Abstract: Systems, methods, and computer-readable media are disclosed for filtering data with probabilistic filters for content selection. In one embodiment, an example method may include determining a user interaction history with a first product identifier for a user account, determining a first parent product identifier of the first product identifier, and generating a database with the first parent product identifier and a user account identifier for the user account. Example methods may include determining a set of candidate content with first content and second content for the user account, determining a second product identifier associated with the first content, and determining a second parent product identifier of the second product identifier. Example methods may include determining that the second parent product identifier is not present in the database using a probabilistic filter, and determining that the first content is eligible for presentation.

Abstract: Integrating a fulfillment service provider into a third-party application via an Application Programming Interface (API) is described. In an example, a computing device associated with a fulfillment service provider can determine, based at least in part on an indication of an interaction between a user and a third-party application, that the fulfillment service provider has been initialized. In one example, functionality associated with the fulfillment service provider can be accessible to the third-party application via an API. In at least one example, the computing device can generate, based at least in part on the interaction with the third-party application and while the fulfillment service provider is initialized, a recommendation of at least one of a service, a merchant, or an item associated with the fulfillment service provider. The computing device can cause the recommendation to be presented via at least one of the third-party application or the fulfillment service provider.

Abstract: An Indoor location mapping and wayfinding system for mapping waypoints on an interactive mapping system that can function both indoors and outdoors based on user selections and location. It can include a shopping system that allows users to pre-select items for purchase, maps the items on an indoor map of the store, and provides a route to the user for the collection of the selected items.

Abstract: Technologies relating to generation of training data for use in training a computer-implemented ranker are described. A product name extracted from a URL in a log entry of a search log of a search engine is mapped to a catalog product name from a catalog of a website, wherein the catalog product name identifies a product that is available for acquisition by way of a webpage of a website. A query assigned to the URL in the log entry is assigned to the catalog product name due to the product name being mapped to the catalog product name. The computer-implemented ranker is trained based upon the query being assigned to the catalog product name.

Abstract: A system and method of displaying advertising content includes transmitting data associated with a vehicle to a data center. An advertisement is generated based on the transmitted data. The advertisement is transmitted to the vehicle. An evaluation period is determined during which the advertisement is prevented from being displayed. The advertisement is displayed on a display of an in-vehicle infotainment system following the evaluation period.

Abstract: A method and a system segmenting a user viewing listings in online publications to render the listing according to a rule received from a seller. For example, the system receives one or more listings submitted by a seller. The listing comprises one or more modifiable parameters. The system also receives a rule from the seller, the rule associated with a first listing of the one or more listings. A profile is associated with a user based on data collected about the user. The first listing is rendered to the user based on the profile associated with the user and the rule by modifying the one or more parameters.

Abstract: Techniques performed by a data processing system for caching data herein include initializing a single instance of a persisted cache service on the data processing system, receiving data requests from a plurality of single page applications (SPAs) on the data processing system, processing the data requests using the persisted cache service to obtain requested data from a cache implemented on the data processing system or from one or more remote data sources via a network connection, and providing the requested data obtained from the cache or the one or more remote data sources to an SPA of the plurality of SPAs from which each data request originated.

Abstract: In an approach for constructing private profile machine learning models for recommending products to a user, a processor gathers user data associated with interactions of the user on an ecommerce website. A processor analyzes the user data using machine learning (ML) techniques. A processor trains a private profile ML model on the analyzed user data, wherein the private profile ML model is stored on a private storage of the user. A processor predicts a product recommendation using the private profile ML model. A processor outputs the product recommendation.

Abstract: Data for interactions performed by users through a portal page is collected. The data comprising a plurality of sequences of interactions performed by a user on representations of products displayed in the portal page. The plurality of sequences of interactions are input to train a neural network on temporal dependencies between interactions within a sequence from the plurality of sequences. The plurality of sequences are processed by the neural network through a plurality of learning layers to generate a model for product identification. Upon receiving an interaction by a first user at the portal page in relation to a product from the products and based on the model, identifying a first product from the products to be displayed in the portal page for the first user.

