Abstract: Provided is a system for providing removals simulation using VR and AR and brokering real estate therethrough, and the system includes: a background providing unit which extracts background information inside a real estate object provided by a real estate provider and presents the background information to the real estate customer; and an AR providing unit which overlaps props information of a real estate customer on the background information of the real estate object so as to be arbitrarily arranged by the real estate customer, wherein the real estate customer can simulate by overlapping props information on the background information, when the simulation is determined, the determined information is transmitted to a number of moving service servers, and thus provides an advantage in that a number of moving centers can propose moving costs to the real estate customer in a reverse auction manner based on the props information.

Abstract: Systems and methods are provided and include a server configured to receive a copy of paint product catalog information associated with a coating manufacturer, store a paint product ordering application, receive a measured color of a flooring product from a dealer computer terminal located at a flooring store, determine paint colors that coordinate with the flooring product based on a measured color of the flooring product and the copy of the paint product catalog information, communicate the paint colors to the dealer computer terminal, run the paint product ordering application, receive an order for a paint product from the dealer computer terminal, and communicate the order for the paint product to a computer system located at a coating manufacturer facility, the computer system being configured to receive transmission of the order for the paint product from the server for order fulfillment at the coating manufacturer facility.

Abstract: A cloud-based cyber shopping mall system is provided. The cloud-based cyber shopping mall system includes a cloud-based server module, a scene movement module, a product introduction module, a customer service module, a shopping cart module, a style change module, and an exhibition area switching module. The cloud-based server module includes a cloud-based database and a cloud-based shopping mall webpage. Through the scene movement module, the product introduction module, the customer service module, and the shopping cart module, a user can click on related options adjacent to any product viewed on the cloud-based shopping mall webpage to view an introduction of the product, contact the customer service, and place an order. Through the style change module, the user can change a style of a three-dimensional product model on the cloud-based shopping mall webpage.

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: 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: 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 acts of: generating a feature vector for a user based, at least in part, on historical data pertaining to the user's previous transactions; generating, using a quantity prediction model of a machine learning architecture, a respective item quantity prediction for each of one or more items included in a predicted basket based, at least in part, on the feature vector for the user; and populating a respective quantity selection option for each of the one or more items included in the predicted basket based on the respective item quantity prediction generated for each of the one or more items. Other embodiments are disclosed herein.

Abstract: This disclosure describes systems and methods for matching user provided images that include representations of items with sellers of those items. A management service, as described herein, may provide a web site where users can post images, view images, share images, correspond with other users, etc. The management service may identify items represented in the images and determine one or more sellers that offer those items for sale. When another user requests to view the user provided image, the image, seller information identifying the seller determined to sell the item represented in the image, and/or a purchase control that may be selected by a user to initiate a purchase with the seller is presented.

Abstract: Techniques are described for enhancing a user's experience with a retail software application. In one technique, a first trigger event within a first widget of a first page of an application is detected. The first widget indicates a set of items associated with a user interacting with the application. A non-modal window is presented on the first page of the application in response to the detection of the first trigger event. The non-modal window includes information associated with items indicated by the first widget. A second trigger event associated with one of the items within the non-modal window is detected on the first page of the application. A selection state of the item is determined and stored in response to the second trigger event. The non-modal window is collapsed in response to detection of a third trigger event outside of the non-modal window.

Abstract: Methods and software facilitate supplier willingness awareness in a marketplace of suppliers of structures represented and/or specified in a design. In some embodiments, methods and software of the present disclosure allow each of any one or more designers participating in an automated marketplace to view a list of suppliers that are willing to fabricate a particular design and/or prices associated with fabricating such a design such that the designers can quickly and easily identify suppliers that are not only capable of fabricating particular designs but also willing to do so. Such a list may be generated by comparing a list of objective requirements for a design, which may be generated from fabrication data associated with a designer's request for price or computer aided design file, to willingness data associated with one or more suppliers.

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: Sharing a digital ad between two or more users over a network. In one embodiment, a method may include presenting a digital ad to a first user on a first network device. The method may also include receiving from the first user a request to share the digital ad with a second user on a second network device. The method may further include sending the second user an invitation to view the digital ad and, in response to an acceptance of the invitation, presenting the digital ad to the second user on the second network device.

Abstract: Methods for product ordering relating to an automation system are described. Exemplary methods may include receiving one or more inputs, identifying one or more product order-related parameters, receiving information related to a product order, determining delivery data based at least in part on the information, and initiating an automation system operation based at least in part on the delivery data.

