Abstract: A method of generating a user-interface to be displayed at a remote location may include receiving a search request for an item listing and retrieving a first listing and a second listing based on the search request, determining a similarity score between the first and second listings that is based on multiple properties common to the first and second listings, and generating instructions to be transmitted to a remote location to generate a user interface to be displayed at the remote location, the user interface including the first listing, the instructions excluding the second listing from a list of results displayed on the user interface based on the similarity score exceeding a threshold and the first listing including superior values in at least one of the plurality of properties common to the first and second listings. The method may also include transmitting the instructions to the remote location for display.

Abstract: A method and a system for recommending a target garment matching an inputted garment. The method includes: extracting attributes from text description and image of the inputted garment to obtain extracted attributes; querying a knowledge graph using the extracted attributes to obtain matched attributes; retrieving candidate products from a garment pool using the matched attributes; extracting features from the inputted garment and the candidate products; determining the target garment from the candidate products based on grading scores between the features of the inputted garment and the features of the candidate products; and recommending the target garment. The knowledge graph includes nodes corresponding to type of clothes, category of clothes, attribute keys, values of attribute keys, context keys, values of context keys, combination of the values of the attribute keys and the type of clothes, and combination of the value of the attribute keys and the category of clothes.

Abstract: Features for adaptation and control of a graphical user interface (GUI) and GUI functionality are disclosed herein. In an example, a user interface control is provided in a GUI to receive interaction from a user, which is provided in an enabled state to offer functionality for the user to attempt an initial commerce action with a constrained item. The user interface control is changed from the enabled state to a disabled state, in response to receipt of the interaction from the user, and a delay time period is calculated for the disabled state (with the delay time period being uniquely calculated for the user). The user interface control is changed from the disabled state to the enabled state, upon expiration of the delay time period, and the enabled state of the user interface control provides functionality for the user to perform a commerce action with the constrained item.

Abstract: A method of accumulating a personalized list of products viewed by a user on different website domains includes providing a first embedded code on a first website domain and a second embedded code on a second website domain in which the first website domain is different from said second website domain. Each of the embedded codes allows a specified third party server to communicate interactively with the user. The method further includes automatically accumulating a personalized list of products viewed by the user in a database on the specified third party server, wherein the personalized list includes at least a first product and a second product, wherein the first product is on the first website domain and the second product is on the second website domain.

Abstract: Systems, methods, and computer-readable storage media of protecting customer information. One method includes detecting a user device associated with a user has navigated to a page of an online store, inserting code comprising a first interactive element associated with a purchase option into the page prior to presenting the page on the user device, and receiving a pending purchase order. The method further includes transmitting a notification to a merchant system associated with the online store to reserve a good or service for a period of time, capturing, via an input circuit of the user device, user input of the user, and assigning a point value to the user input. The method further includes generating a recommendation to cancel, proceed, or modify the pending purchase order based on an evaluation of the point value, and providing, to the user device, the recommendation during the pendency of the period of time.

Abstract: A method includes determining a first taxonomy of an anchor product. The first taxonomy includes a plurality of levels for classifying products organized from a highest taxonomy level to a lowest taxonomy level. The method further includes determining a second taxonomy closest to the first taxonomy. The second taxonomy is associated with a group of products, the first taxonomy and the second taxonomy have at least a common highest taxonomy level, and the determination is made at least in part based on co-purchase data indicating that the anchor product and at least one product in the group of products are purchased together more often than products associated with other taxonomies are purchased with the anchor product. The method further includes determining a most similar product to the anchor product from the group of products of the second taxonomy and associating the anchor product and the most similar product with one another in a product collection.

Abstract: Methods for determining which image of a set of images to present in a search results page for a product are described. Components of a server system may receive a set of images for a set of items associated with a product. Components of the server system may perform image ranking to rank the set of images to identify a representative image of the set of images for the product, based on a user interaction metric of each image of the set of images. The components of the server system may then receive, from a user device, a search query that may be mapped to the product, and the component of the server system may transmit, to the user device, the search results page that includes at least one item of the set of items and the representative image based on the interaction metric of the representative image.

