on a map along with information representing the popularity of the events. Thus, the user can choose to attend those events in the user's area which are more popular. The map can be displayed on a user device, such as a cellular telephone. In this manner, the user can more readily attend those particular events which the user is more likely to enjoy.

Abstract: An example computing system is configured to: (i) apply a first access permission setting that defines whether a party can access a data object associated with a multi-phase construction project during a first phase of the multi-phase construction project; (ii) determine that the multi-phase construction project has transitioned from the first phase to a second phase; and (iii) based at least on the determination that the multi-phase construction project has transitioned from the first phase to the second phase, apply a second access permission setting that defines whether the party can access the data object associated with the multi-phase construction project during the second phase of the multi-phase construction project, where the second access permission setting differs from the first access permission setting.

Abstract: Techniques for a modeling platform associated with simulating risk models. According to certain aspects, systems and methods include simulating the impact of qualitative assumptions on the risk model. Accordingly, the risk model may include a hierarchical tree formed of component qualitative assumption objects and quantitative assumption objects. Quantitative assumption objects include indications of distribution function parameters associated with the assumption object and qualitative assumption objects include an indication of an impact on a parent quantitative assumption. When simulating the risk model, systems and methods may adjust sampled values quantitative assumption object when a child qualitative assumption object is enabled.

Abstract: Energy consumption modelling requires to consider various factors affecting the energy consumption in buildings, to be able to effectively forecast future consumption. Even though some of the state of the art deep learning based approaches are able to address these requirements to some extent, they are computationally heavy. The disclosure herein generally relates to energy forecasting, and, more particularly, to a method and system for graph signal processing (GSP) based energy modelling and forecasting. The system monitors and collects information on energy consumption in a building and values of associated energy consumption parameters. This input data is further processed using GSP to generate a building energy consumption model, from which a smooth signal is obtained by applying total variation minimization. The system further performs forecasting using the smooth signal.

Abstract: A system includes a computer processor, a computer memory, and a user interface. The system receives a plurality of tasks, data relating to conditions and environments associated with the plurality of tasks, and a plurality of goals relating to planning and scheduling of the plurality of tasks. The goals are received from a plurality of sources, and the goals are addressed as a function of the conditions and environments. The system displays on the user interface, as a function of the plurality of goals, an analytical view of the conditions and environments relating to the plurality of tasks and an analytical view of a status of the plurality of tasks.

Abstract: A method for improving processing of data from a plurality of data sources by extracting signals from data sets includes retrieving the data from the plurality of data sources, generating a correlation matrix or a covariance matrix based on the retrieved data, performing an eigenvalue decomposition on the correlation matrix or the covariance matrix to determine a set of eigenvector loadings, and converting a result of the eigenvalue decomposition into an indicator of a common signal among the retrieved data. Converting the result of the eigenvalue decomposition into the indicator of the common signal includes applying a loading from the set of eigenvector loadings as a weight to at least one corresponding observation in the retrieved data from the plurality of data sources, and recursively repeating the steps of retrieving, generating, performing, and converting.

Abstract: Various methods, apparatuses/systems, and media for managing metadata are disclosed. A processor extracts technical metadata corresponding to enterprise applications from a plurality of databases; builds a metadata repository in a graph database; builds a web-based metadata application based on developing a normalized representation for data flows corresponding to the extracted technical metadata by utilizing the graph database. The extracted technical metadata is stored onto the metadata repository in the graph database. The processor authenticates and authorizes a user to utilize the web-based metadata application; receives search criteria from the user; accesses the metadata repository in the graph database to retrieve the technical metadata and/or data lineage within the enterprise applications from the metadata repository based on received search criteria; and displays the technical metadata and/or the data lineage within the enterprise applications onto a user interface.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for determining a probability of presence for a user of a first device at a second media presentation with a second device. An example apparatus includes memory, instructions in the apparatus, and processor circuitry to execute the instructions to determine a first probability of presence based on a first demographic impression, a non-demographic impression, and a shared data item, the first demographic impression logged by a database proprietor for a first device, the shared data item provided by the first device, the first probability of presence indicative of a likelihood that a user of the first device corresponds to the non-demographic impression.

Abstract: A construct information management system and method for enabling handling of different types of data is provided. A construct information management system 1 for managing information related to a construct includes: a data collection unit 11 configured to collect different types of source data related to different types of constructs from prescribed data sources 2A, 2B, 3A, 3B and retain the collected source data; and a data management unit 12 configured to map the collected source data onto a prescribed spatiotemporal model, acquire prescribed data associated with input data on the basis of at least mapping information on the prescribed spatiotemporal model, and process and output the acquired prescribed data.

Abstract: Techniques for a modeling platform associated with simulating risk models. According to certain aspects, systems and methods include simulating the risk model over time. The risk model may include a hierarchical tree formed of component assumption objects associated with distribution functions. The systems and methods may apply a time function to generate time-adjusted values for the component assumption objects corresponding to defined distribution functions. The systems and methods may then combine the time-adjusted values to generate time-adjusted values for parent assumption objects.