Abstract: A computing system includes one or more processors and one or more computer-readable storage media having instructions stored thereon that, when executed by the one or more processors, causes the one or more processors to receive a pending purchase order from a user device in response to a selection of an interactive element presented on a payment page of an online store via the user device, the pending purchase order corresponding to a purchase of a good or service from the online store and including payment information, store the payment information in an escrow database for a window of time, generate a notification corresponding to the pending purchase order, the notification including information corresponding to the good or service and excluding the payment information, and transmit the notification to a merchant system associated with the online store to reserve the good or service during pendency of the window of time.

Abstract: A system and method for predicting sellability of a fashion product is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access one or more catalogue images of a fashion product. The processor is configured to determine a plurality of visual attributes of the fashion product. The processor is further configured to determine a plurality of non-visual attributes corresponding to the fashion product. In addition, the processor is configured to estimate a first sellability confidence value for the reference fashion style using a deep learning model. The first sellability confidence value is estimated based upon the visual attributes. Further, the processor is configured to estimate a second sellability confidence value for the reference fashion style using a non-visual parameter model. The second sellability confidence value is estimated based upon the non-visual attributes.

Abstract: In implementations of systems for generating recommendations, a computing device implements a recommendation system to receive prior interaction data describing prior interactions of entities with items. The recommendation system processes the prior interaction data and segments the entities into a first set and a second set. The entities included in the first set have greater numbers of prior interactions with the items than the entities included in the second set. The recommendation system then generates subset data describing a subset of the entities in the first set. This subset excludes entities having numbers of the prior interactions with the items below a threshold. The recommendation system forms a recommendation model based on the subset data and the system uses the recommendation model to generate a recommendation for display in a user interface.

Abstract: A method and system for identifying and labeling fraudulent store return activities includes receiving, by a server, retailer events from an online transaction system of a retailer, the retailer events comprising records of transactions between customers and the retailer, including sale, exchange and return activities across multiple stores. The retailer events are processed to build a network that associates stores, transactions, payment instruments, and customer identification over related activity sequences of transactions.

Abstract: A system generates a first gift selection matrix that includes a first set of items of interest to a recipient organized in columns of increasing cost and rows of decreasing interest to the recipient. The system transmits the first gift selection matrix to a first user computing device and to a second user computing device. Item selections are received from users, along with gift purchase contribution pledges. If the pledges are insufficient to cover a cost of one of the selected items, the system sends a request to the first user and the second user for either an a second gift selection, or a pledge of additional funds. If the new gift selections are not the same, or if the pledged amounts are insufficient to purchase a selected gift, the system generates a second gift selection matrix. The system transmits the second gift selection matrix to the first user computing device and the second user computing device. A final gift selection can be made from the second matrix.

Abstract: Embodiments provide a recommendation for an additional item in response to receiving a basket of goods determine a type for the basket of goods from a set of basket types, receive a set of additional targeted items as target recommendations and receive a history of received types of baskets of goods. Embodiments iteratively perform a clustering into a plurality of clusters of each of the basket types based on the history of received types of baskets of goods, and preference updating for each of the targeted items into each of the plurality of clusters. The iteratively performing, after a plurality of iterations, outputs a sequence of mappings and a sequence of preference parameters. Embodiments generate a frequency of tabulation of mappings from the sequence of mappings and then generate the recommendation based on the sequence of mappings, the sequence of preference parameters and the frequency of tabulation of mappings.

Abstract: Systems, methods, and media for translating requests to acquire or change goods and services by receiving a request in a service catalog. The received request is received in a format that is not suitable for a target vendor. The received request is then translated into a format suitable for the target vendor. The translated received request is then transmitted to the vendor using the translated format.

Abstract: A vehicle is detected at a drive thru terminal and an automated voice-based dialogue is established with a user in the vehicle and the terminal. An order is placed for a transaction using natural-language speech. The automated voice-based dialogue identifies commands, nouns associated with menu items, adjectives associated with modifying the menu items, prepositions associated with modifying the menu items, and exclamations associated with confirming the order and associated menu items. The automated speech is identified and processed based on a specific lexicon associated with a specific type of restaurant. The speech is translated into actions processed through an ordering system/interface as text-based instructions. Feedback for the order and guidance during the order are provided to the user through: speech played over a speaker associated with the terminal, text displayed on a display, and/or images associated with the ordered items.