Abstract: Multiple users of a household can each have a different profile associated with a common account for an online concierge system. This association of different profiles with the common accounts allows the concierge system to show a user of the household what other users of the household purchased and rank items for suggestion to the user based one purchases of other users, facilitating order building. The online concierge system also enables a user profile to designate a user profile associated with the common account for an order pickup or as a contact for a home delivery. Additionally, association of different user profiles with the common account may be used for account recovery of one of the user profiles. Further, different user profiles may have different permissions for creating an order with the online concierge system.

Abstract: A method for database reconciliation, comprising: receiving, from one or more sources, attribute data of a plurality of attribute data types representing aspects of a product; generating a plurality of attribute categories based on the received attribute data types, each attribute category corresponding to one of the received attribute data types and containing all attribute data of the one of the received attribute data type; determining data scores for each of the attribute data contained in each of the plurality of attribute categories; generating reconciled data for each of the attribute categories, the reconciled data being the attribute data in each of the attribute categories having the highest data score; storing in a database, the plurality of attribute categories each containing reconciled data corresponding to the product; and providing, from the database, the reconciled data for display on a display interface.

Abstract: Methods and systems for predicting relevant items to be presented to a user in an online environment are described. The methods and systems described herein generate models based on previous item selections to determine an overall time series model for predicting a relevant time of next item selection as well as items most likely to be selected at that time. Complementary items can be presented to the user alongside the selection of most relevant items.

Abstract: An assistive shopping cart system for guiding a user and monitoring the user's physical and cognitive conditions in a shopping environment is described. The assistive shopping cart system provides assistance and guidance to a user based on a user profile. The assistive shopping cart system routes the user through the shopping environment using a shopping route generated based on the user profile. The assistive shopping cart system also detects and tracks user physical and cognitive conditions and user actions in the shopping environment. The user actions are used to aid in the completion of a purchase/transaction and generate shopping notifications for the user and others to understand the process of the shopping experience.

Abstract: A search engine provides diverse search results in response to a search query using a trained diversity ranker. The diverse results may be generated by determining ranking positions of at least some search results based on delta feature values that are dependent on higher-ranked results. Delta feature values indicate a degree or magnitude of difference between a particular result and other results with respect to a particular feature, such as price, category, or shipping type. In providing the ranked results for presentation to a user at a computing device, a diversity feature indicator for at least some results may be generated. The diversity feature is a feature that distinguishes a given result from other results. As such, the diversity feature indicator represents that diversity feature for the particular result being different from other results and distinguishes the diversity feature from other features in the particular result.

Abstract: A system for size and fitting recommendation for fashion products is provided. The system includes a memory having computer readable instructions stored therein. The system further includes a processor configured to access purchase and content data of one or more fashion products purchased by a plurality of users. The processor is configured to generate an observable feature vector for each of the one or more fashion products. The observable feature vector is generated based upon observable features data corresponding to each of the one or more fashion product. The processor is further configured to aggregate the observable feature vectors of the fashion products purchased by each user to compute an observable user vector for the respective user. In addition, the processor is further configured to generate a latent feature vector for each of the one or more fashion products. The latent feature vector is generated based upon latent features data corresponding to each fashion product.

Abstract: Consumer safety of repaired vehicles can be improved by providing systems and methods for generating vehicle repair estimate reports based on predictive estimating and transmitting these reports to clients. A master server serviced by a vehicle manufacturer generates a vehicle repair estimate report based on predictive estimating and transmits this report to a client via a web-based graphical user interface. Also, a master server serviced by a vehicle manufacturer generates a vehicle repair estimate report based on predictive estimating and transmits this report to a client via a vehicle repair claims management user interface. The vehicle repair estimate report based on predictive estimating may comprise repair packages and repair information relating to recommended replacement parts and quantities thereof, the part numbers for the suggested replacement parts, the price estimate for the suggested replacement parts, manufacturer-recommended repair instructions, and other relevant information.

