Abstract: Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating sellability and cancellability scores for selling objects on an electronic marketplace. An embodiment operates by receiving, from a mobile device, an image including an object for sale and determining information associated with the object for sale. Information associated with pre-identified objects is determined from information associated with pre-identified objects, where each of the pre-identified objects corresponds to the object for sale. A sellability score and/or a cancellability score is generated based at least in part on the information associated with the object for sale and the information associated with the pre-identified objects. The sellability score and the cancellability score are further provided to users.

Abstract: Provided herein are various embodiments for automating the creation of listings using augmented reality. An embodiment operates by identifying a template for a for sale object (FSO), selecting a first image of the one or more common images of the template, and determining a boundary of the first image. It is determined that a listing image of the FSO, through a camera of a computing device, is smaller than the boundary prior to taking the listing image through the camera, and instructions are provided to move the FSO to more closely align to the boundary. A command is provided to the camera to take the listing image of the FSO responsive to the detecting that the listing image of the FSO more closely aligns to the boundary. A listing for the FSO is generated using the listing image.

Abstract: 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.

Abstract: Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using computer technology to automate the creation of consistent, high quality listings for selling “for sale objects” (FSO) on an ecommerce site. Some embodiments are configured to or operate by: identifying a category of a FSO; accessing templates for the category from a template database; navigating a user through a computer generated augmented reality (AR) environment using the templates to generate images of the FSO; analyzing one or more of the images to determine characteristics of the FSO; and generating a listing for the FSO using the images and the characteristics.

Abstract: Disclosed herein are embodiments for intelligent listing creation for a for sale object (FSO). Some embodiments operate by determining a numerical identifier corresponding to a category of the FSO. A binarization of the numerical identifier using hot encoding is performed and using a neural network regression model, an optimal offer price is generated based on a category of the FSO. Information about the FSO is provided to the neural network regression model that tokenizes the textual input, and a unique binary vector representing the category is provided instead of the numerical identifier to the neural network regression model. An optimal price, generated by the neural network regression model, based on the unique binary vector representing the category.

Abstract: Disclosed herein are embodiments for intelligent listing creation for a for sale object (FSO). Some embodiments operate by determining a numerical identifier corresponding to a category of the FSO. A binarization of the numerical identifier using hot encoding is performed and using a neural network regression model, an optimal offer price is generated based on a category of the FSO. Information about the FSO is provided to the neural network regression model that tokenizes the textual input, and a unique binary vector representing the category is provided instead of the numerical identifier to the neural network regression model. An optimal price, generated by the neural network regression model, based on the unique binary vector representing the category.

Abstract: Disclosed herein are system, method, and computer program product embodiments for probabilistic search biasing and recommendations. A system including at least one processor may be configured to receive an input relating to an identified item, generate a database query based on the input, and receive a response to the database query. The response may include information on comparable items similar to the identified item, and corresponding metadata for the comparable items. The corresponding metadata may include a range of values corresponding to the comparable items. The system may be further configured to generate a probability score for at least two values of the range of values, based at least on the corresponding metadata for the comparable items. The system may be further configured to output at least a suggested value based on at least the generated probability score for the range of values and prompt for further input.

Abstract: Described herein are embodiments for machine-generating and naming ontologies for for-sale items. A neural network may be used to train information describing for-sale items into feature vectors that describe the for-sale items. These feature vectors may be sorted into clusters based on their relative proximity using clustering algorithms. The resulting clusters may be sub-divided into smaller clusters depending on the precision used in the clustering algorithm. The set of clusters may form a hierarchical data structure where each level has clusters determined at a certain precision and each lower level sub-divides those clusters. The clusters may be named based on the most salient facets that describe the for-sale items in the clusters.

Abstract: Disclosed herein are embodiments for automatic, intelligent generation of listings for a for sale object (FSO) being offered by a seller. Some embodiments operate by: receiving information relating to the FSO, including specifications for selling the FSO and an election of an automatic listing option; determining a category of the FSO; generating an optimal offer price based on at least the category; and generating multiple listings for the FSO, wherein the multiple listings have varying titles, descriptions, pictures and offer prices.

