Systems and method for lifelong tag learning. The system includes a computing device having a processor and a storage device storing computer executable code. The computer executable code is configured to: provide product descriptions and seed tags characterizing products; train a named-entity recognition (NER) model using the product descriptions and the seed tags; predict pseudo tags from the product descriptions using the NER model; calculate confidence scores of the pseudo tags; compare the confidence scores with a threshold, and define the pseudo tags as true tags when the confidence scores are greater than the threshold; add the true tags to the seed tags to obtain updated tags; and repeat the steps of training, predicting, calculating, comparing and adding using the product descriptions and the updated tags, so as to keep updating the updated tags.

A method for assisting selection of an accommodation by an accommodation search system includes receiving user credentials from a user device; receiving trip parameters from the user device; determining a basic list of accommodations that correspond with the trip parameters; determining one or more factors that apply to each individual accommodation of the basic list of accommodations; applying a weight value to each of the one or more factors that apply to each individual accommodation of the basic list of accommodations; aggregating the weight values of the one or more factors that apply to each individual accommodation to determine an aggregate weighted score for each individual accommodation of the basic list of accommodations; sorting the basic list of accommodations into a sorted list of accommodations based on the aggregate weighted score for each individual accommodation; and providing the sorted list of accommodations to the user device for viewing by a user.

Systems and methods for generating, administering and analyzing a user experience study are provided. In particular, intents can be generated from a user experience study by applying one or more screener questions to participants and subjecting the screened participants to one or more tasks. Corresponding clickstreams and success data for each participant engaging in the tasks can be recorded. The success and clickstream data can also be aggregated for all the screened participants as aggregated results. Video data including audio for each of the screened participants can also be recorded.

A multimodal recommendation identification system analyzes data describing a sequence of past content item interactions to generate a recommendation for a content item for a user. An indication of the recommended content item is provided to a website hosting system or recommendation system so that the recommended content item is displayed or otherwise presented to the user. The multimodal recommendation identification system identifies a content item to recommend to the user by generating an encoding that encodes identifiers of the sequence of content items the user has interacted with and generating encodings that encode multimodal information for content items in the sequence of content items the user has interacted with. An aggregated information encoding for a user based on these encodings and a system analyzes the content item sequence encoding and interaction between the content item sequence encoding and the multiple modality encodings to generate the aggregated information encoding.

Embodiments are directed towards providing analytics and marketplace data to members of a user community. In some embodiments, the analytics and marketplace data are generated based on machine data provided by the members. The analytics and marketplace data may enable automatically identifying, configuring, monitoring, controlling, managing, and/or maintaining a machine or a collection/system of machine components. The analytics may include, but are not limited to analytics related to machine component reliability, machine maintenance conditions, machine prohibited conditions, machine usages, machine alert conditions, and the like. The marketplace data may include information relating to the maintenance of the machine, replacement components or alternative components for the machine, and the like for various machines. Marketplace data may include an aggregation of electronic (e)-commerce data. The marketplace data may be provided is based on data aggregated from various sources, including vendors, suppliers, buyers, sellers, online auctioneers, or other members of the user community.

An online agricultural system manages and optimizes interactions of entities within the system to enable the execution of transaction and the transportation of crop products. The online agricultural system accesses historic and environmental data describing factors that may impact crop product transactions and/or transportation to determine market prices for crop products and crop product transportation. Responsive to receiving a request from an entity, the online agricultural system determines an optimal transaction for the entity, such as a price for selling a crop product, an available crop product for purchase, or a transportation opportunity to transport a crop product.

Methods, systems, and media for presenting an advertisement are provided. In some embodiments, the method comprises: causing an advertisement to be presented in connection with presentation of a video having content associated with an application, wherein the advertisement includes information indicating one or more virtual items associated with the application available for purchase; receiving a user input indicating a purchase of at least one of the one or more virtual items; causing payment information to be collected based on a user account associated with a request for presentation of the video to complete the purchase; and transmitting information indicating the completed purchase to an entity associated with the application.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: for each respective record in a plurality of records, assigning the respective record: (1) to a first database cluster on a first database server; or (2) to a second database cluster on a second database server; receiving a search request from a requester; executing the search request in the first database cluster to retrieve a first set of results; when the first set of results is greater than a threshold number of results, presenting the first set of results to the requester; and when the first set of results is less than the minimum number of results: executing the search request in the second database cluster to create a second set of results; and presenting the second set of results to the requester, wherein: the threshold number of results is configured such that a probability that the first set of results is greater than the minimum number of results is at least fifty percent. Other embodiments are disclosed herein.

A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. The user's preview may be based upon a two-dimensional image of a wear pattern in a laser input file and, from a set of two-dimensional images of a base garment, create a three-dimensional view of the base garment with the wear pattern.

A method, an apparatus, and an electronic device for processing a data transaction are disclosed. The method includes receiving an application request from a client to perform a data operation in a target data partition; creating a corresponding data transaction according to the application request, and assigning a transaction identifier to the data transaction; returning the transaction identifier that is assigned to the data transaction to the client; performing the data operation based on the target data partition according to the data operation carrying the transaction identifier and sent by the client; and processing the data transaction according to a transaction instruction sent by the client. The method enables a data operation to implement transactional attributes, and to satisfy a transactional nature of the data operation. Moreover, the service logic of data transactions implemented by the method is relatively simple, thus ensuring that data services have a good transactional nature.