Abstract: Disclosed herein are system, method, and computer program product embodiments for the prediction of listing attributes for a for sale object (FSO). Data analyzed with respect to historical listings in a database is compared to attributes of the FSO using machine learning (ML) and artificial intelligence (AI), in order for the user to select a category related to the FSO, and for a listing generation module to generate a ultimately reduced set of listings related to the FSO, where the ultimately reduced set is used to predict a price for the FSO based on the selected category, and generate a listing for the FSO, wherein a listing for the FSO is monitored, and information from the monitoring is used as machine learning feedback to train and enhance predictions.

Abstract: A system includes a processor and an information wallet application stored on machine readable storage media coupled to the processor and including program logic that causes the processor to receive a shopping list from a first information wallet adapter stored on a user computing device, send the shopping list to a second information wallet adapter stored on a merchant computing device, receive merchant data from the second information wallet adapter, wherein the merchant data includes one of price data and quantity data for at least one item included in the shopping list, and send the merchant data to the first information wallet adapter. The system also includes a cloud storage computing system accessible by the information wallet storage application and configured to communicate with the first and second information wallet adapters in order to store and retrieve shopping list data associated with the shopping list.

Abstract: Because an electronic apparatus includes: an input means; and a display means for, when a first product registered in a first classification is newly registered in a second classification on the basis of an operational instruction via the input means from a user, displaying a first image in which information about the first product is included, and a second image in which information about the first product is added, and for, when a second product registered in the second classification is newly registered in a third classification, displaying the second image in which information about the second product is deleted, and a third image in which information about the second product is added, the electronic apparatus provides a purchase management function of properly displaying a state of each product and making it easy for the user to perform management in accordance with the classifications.

Abstract: In online apparel shopping, user finds difficulty in choosing apparel of his/her preferences. This disclosure relates to recommend an apparel specific to a user by estimated attribute values in digital environment. An information associated with the user and apparels is processed to obtain a first parameter and a second parameter and associated data independent matrix and data dependent matrix is derived. The data independent matrix and the data dependent matrix is learned to obtain trained multivariate multi structure model. A significant pattern associated with each user is determined by extracting plurality of images. The derived significant pattern is deployed on k-nearest neighbor model to obtain recommended pattern. The trained multivariate multi structure model and the recommended pattern is applied on state of the user in a real time to estimate the attribute values. The estimated attribute values is mapped with existing apparels in repository to recommend prioritized apparels.

Abstract: The method includes urging a customer a selection of a base robot that becomes a base of the robot by communicating electronic data, receiving the selection of the base robot, extracting variable specification items of the selected base robot based on information related to variable specifications among a given basic specification of the base robot from a variable specification database, determining a special order specification in which at least one of the variable specification items is changed from the basic specification, searching the information related to component parts of the base robot and parts attachable to the base robot for parts that constitute the robot so that the special order specification is realized, presenting to the customer a virtual object of the robot where the searched parts are mounted to the base robot, urging the customer an input of an order for the robot, and receiving the order for the robot and accepting the order for the robot.

Abstract: In one aspect, a computerized method for implementing a hair-service based digital image search engine and ranking comprising the step of providing a hair-service search engine, wherein the hair-service search engine receives a digitalized hair-style portfolio from a hair stylist. The hair-style portfolio comprises a set of hair-style digital images. The set of hair-style digital images comprises one or more views of a set of hair-stylist customers. The method receives a set of tags for each hair-style digital image of set of hair-style digital images. Each tag comprises a hair-style descriptor of the hair style depicted in the hair-style digital image. The method receives a hair stylist contact information. The method stores the digitalized hair-style portfolio, the set of tags and the hair stylist contact information in a digitalized hair-style portfolio database; receives a hair-style search from a user. The method parses the hair-style search ad generating a set of terms.