Abstract: A seasonal recommender system includes a computing device configured to obtain periodic sales data characterizing a number of purchases made of each item of a plurality of items in a specified period and to obtain periodic buyers data characterizing a number of unique customers of each item in the plurality of items in the specified period. The computing device is further configured to determine a final item seasonality embedding for each item based on the periodic sales data and the periodic buyers data and to determine a final user seasonality embedding for each user based on the periodic purchase data. The computing device is further configured to determine a final user-item score for each item based on the final item seasonality embedding and the final user seasonality embedding and to send a recommendation to a user based on the final user-item score.

Abstract: A merchant may operate a retail store that users are able to visit in person in order to view and purchase products. When a user visits the store, the user might not know where a desired product (“target product”) is located. Computer technology may help direct the user to the target product in real-time. In some embodiments, a model of passable areas and the location of products in the retail store may be determined, e.g. by a merchant device. In some embodiments, when the user visits the retail store, a computer generates a product recommendation, e.g. based on user-specific information, and a route in the retail store is determined for the user. In some embodiments, the route in the retail store may be determined using the model based on the target product, the user's location in the store, and one or more recommended products.

Abstract: A user may request a recommendation for an item from other users. Other users may respond to the request by recommending for or against items. Users may up-vote or down-vote the recommendations or responses of other users. The recommendations of the other users may be used to identify items and provide one or more recommendations to the requesting user. The original question and the responses may form a conversation thread. The recommendations may be inserted into the thread as responses, may be presented alongside the thread, or may be presented at the end of the thread. The recommendations may be based on one or more attributes of the user. The weight of the recommendations provided by other users may vary.

Abstract: Methods and systems are provided herein for recommending a media asset based on a geographic location at which that media asset was frequently consumed. For example, the system may monitor a location, such as New York City or Times Square, to determine popular media assets watched there, such as “The Avengers,” and when another user visits New York City, the system may then notify the user that the movie, such as “The Avengers,” is associated with New York City. The system stores the geographic locations associated with the media asset in the database based on the consumption of the media asset so that other users may be notified which media assets are associated with each geographic location.

Abstract: The present disclosure relates to methods, systems, and apparatuses for identifying related records in a database. The method includes receiving, via a network interface, a related records query, the related records query identifying at least one record stored in the electronic database, determining, based on transaction data, at least one related record that is related to the identified at least one record, determining, by a processor, that the at least one related record is unavailable, in response to determining that the at least one related record is unavailable, determining at least one keyword associated with the at least one related record, selecting at least one of one or more substitute records based at least in part on comparing the at least one keyword with a set of keywords associated with one or more substitute records, and providing the selected one or more substitute records as a response to the related records query.

Abstract: This application relates to apparatus and methods for generating preference profiles that may be used to rank search results. In some examples, a computing device obtains browsing session data and determines items that were engaged, such as items that were viewed or clicked. The computing device obtains item property data, such as product descriptions, for the items, and applies a dependency parser to the item property data to identify portions that include certain words, such as nouns or adjectives, which are then identified as attributes. The computing device generates attribute data identifying portions of the item property data as item attributes. In some examples, the computing device applies one or more machine learning algorithms to the session data and/or search query to identify item attributes. The computing device may generate a profile that includes the item attributes, and may rank search results based on the attribute data, among other uses.

Abstract: Embodiments described herein provide an attentive network framework that models dynamic attributes with item and feature interactions. Specifically, the attentive network framework first encodes basket item sequences and dynamic attribute sequences with time-aware padding and time/month encoding to capture the seasonal patterns (e.g. in app recommendation, outdoor activities apps are more suitable for summer time while indoor activity apps are better for winter). Then the attentive network framework applies time-level attention modules on basket items' sequences and dynamic user attributes' sequences to capture basket items to basket items and attributes to attributes temporal sequential patterns. After that, an intra-basket attentive module is used on items in each basket to capture the correlation information among items.

Abstract: A computer identifies, based on sensor data from one or more sensors located in proximity to a fire site and on a corpus of firefighting knowledge, one or more firefighting goals. The computer generates, based on the one or more firefighting goals and the corpus of firefighting knowledge, one or more firefighting recommendations. The computer scores, using the corpus of firefighting knowledge, the one or more firefighting recommendations based on historical effectiveness of prior firefighting actions.