Abstract: A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.

Abstract: Methods and computer readable medium for queue management are disclosed. The method includes displaying a queue panel including two or more queue categories of queues. A queue is configured to include items that have at least one parameter is common. The queue panel is further configured to display activity data corresponding to queues in at least one of the two or more queue categories. The method also includes determining whether the activity data needs to be refreshed, identifying a list of queues belonging to the at least one queue category; generating a refresh request for the identified list of queues; communicating the refresh request to a remote server; receiving updated activity data from the remote server for the identified list of queues; and updating the activity data displayed in the queue panel based on the received updated activity data.

Abstract: Natural language can be used to conduct a conversation that yields analytic results. An interactive user interface can present suggestive content associated with a natural language input to a user. The suggestive content can guide assist the user in obtaining analytic data/information relating to a business, industry, and/or the like. An ontology comprising one or more content items associated with the natural language input can generated. The ontology can be represented as and/or associated with a data structure that temporal correlates a plurality of content items to the natural language input.

Abstract: A method and an apparatus for creating a workflow, the method being performed by a computing device, and including obtaining a log file generated while a user performs a task, parsing each of a plurality of events recorded in the log file, and creating an activity sequence to correspond to an order of the events, grouping a plurality of partial sequences extracted from the activity sequence, and creating a plurality of activity groups to correspond to each of a plurality of different repetitive tasks included in the task and creating the workflow of at least one activity group among the plurality of activity groups.

Abstract: Exemplary implementations may provide a workforce sentiment and structure descriptions. A survey management tool can solicit and retrieve ratings data from employees via a survey. The received ratings can be aggregated and scaled according to employee ratings to identify and adjust for the impact of influential employees. An organizational chart may be updated based on the survey results and users may navigate the updated organizational chart to review employee ratings.

Abstract: A program is executed on a processor to produce execution events. The execution events are traced using a first trace mode during a first portion of the program execution, wherein a portion of trace information for the execution events is omitted from a trace report while tracing in the first trace mode. The mode of tracing is dynamically changed to a second trace mode in response to an event trigger, such that all execution events that occur during the change of mode are captured. Execution events are traced during a second portion of the program execution using the second trace mode, wherein additional trace information for the execution events is included in the trace report while tracing in the second trace mode. The trace mode may be dynamically switched between the two trace modes during execution of the program.

Abstract: A server computing device generates an input data set by determining a set of user information, a set of market index information, and available annuity products. A machine learning processor executes a price optimization module to traverse a computer-generated annuity matching model and select a subset of the available annuity products that are associated with product characteristics that match user objectives and generate annuity product recommendations for the user. The processor executes a market simulation module to traverse a computer-generated annuity perfor-mance prediction model using the annuity product recom-mendations and predictions of market performance to gen-erate simulated outcomes for each of the annuity products. A client device generates a graphical user interface for display to the user via a display device, the graphical user interface including visual representations of each of: the annuity product recommendations and the simulated out-comes.

Abstract: A computer system receives customer records listing customer attributes and an adoption status of the customer, such as whether the customer has enrolled in a particular energy efficiency program. An initial set of patterns are identified among the customer records, such as according to a decision tree. The initial set is pruned to obtain a set of patterns that meet minimum support and effectiveness and maximum overlap requirements. The patterns are assigned to segments according to an optimization algorithm that seeks to maximize the minimum effectiveness of each segment, where the effectiveness indicates a number of customers matching the pattern of each segment that have positive adoption status. The optimization algorithm may be a bisection algorithm that evaluates a linear-fractional integer program (LFIP-F) to iteratively approach an optimal distribution of patterns.

Abstract: The present invention relates to the use of free delivery to create a new system, method, and apparatus used for uploading, listening, voting, organizing, and downloading of music, and/or video, which optionally may be used in conjunction with a hybrid hard copy/soft copy advertising and marketing that also includes a coupon exchange system. The present invention also includes a novel “flush” vote system for rating music, and/or video.

Abstract: Multidimensional data analysis applications, including OLAP applications, simultaneously aggregate across many sets of dimensions. However, computing multidimensional aggregates is a performance bottleneck for OLAP data analysis applications. In order to improve the speed of interactive analysis, OLAP databases often precompute aggregates at various levels of detail and on various combinations of data attributes. However, the cost and speed of precomputation influences how frequently the aggregates can be brought up-to-date. Systems and methods disclosed herein provide graph based multidimensional analysis processing without pre-aggregating or precomputing the data along dimensional hierarchies, and by providing the results to the end user on-demand. Since preaggregation or precomputation of data along dimensional hierarchies is not necessary, implementations allow the end user to perform data analysis as soon as the data is available.