Abstract: Technologies are described for automatic association and sharing of photos with calendar events. For example, photos or similar material associated with a calendar event may be determined and searched for through a variety of resources such as enterprise databases, personal data stores, cloud resources, or even the Internet based on an attribute of each photo and an attribute of the calendar event. Candidate photos resulting from the search may be presented to a user such as an organizer of a meeting or person setting an appointment for confirmation and selection. Upon receiving selection and confirmation of one or more photos from the candidate photos, the one or more photos may be made available to a group of users within a context of the calendar event. Various sharing options such as email, shared cloud storage, or calendar event itself may be used for sharing the photos.

Abstract: A computerized method for controlled testing, comprising: providing a design specification for event data, the design specification including at least one of an event data source, an event data filter, and an event format; retrieving testing metrics; configuring testing events based on the design specification, by: retrieving testing events from the event data source specified in the design specification; filtering the retrieved testing events based in the design specification; and formatting the filtered testing events based on the design specification; generating analysis data by applying testing metrics to the configured event data; generating output data based on testing rules; and generating a user interface to display the output data.

Abstract: The customer order fulfillment system includes an order collection unit for collecting information associated with a plurality of customer orders from a plurality of customers and generating customer order data that includes data associated with each of the plurality of customer orders and the plurality of customers. Each of the plurality of customer order includes one or more items associated therewith. The system also includes an order generating unit for receiving the customer order data from the order collection unit and generating in response thereto consolidated order fulfillment data, and a pick tour generating subsystem for receiving the consolidated order fulfillment data from the order generating unit and in response thereto generating pick tour instructions associated with a pick tour from the consolidated order fulfillment data.

Abstract: A method and system for transforming communication metadata and sensor data into an objective measure of the participant communication distribution of an organization is disclosed. Embodiments of the present disclosure enable the capturing communication data from phone, email, or other virtual means of communication to develop a complete objective model of a human network. Metadata is extracted from the captured communication data and the extracted communication metadata is analyzed by (i) calculating time spent on each activity or interaction (e.g., email, meeting, call, chat, conversation) for each participant; (ii) prioritizing activities and interactions for each participant; and (iii) building a pairwise adjacency matrix based on the attention time each participant spent communicating with each other participant. Based on the pairwise adjacency matrix, a visualization may be created illustrating the communication distribution of the participants throughout the organization.

Abstract: Various embodiments provide a method of connecting an employer with a candidate, comprising: receiving criteria data from the employer regarding a job opening; receiving background data from the candidate; recording data of the candidate in a video interview; analyzing the data of the candidate with speech-to-text analysis to identify candidate data, comparing real-time connection attributes to the candidate data; if a threshold amount of real-time connection attributes are satisfied by the candidate data, then sending, a first offer to the employer for a real-time connection with the candidate; receiving an employer acceptance of the first offer for a real-time connection with the candidate; sending a second offer to the candidate for a real-time connection with the employer; receiving a candidate acceptance; and connecting the candidate and the employer in real time by establishing a live audio connection or a live audio and video connection.

Abstract: Generally discussed herein are devices, systems, and methods for resource retrieval. A method may include determining that a calendar event is scheduled to occur in a specified period of time, responsive to the determination, extracting content of a calendar event on a calendar of the messaging interface, generating a list of resources accessible by the user and related to the extracted content of the calendar event, ranking the resources by a comparison of the extracted content of the calendar event and the content of resources of the list of resources, and causing respective summaries of a specified number of the respective resources with higher respective ranks to be output on the display.

Abstract: Implementations of the present specification provide methods, apparatuses, and electronic devices for resource allocation based on blockchain. The blockchain stores a mapping relationship between a digital digest of an invoice and a resource allocation state corresponding to the invoice. The method includes: receiving a target transaction submitted by a client to participate in resource allocation based on a target invoice; in response to the target transaction, calculating a digital digest of the target invoice, and querying a resource allocation state stored in the blockchain and corresponding to the digital digest; and if the detected resource allocation state is an unallocated state, invoking resource allocation logic declared in a smart contract published in the blockchain, to allocate resources to the client from a predetermined resource pool based on a predetermined allocation rule, and returning a resource allocation result to the client.

Abstract: A Retail as a Service (RaaS) platform enabling a customer of the RaaS platform to make a product available for retail utilizing the resources and expertise of the RaaS platform, and to monitor the effectiveness of retail efforts with data analytics provided by the RaaS platform. The RaaS platform enables intelligent updating of RaaS parameters in real time, and may include one or more of trained staff, product demo procedures, product placement, onboarding technology, product display technology, and a variety of retail facility sensors.

Abstract: A system is provided for operator profiling based on pre-installed sensor measurement. In example implementations, the system extracts a set of segmented time series data associated with a unit of operation and build models which distinguish the operators by machine learning algorithms. The system uses the models to output the evaluation score assigned to each operation, identify the key movements for skilled/non-skilled operators, and recommends appropriate actions to improve operation skill or adjust the scheduling of the operators.

Abstract: A customer order fulfillment system comprising an order collection unit for collecting information associated with a plurality of customer orders and generating related customer order data. The system also includes an order generating unit for receiving the customer order data from the order collection unit and generating in response thereto consolidated order fulfillment data, and a bulk pick order fulfillment unit for receiving the consolidated order fulfillment data from the order generating unit and grouping together similar ones of the items associated with the customer orders to form a plurality of bulk picks, wherein one or more of the bulk picks can form part of one or more bulk pick tours. The system further includes a pick tour generating unit for receiving the consolidated order fulfillment data from the order generating unit and for generating pick tour instructions associated with a pick tour from the consolidated order fulfillment data.