Abstract: A hydrogen generator electrically coupled to a cloud monitoring system comprises a hydrogen generating device, a monitoring device, a network device, and a controlling device. The monitoring device monitors the machine condition of the hydrogen generating device and generates a condition signal. The network device selectively transmits a machine information including the condition signal to the cloud monitoring system. The controlling device receives an operating parameter from the cloud monitoring system via the network device and controls the hydrogen generating device according to the operating parameter. The hydrogen generator monitoring system of the present invention collects the relevant data of the user using the hydrogen generator and tracks the health status of the user to perform big data analysis.

Abstract: Facial skin analysis methods and systems for improving facial skin conditions using vehicle cameras of vehicles having onboard communication modules. Each vehicle is equipped to analyze the facial skin images over time periods and compare the images to determine skin conditions. Based on the facial skin conditions, a treatment recommendation can be transmitted to a seat occupant. Each vehicle is operatively connected to a facial skin analysis application in a data center. The facial skin analysis application includes a registration module which registers each vehicle. Additionally, a vehicle user may register with the facial skin analysis application to have his/her facial skin analyzed when travelling in any of the plurality of vehicles. The facial skin analysis application is operatively connected to a skin data AI analytics module and data lake and searches a plurality of databases for information related to the facial skin conditions to improve the treatment recommendation.

Abstract: According to some aspects, disclosed methods and systems may include determining, by a device and based on historical data associated with a first user, a first user profile comprising one or more content recommendation periods each associated with a time period and a content classification, and in response to detecting a user interaction, selecting a first content recommendation period of the one or more content recommendation periods. The methods and system may also include determining one or more content candidates corresponding to the content classification from a plurality of content assets based on an amount of remaining time in the time period associated with the first content recommendation period and a correlation between the historical data associated with the first user and one or more contextual features associated with the plurality of content assets, and transmitting, to a client device, an indication of the one or more content candidates.

Abstract: Methods, systems, and computer program product for automatically performing sentiment analysis on texts, such as telephone call transcripts and electronic written communications. Disclosed techniques include, inter alia, lexicon training, handling of negations and shifters, pruning of lexicons, confidence calculation for token orientation, supervised customization, lexicon mixing, and adaptive segmentation.

Abstract: A computing system comprises a database of garments in a retailers inventory, a database of users, a database of garments not in inventory, and a database of mappings, wherein a mapping maps one or more users of the database of users to one or more garments of the database of garments and wherein each mapping includes a weight for its corresponding user-garment pair.

Abstract: A computer-implemented method for improving efficiency in an electronic procurement system for sourcing resources, comprising, during digital electronic interactions of a buyer computer with one or more software platforms and without receiving explicit request for recommendations from the buyer computer: automatically generating, at a coding computer, implicit observation data of the buyer computer; automatically determining, at the coding computer, one or more active sourcing events from a plurality of sourcing events, based on at least the implicit observation data of the buyer computer; using the coding computer, causing to display at least one of the one or more active sourcing events in a graphical user interface.

Abstract: Using a natural language analysis, it is determined that a compendium requires a natural language response to a natural language query, the compendium comprising a set of stored natural language responses to natural language queries. A relevance of a portion of narrative text to the natural language query is scored according to a query relevance measure, the portion extracted from a corpus of narrative text. The compendium is enhanced according to the query relevance score with information in the portion.

Abstract: Techniques for performing outputting additional content associated with but nonresponsive to an input command are described. A system receives input data from a device. The system determines an intent representing the input data and receives first output data responsive to the input data. The system determines, based on context data, that additional content associated with the first output data but nonresponsive to the input data should be output. The system receives second output data associated with but nonresponsive to the input data thereafter. The system then presents first content corresponding to the first output data and second content corresponding to the second output data.

Abstract: Systems and methods for that allow for the creation and management of a centralized gift registry are described. Gifts are added to the centralized gift registry from retailer-specific registries. A gift registrant may select one or more retailers. The centralized gift registry system may automatically submit a request for the creation of retailer-specific registries at each of the retailers selected by the gift registrant, based in part on information provided to the centralized gift registry by the gift registrant. This creation may involve the use of APIs at the centralized gift registry or the retailer-specific registries. A gift list is created and displayed. Gift givers may select a gift from the centralized gift registry.

