Patent classifications
G06Q30/0204
SYSTEM AND METHOD FOR GENERATING AND TRANSMITTING SHAREABLE ELECTRONIC NOTIFICATION DATA VIA A HARDWARE DEVICE NETWORK
Embodiments of the invention are directed to a system and method for generating and transmitting shareable electronic notification data via a hardware device network. A non-transitory wireless signal is broadcasted from a front-line unit in a network of front-line units, and a user determined to be in proximity to the front-line unit receives via the wireless signal reward data from a database. Electronic notification data is transmitted to the user device, whereafter the electronic notification data is displayed and an option to share the reward data to a secondary user is provided. Once shared, the secondary user's user device establishes a connection to the front-line unit to receive the reward data from the rewards database.
SECURE SYSTEM UTILIZING A LEARNING ENGINE
Methods and systems are disclosed for determining resource suitability based at least in part on physical geographic mapping data. A learning/learning engine may be trained to determine such resource suitability using training data. The trained learning/learning engine may then me used to generate suitability indicators. The suitability indicators may be rendered in association with a map comprising the resource. The resource may be configurable to be shared amongst a plurality of physical resource users in a time displaced manner. learning
SYSTEMS AND METHODS FOR MULTI-CHANNEL CUSTOMER COMMUNICATIONS CONTENT RECOMMENDER
Interaction events collected across disparate customer communication channels of an enterprise are processed to generate an encoded unique content item identifier for each content item referenced in an interaction event such that the content item is resolvable to a location in a content repository. A training data set is built using the interaction events thus processed and a multi-channel content recommendation model is trained using the training data set. The multi-channel content recommendation model thus trained stores data points representing intersections of customers and content items that the enterprise has been tracking, with each data point having an effectiveness score for an associated content item. The multi-channel content recommendation model thus trained can be queried by content designers of the disparate customer communication channels through a recommender application for content recommendations based on the effectiveness of the content, agnostic to the disparate customer communication channels.
SYSTEMS AND METHODS FOR WARRANTY RECOMMENDATION USING MULTI-LEVEL COLLABORATIVE FILTERING
Systems and methods are disclosed for warranty recommendations for users based upon warranty selections of peer users. The users are clustered into peer groups based upon industry or market segment based upon user data including primary variables, such as workload type data and market segment data, and secondary variables, such as virtual machine size or number, cluster size, cost, and downtime. New users are matched to a top similar user within their peer group based upon a vector distance, wherein the vector comprises the primary and secondary variables. A current warranty of the top similar user is recommended to the new user. Warranty changes by members of a peer group cause trigger an updated ranking of the peer group warranties. Expert user comments and rankings are used to generate expert user recommendations. A cost-based impact assessment may also be used for warranty recommendations by highlighting favorable and unfavorable warranty properties.
System and Method for Assortment Planning with Interactive Similarity and Transferable Demand Visualization
A system and method are disclosed for interactive product assortment planning and visualization by receiving product attribute values for items of a product assortment is disclosed. Embodiments include displaying icons on an interactive visualization, connecting the icons with transferable demand links, identifying items to be removed from a product assortment, and transporting items among one or more supply chain entities.
System and Method for Assortment Planning with Interactive Similarity and Transferable Demand Visualization
A system and method are disclosed for interactive product assortment planning and visualization by receiving product attribute values for items of a product assortment is disclosed. Embodiments include displaying icons on an interactive visualization, connecting the icons with transferable demand links, identifying items to be removed from a product assortment, and transporting items among one or more supply chain entities.
Systems, methods, and articles of manufacture to measure online audiences
Methods and apparatus to monitor media content at a content display site are described. An example method includes assigning a first set of weights to each of a plurality of panelists based on a set of collected characteristics for each person of a subset of unmeasured persons at unmeasured locations, the subset of unmeasured persons being the unmeasured person for which the collected characteristics are know selecting a subset of the panelists based on the first set of weights, each panelist of the subset of panelists selected to be representative of an unmeasured person of the unmeasured persons, re-weighting the subset of the panelists based on estimated characteristics of the unmeasured persons at the unmeasured locations to generate a second set of weights, generating a virtual panel.
System and method for applying tracing tools for network locations
A method is disclosed for enabling a network location to provide an ordering process for data relevant to connected network devices' activities. The method includes assembling the data, utilizing the activity data, and associating the data, such that information is derived to enable a desired expansion of at least one designated activity. Another method is disclosed for managing an object assignment broadcast operations for a network location based on a network device's previous activities. This second method includes tracing a network device's conduct to determine that a network device prefers a particular class of content. The method also includes tagging a network device's profile with the respective observation and deciding by a network location as to the classification factor for a network device to be targeted for an object assignment broadcast.
METHOD AND SYSTEM FOR EXTRACTING CONTEXTUAL PRODUCT FEATURE MODEL FROM REQUIREMENTS SPECIFICATION DOCUMENTS
The present disclosure extracts contextual product feature model from requirement specification documents where the conventional methods fail to perform. Initially, the system receives a plurality of requirement specification documents pertaining to a product, a domain dictionary, a plurality of configuration parameters, and a plurality of extraction patterns. A product feature model is generated using a NLP based feature extraction technique. The product feature model includes a plurality of product feature elements comprising a feature area, a major feature and a plurality of features arranged hierarchically and classified into feature types. Further, a plurality of ContextType associations like core, client, geography and market are extracted for each of the plurality of features using a ContextType extraction technique. Finally, the plurality of ContextType associations is updated in the product feature model to obtain a contextual product feature model. Various types of feature exports can be generated using a natural language interface.
Methods and apparatus to model on/off states of media presentation devices based on return path data
Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a first probability distribution indicative of actual durations of panel tuning segments, the panel tuning segments corresponding to time periods during which panelists were exposed to first media; generate a second probability distribution indicative of modelled durations of modelled tuning segments, the modelled tuning segments corresponding to modified lengths of the panel tuning segments; and estimate a set-on time for a media set associated with an RPD device based on RPD tuning information and the first and second probability distributions, the RPD tuning information reported from the RPD device, the RPD tuning information indicative of a reported RPD tuning segment during which the RPD device was accessing second media.