Abstract: The customer order fulfillment system includes an order collection unit for collecting information associated with a plurality of customer orders having items and generating customer order data. Each of the plurality of customer order includes one or more items associated therewith. An order generating unit for receiving the customer order data and generating in response consolidated order fulfillment data, a pick tour generating subsystem for receiving the consolidated order fulfillment data and in response thereto generating pick tour instructions associated with a pick tour, and a bulk pick order fulfillment unit for grouping together similar ones of the items associated with the plurality of customer orders to form a plurality of bulk picks. An automated fulfillment system receives the consolidated order fulfillment data from the order generating unit and automatically selects one or more of the items from one or more carousels, employing the pick tour or the bulk pick.

Abstract: Techniques are disclosed relating to a system capable of processing instances of different versions of a workflow. The system may store workflow information indicating different versions of a workflow. The system may receive requests to create instances of the workflow. The requests may include a first request associated with a first, non-current version of the workflow and a second request associated with a second, different version of the workflow. The computer system may create a set of instances of the workflow, including a particular instance corresponding to the first request. The computer system may receive a request to migrate the particular instance to a particular version different from the non-current version associated with the first request. The computer system may migrate the particular instance to the particular version of the workflow, such that subsequently received instance data for the migrated particular instance is processed according to the particular version.

Abstract: Systems and methods for scheduling early riders (ERs) and late riders (LRs) to vehicles in a multi-modal transportation network (MTN). Stored instructions, when executed, cause a processor to perform acts of forecasting a finite set of scenarios, each scenario having a possible set of forecast LRs (FLRs) itinerary requests. Iteratively, generate ER groups and FLR groups for each scenario, based on a desired time of arrival at a destination. Assign a commuter vehicle (CV) for each ER and FLR group in each scenario. Iteratively, determine for each ER and FLR group a start time and an arrival time at the destination in the corresponding CV, for which, the ER and FLR group are assigned. The iterations continue until a joint schedule for the ERs and the FLRs form each scenario that minimizes an objective function. Formulate assignment information, and transmit the assignment information to the ERs and the assigned CVs.

Abstract: A machine-learning tool evaluates an acquirer's current portfolio and then develops a model portfolio that mathematically redistributes the effect of the current portfolio by suggesting business categories that would better serve the acquirer from a risk/reward perspective. The machine-learning tool is trained with model portfolios and then generates a suggested portfolio that incorporates the acquirer's current partners and supplements them with additional business categories that would improve the risk/reward metric. The machine-learning tool may also select specific businesses from within the suggested business categories for the acquirer to use in achieving the suggested improvement.

Abstract: Systems and methods are provided for managing organizational or corporate structures, including the employee roles or activities administered by human resources. A portion of the role datasets received within human resource records may be used to generate role tokens comprising unique datasets that have been truncated and deduped. Such tokens may be extracted based on assigned prioritization scores, and further assigned training labels representing categorical levels. Predictive labels may be assigned to a remaining portion of the extracted tokens via a logistic regression classifier, and a model organizational dataset may be generated based on the assigned training labels and the assigned predictive labels. The prediction certainty of the role tokens in the model organizational dataset may be used to map the identified role tokens to the roles represented in the human resource records.

Abstract: A fleet management system includes a market component that monitors a hydrogen market and identifies one or more hydrogen parameters associated with the hydrogen market, an electric vehicle component that analyzes the hydrogen parameters and selectively instructs one or more electric vehicles to provide electricity for generating hydrogen based on the hydrogen parameters, and a hydrogen vehicle component that selectively instructs one or more hydrogen vehicles to obtain at least a portion of the hydrogen generated from the electricity provided by the electric vehicles. The fleet management system enables a fleet of vehicles using a plurality of fuel types to be effectively and efficiently managed. Moreover, the fleet management system allows a hydrogen economy to grow in an economical and pragmatic manner.

Abstract: Systems and methods for force-supplying cached API call data are disclosed. A system may comprise a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving initial order data from a user device, the initial order data comprising a product identifier, a user identifier, and a promotion identifier; determining an initial reduction amount based on the received product identifier and promotion identifier; mapping the initial reduction amount to a cache identifier; caching the initial order data and the cache identifier; receiving an order request from a device associated with the user identifier, the order request being associated with the promotion identifier; calling an API to complete the order request; detecting a failure of the API attempting to complete the order request; retrieving the cache identifier; determining a final reduction amount; and completing the order request using the final reduction amount.

Abstract: Methods and systems for analyzing and evaluating item recommendations presented on a web site are disclosed. In one aspect, a user interface is generated for display on a website. Item recommendations personalized for an individual user are displayed within in item recommendation region of the website. Impression, clickstream, and sales data are received from user activity on the website. The impression, clickstream, and sales data are displayed on a dashboard of an administrator user interface. An administrator user can select visualizations to display on the dashboard using selectors for impressions, clicks, sales, users, and time. Two or more sets of data can be overlaid to illustrate relationships between user interactions with recommended items and actual sales of those items. The dashboard is dynamically updated in response to new data received from the website in real-time.

Abstract: A method and a system for predicting business outcomes by analyzing image interests of users are provided. The method includes generation of predictor models based on sample data of tests users. The sample data includes historical data of the test users, images that are of interest to the test users, and answers provided by the test users to psychometric questions. The predictor models are then used to predict psychometric features and business outcomes for a target user based on target data of the target user. The target data includes images that are of interest to the target user, historical data of the target user, and answers provided by the target user to the psychometric questions.

Abstract: A network computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or the transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location, and manage the dynamic queue by sequentially routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs.