A data processing system receives location data points from computing devices. The system annotates the location data points with entities and determines a duration each of the computing devices was at corresponding entities. The system aggregates the location data points into a set of sequences based on the duration and the entities and stores the set of sequences in a data record. The system accesses the database record including a set of sequences generated from location data points received from computing devices. The system receives, from a computing device, a request for a location sequence that includes a query. The system identifies an attribute of the computing device. The system identifies a sequence based on the set of sequences using the query and the attribute. The system transmits the sequence for display on a display device.

A product catalog service allows merchants to create and store product catalogs indicating products that are available from the merchants. Transaction data from point-of-sale (POS) devices of a plurality of merchants can be received. A first catalog of a first merchant can be obtained from a first POS device of a first merchant. The first catalog contains items to be sold by the first merchant. Using the transaction data and the catalog, a second catalog of items to be sold by a second merchant can be generated or updated and transmitted to the second merchant. Items can be compared using item attributes. Item descriptions in the second catalog can be based on item descriptions in the first catalog.

The present disclosure relates to method and system for assessing quality of commodities. An image of bulk commodity is captured and segmented into one or more segmented images for classification into one of predefined categories of commodities. The method and system classify the commodities based on generalized features created from training images. One or more features in the training images are determined and grouped to obtain the generalized features. A feature score and corresponding weightage score of the generalized feature is then determined to estimate a predetermined regression score. Based on the generalized features and predetermined regression score, a likelihood score of the segmented image is determined that enables the classification of the input image to one of the predefined categories of commodities. Thus, the present disclosure enables quality assessment of commodity by categorizing each commodity of input image into corresponding category with improved accuracy and reduced classification error.

Techniques are provided for identifying objects (such as products within a physical store) within a captured video scene and indicating which of object in the captured scene matches a desired object requested by a user. The matching object is then displayed in an accentuated manner to the user in real-time (via augmented reality). Object identification is carried out via a multimodal methodology. Objects within the captured video scene are identified using a neural network trained to identify different types of objects. The identified objects can then be compared against a database of pre-stored images of the desired product to determine if a close match is found. Additionally, text on the identified objects is analyzed and compared to the text of the desired object. Based on either or both identification methods, the desired object is indicated to the user on their display, via an augmented reality graphic.

Some aspects of the present disclosure are directed to computerized methods for extracting attributes from product titles. The method may include: retrieving a title associated with a product listing and historical product title data; refining the title; determining at least one tag associated with an attribute; generating, based on the at least one extracted tag and the historical title data, a first combination of one or more attributes; determining whether the title includes at least one plurality of product options, and if so: determining, for each product option hi the plurality of product options, a second combination of one or more attributes by removing attributes associated with alternative product options from the first combination; and generating a product identifier based on the second combination; and if the title does not include at least one plurality of product options, generating, the product identifier based on the first combination.

Disclosed herein are embodiments for automated intelligent price guidance of listings for a for sale object (FSO) being offered by a seller. Some embodiments may operate by: receiving information relating to the FSO, including specifications for selling the FSO, wherein the specifications include an original offer price and a time window for selling the FSO; determining a category of the FSO; generating an optimal offer price for the FSO based on one or more of: (a) past listings of previously sold FSOs that have a same or similar category of the FSO; (b) the specifications, including the time window; (c) a category decay curve applicable to the category; and (d) seller flexibility curve of the seller; and through the use of a machine learning neural networking analysis suggesting the optimal offer price to the seller as an offer price for a listing corresponding to the FSO, wherein this price is evaluated over time and suggestions are made accordingly.

In some embodiments, apparatuses and methods are provided herein useful to searching retail products for purchase and locations of physical retail stores. In some embodiments, there is provided a system for searching both retail products for purchase and locations of physical retail stores including a user interface; a memory device; one or more databases; a universal search bar cooperatively operating with the user interface to provide a single search tool for a customer to search the one or more databases storing at least retail product inventories and a plurality of retail locations; and a control circuit configured to: receive a communication signal; autonomously determine a first term associated with the customer; and initiate entry of the first term in the universal search bar to automatically suggest a search term, thereby prompting customer engagement on the user interface.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform receiving a title of an item associated with an online catalog; interpreting, using a natural language model, one or more attributes of the predetermined set of attributes; determining a first title quality score for the title based on a first rule; determining a second title quality score for the title based on a second rule; determining an aggregated title quality score for the title based on at least the first title quality score and the second title quality score; generating a content quality list for the title; and sending instructions to display, on a user interface of an electronic device, a content quality dashboard comprising the content quality list for the title of the item. Other embodiments are disclosed.

Disclosed are various embodiments for generating customized user interfaces including offers for items available by multiple merchants in an electronic marketplace. A search of an item database is performed in response to receiving a search query. If an item is available from multiple merchants in an electronic marketplace, a user interface element including selectable components for a subset of the merchants is inserted in proximity to a presentation of the item in a user interface. Interactions with the user interface element can be used to predict a preferred merchant of the user.

An example method for estimating vehicle repair costs includes receiving, via one or more sensors coupled to a damaged vehicle involved in a crash, crash information of the damaged vehicle, the crash information including vehicle operating information of the damaged vehicle; analyzing the crash information with respective collision data of a vehicle type that includes or is similar to the vehicle type of the damaged vehicle, the analyzing including comparing at least one of a velocity or an acceleration included in the vehicle operating information to vehicle operating characteristics indicated by the respective collision data of the vehicle type; determining one or more damaged vehicle parts of the damaged vehicle based on the analyzed crash information; determining a cost estimate to repair the damaged vehicle based on the one or more damaged vehicle parts; and transmitting an indication of the cost estimate.