Abstract: A vehicle recommendation device and a method for machine learning based recommendation of vehicle is provided. The vehicle recommendation device receives vehicle log data from a plurality of sensors associated with each of a first set of vehicles. The first set of vehicles are classified based on a set of vehicle types. The vehicle recommendation device generates vehicle trip data, associated with a plurality of trips of each of the first set of vehicles, based on the received vehicle log data. The vehicle recommendation device further determines a set of features, associated with the plurality of trips or with information about the first set of vehicles, based on the generated vehicle trip data. The vehicle recommendation device further generates a machine learning model which is trained based on the determined set of features to output a first type of vehicle from the set of vehicle types.

Abstract: A computer-implemented method optimizing genetic algorithms for finding solutions to a provided problem is described. The method implements a multi-arm bandit algorithm to determine performance scores for candidate individuals from a candidate pool in dependence on successes and failures of the one or more candidates. The method evolves the candidate individuals in the candidate pool by performing evolution steps including: determining a fitness score for each of the candidate individuals in the candidate pool in dependence on the performance scores for the candidate individuals, discarding candidate individuals from the candidate pool in dependence upon their assigned performance measure, and adding, to the candidate pool, a new candidate individual procreated from candidate individuals remaining in the candidate pool after the discarding of the candidate individuals.

Abstract: A system for assessing text content of a product. The system includes a computing device having a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: provide text contents and confounding features of products; train a first regression model using the text content and the confounding features of the products; train the second regression model using the confounding features; operate the first regression model using the text contents and the confounding features to obtain a total loss; operate the second regression model using the confounding features of to obtain a partial loss; subtract the total loss from the partial loss to obtain a residual loss; use the residual loss to evaluate models and parameters for the regression models; and use the first regression model to obtain log odds of the words indicating importance of the words.

Abstract: Media content may be recommended based on feedback weightings. Input data describing the presentation of a media content items in association with content management accounts may be represented as data points. Each data point may identify feedback data for a media content item previously recommended for presentation in association with a content management account. The feedback data may identify a viewer reaction to the recommended media content item. A weighting factor based on the feedback data for the media content item presented in association with the content management account may be applied to produce a recommendation.

Abstract: A procedure and an installation for the control of home appliances that uses only the data that is necessary, avoiding saturation of the memories of the elements involved and/or the communications bandwidth. The procedure is simple and reliable so that it does not require the intervention of an expert user or a service person. The procedure includes the standardization of the data identifiers of each home appliance by identifying the identifier that contains a value for each data point and checking that the scale of each data point is equivalent to a predetermined scale. The installation includes a standardization system for such purpose.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for content recommendation using neural networks. In One aspect, a method includes: receiving context information for an action recommendation from multiple possible actions; processing the context information using a neural network that includes Bayesian neural network layers to generate, for each of the actions, one or more parameters of a distribution over possible action scores for the action, where each parameter for each Bayesian layer is associated with data representing a probability distribution over multiple possible current values for the parameter; for each parameter of each Bayesian neural network layer, selecting the current value for the parameter using data representing probability distribution over possible current values for the parameter; and selecting an action from multiple possible actions using the parameters of the distributions over the possible action scores for the action.

Abstract: Embodiments include methods and systems to remotely and electronically enhance measurement accuracy and speed of electronic brassiere fitting data. A method according to an embodiment can include receiving a set of current user brassiere data from a remote user computing device, receiving a set of physiological images from the remote user computing device, and receiving brassiere fitting data from one or more data sources. The method can further include filtering the brassiere fitting data responsive to the set of current user brassiere data, and generating a first brassiere size responsive to filtering the brassiere fitting data. The method can further include modifying the first brassiere size responsive to the set of physiological images, and generating a recommended brassiere size responsive to modifying the first brassiere size.

Abstract: Methods and devices for determining a load vector on an object are disclosed herein. An example method includes collecting location observations related to the object. The example method further includes filtering the location observations to determine an estimated model path. The example method further includes outputting a set of data from the estimated model path, wherein the set of data includes a model location, a model velocity, a model acceleration, and a model jerk. The example method further includes calculating a load vector from the set of data, scaling the load vector via a scaling index, and transmitting the scaled load vector to a remote device.

Abstract: A vehicle includes a system for recording and analyzing user preferences during a vehicle test drive. The system includes a processor and a memory that stores processor-readable instructions. When executed by the processor, the processor-readable instructions cause the system to: determine a user identity; create a user preference profile based on the user identity; communicate a prerecorded message describing one or more vehicle options to the user; record a user response of the user in response to the prerecorded message; analyze the recorded user response; and update the user preference profile based on the analysis of the recorded user response.

Abstract: An intelligent store system and an intelligent store method are provided. The method includes: sensing, by a proximity sensor, whether there is a first customer approaching the proximity sensor; sensing, by an image sensor, a movement trajectory of the first customer; and determining whether the first customer is entering or leaving a store in response to the first customer approaching the proximity sensor sensed by the proximity sensor. If the first customer is entering the store, a first virtual identity and a first virtual shopping cart corresponding to the first virtual identity are generated for the first customer, and a first product list of the first virtual shopping cart is updated according to the movement trajectory. If the first customer is leaving the store, a first operation of the first customer is received by a human machine interface, and the first product list according to the first operation is updated.

Abstract: A computer-implemented method of digital information presentation may include receiving a selection of an item reference from among digital data via a digital user interface. The method may further include receiving a request to search for information relating to the item reference. The method may include sending a request to search for the information relating to the item reference in the digital database. The method may also include receiving the information relating to the item reference. The method may further include presenting the information relating to the item reference via the digital user interface, the digital user interface including a purchase information element. The method may include facilitating a purchase of the item via the digital user interface.

Abstract: Top attributes of a product are identified from text content of an electronic document and are presented as visual depictions of the attributes. The attributes are identified and ranked based on the text content, such as whether the text content describes the attribute in a positive or negative manner. Top attributes are selected from the ranking and a visual depiction of the top attributes is identified. The visual depiction can be a universally recognized symbol or a custom image designated to an attribute. The visual depiction is superimposed on the text content associated with the attributes when the electronic document is presented at a display. In this way, top attributes for a product can be presented in a manner that condenses the relevant information provided by the electronic document into a format better suited for providing the information on small screens of mobile devices.

Abstract: A food product recommendation system may include a camera configured to obtain an image of a food product area having available food products and a remote device associated with a given user. The system may also include a recommendation server configured to cooperate with the remote device to obtain a desired food product characteristic from the given user and determine recommended food products from the available food products based upon the desired food product characteristic. The recommendation server may also be configured to associate a corresponding food product identifier to each recommended food product and communicate the recommended food products to the remote device. The remote device may display the image of the food product area with the recommended food products augmented with the corresponding food product identifiers and obtain user selection for purchase of at least one of the recommended food products based upon the corresponding food product identifier.

Abstract: A skin care computing device that includes a user interface, a camera, a speaker, a communication interface, and a personal care assistant application. The personal care assistant application can identify personal care products being used by a user and product use event data describing the use of a personal care product by the user, such as the date and time of the use, the duration and frequency of the use, and the manner in which the personal care product is being used. Then the personal care assistant application generates user feedback information for the personal care product based on the product use event data, previous instances of product use event data, and/or user profile data for the user.

Abstract: A method, computer program product, and computing system for associating one or more fashion products on a website with a user accessing the website. One or more recommendations may be provided to the user for fashion products based upon, at least in part, one or more fashion-ability scores representative of the one or more fashion products associated with the user on the website and one or more fashion-ability scores representative of the one or more fashion products on the website.

Abstract: A product selecting unit extracts a candidate for recommended product on the basis of browsing information in a browsing information storing unit and unpurchased product information in an unpurchased product information storing unit. Product specifications that are information specific to each product are stored in a product information storing unit. A specification correlation calculating unit extracts a product having a product specification correlated with a product specification of the candidate for recommended product on the basis of the product specifications, and extracts the product as a recommended product.

Abstract: Computer-implemented methods of providing personalized recommendations to a user of items available in an online system, and related systems. First-level features including context features are computed based upon context data. A first-level machine learning model is then evaluated using the first-level features to generate predictions of user behavior in relation to a plurality of individual items available via the online system. A list of proposed item recommendations is constructed based upon the predictions. Second-level features are computed based upon the context data and list features based upon the list of proposed item recommendations and the corresponding predictions generated by the first-level machine learning model. A second-level machine learning model is evaluated using the second-level features to generate a prediction of user behavior in relation to the list of proposed item recommendations.

Abstract: Examples described herein relate to a system consistent with the disclosure. For instance, the system may comprise a data lake including information relating to an in-store activity of a customer and an online activity of the customer, a processing resource, and a non-transitory machine-readable medium storing instructions executable by the processing resource to identify the in-store activity and the online activity of the customer, aggregate and store the in-store activity and the online activity of the customer in the data lake, reduce an amount of products in a product portfolio, compare purchases including in-store purchases and online purchases, and recommend a product of the plurality of products based on the comparison.

Abstract: A computer device determines requirements of a particular device/service by analyzing designated electronic communications. The computer device then monitors performance of the device/service over a period of time to determine performance of the device/service in meeting those derived requirements. An output regarding the performance of the device/service in meeting those requirements is then generated.

Abstract: Embodiments of the invention make consumer application adoption more efficient by giving suppliers access to the desired target audience by displaying the applications to the right audience. Suppliers can provide criteria for the kinds of users they are looking to target using constraints. Embodiments of the invention enable viewers that match the constraints to see the service. The user gets to see an automatically generated application set, that is instantly available, with a high probability of containing the application the user is likely to seek. Identity and Payment support are built into the platform, such that the user no longer needs to register with each application or set up payment with each application. In addition, the platform reduces bandwidth consumption, storage front print, and power consumption of the user device by choosing when and which modules to download to the user device.

Abstract: The system and methods described herein provide for managing user datasets by facilitating interactions between users and their advisors following location-based notification of certain triggering events in the user dataset. The geolocation of the user is used to identify nearby advisors who can provide consultation as required by the user. Some embodiments facilitate introductions to a potential user of a set of advisors matched to the user's profile and in response to certain triggering events in the user's dataset.

Abstract: Systems, devices, and methods are described herein for distributing syndicated content or content with one or more distribution restrictions. In one aspect, a method may include assigning a unique ID to a plurality of content items, where the unique ID of at least one of the content items is associated with one or more property distribution restrictions. The method may further include streaming in a video stream the content items to at least two properties and monitoring the unique IDs of the plurality of content items streamed in the video stream to detect least one content item associated with the one or more property distribution restrictions. The distribution of the least one content item associated with the one or more property distribution restrictions may be blocked from the one or more properties concurrently with streaming the video stream, based on the one or more property distribution restrictions.

Abstract: Aspects of the disclosure relate to use of supervised, unsupervised, semi-supervised, or reinforcement-based machine learning algorithm(s) to perform pattern recognition and/or cluster detection on historical transactional data in order to predict events that may occur in the future and are candidates for automated delivery of items from a source to a customer in a contactless manner, via a secure delivery device, to minimize health risk(s) to the customer. The items may be securely delivered in an automated manner such as, for example, by use of a drone or autonomous vehicle, which may have advanced sensors to facilitate various aspects of the delivery. The items may be contained in a secure carrier coupled to the delivery device and may be unlocked locally or remotely using mechanical or digital means. Novel logical systems, architectures, machines, platforms, delivery devices and components thereof, and methods are disclosed.

Abstract: A method for implementing a recommendation system using an asymmetrically hierarchical network includes, for a user and an item corresponding to a user-item pair, aggregating, using asymmetrically designed sentence aggregators, respective ones of a set of item sentence embeddings and a set of user sentence embeddings to generate a set of item review embeddings based on first item attention weights and a set of user review embeddings based on first user attention weights, respectively, aggregating, using asymmetrically designed review aggregators, respective ones of the set of item review embeddings and the set of user review embeddings to generate an item embedding based on a second item attention weights and a user embedding based on second user attention weights, respectively, and predicting a rating of the user-item pair based on the item embedding and the user embedding.