Abstract: Disclosed herein are system, method, and computer program product embodiments for probabilistic search biasing and recommendations. A system including at least one processor may be configured to receive an input relating to an identified item, generate a database query based on the input, and receive a response to the database query. The response may include information on comparable items similar to the identified item, and corresponding metadata for the comparable items. The corresponding metadata may include a range of values corresponding to the comparable items. The system may be further configured to generate a probability score for at least two values of the range of values, based at least on the corresponding metadata for the comparable items. The system may be further configured to output at least a suggested value based on at least the generated probability score for the range of values and prompt for further input.

Abstract: Disclosed herein are system, computer-program product (non-transitory computer-readable medium), and method embodiments for machine-learning prediction or suggestion based on object identification. A system including at least one processor may be configured to cross-reference an identifier of a selected object with a list of known unique identifiers. The selected object may be selected via received selection. The at least one processor may further retrieve a set of values associated with the identifier of the selected object, upon determining that the list of known unique identifiers includes the identifier of the selected object, and perform machine-learning to derive a predicted-value set based at least in part on the set of values associated with the identifier of the selected object and a category applicable to the selected object. The at least one processor may determine that the predicted-value set satisfies a predetermined confidence condition, and output at least part of the predicted-value set.

Abstract: Disclosed herein are embodiments for automatic, intelligent generation of listings for a for sale object (FSO) being offered by a seller. Some embodiments operate by: receiving information relating to the FSO, including specifications for selling the FSO and an election of an automatic listing option; determining a category of the FSO; generating an optimal offer price based on at least the category; and generating multiple listings for the FSO, wherein the multiple listings have varying titles, descriptions, pictures and offer prices.

Abstract: 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.

Abstract: Described herein are embodiments for improving search engine results of listings of For Sale Objects (FSOs). A search engine may be improved by implementing rules that resolve ambiguity between listings for different (FSOs) that match the same search inputs. An unsupervised machine learning module may evaluate candidate rules and identify improvements that may not be obvious to a human evaluator. An ecommerce site that combines the improved search engine with the unsupervised machine learning module may dynamically evaluate search results using different candidate rules and iteratively improve search results.

Abstract: Described herein are embodiments for assisting in creating a listing for a For Sale Object (FSO). An item name suggestion module receives seller input and provides suggested entries for the listing to help the seller describe the FSO more accurately and consistently. A hierarchical database provides a structure for ordering suggested entries, with the structure ordered based on scores. The scores are based on rules that relate item characteristics and take into account rankings of those item characteristics with respect to one another. Metadata tags that are used by the online merchandise platforms can be identified and included in the listing, even if a seller is not familiar with the metadata tags. The hierarchical database also connects or associates item characteristics in groups that describe specific FSO. The connections can help to optimize search results as the listing is completed by the seller.

Abstract: Disclosed herein are system, method, and computer program product embodiments for probabilistic item matching and searching. A system including at least one processor may be configured to receive a data point relating to a specific item, generate a database query based on the data point, and receive a response to the database query. The response may include multiple candidate items relating to the specific item. The system may be further configured to receive a first input relating to the specific item and generate a probability score for at least two candidate items of the multiple candidate items in the response, based on at least the second input. The system may be further configured to select a selected item from the candidate items, based on the probability score for the selected item. The system may be further configured to output a reference to, or value representing, the selected item.

Abstract: Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using computer technology to automate the creation of consistent, high quality listings for selling “for sale objects” (FSO) on an ecommerce site. Some embodiments are configured to or operate by: identifying a category of a FSO; accessing templates for the category from a template database; navigating a user through a computer generated augmented reality (AR) environment using the templates to generate images of the FSO; analyzing one or more of the images to determine characteristics of the FSO; and generating a listing for the FSO using the images and the characteristics.

Abstract: An electronic device is provided. The electronic device includes a communication module, a microphone receiving a voice input according to user speech, a memory storing information about an operation of the speech recognition service, a display, and a processor electrically connected with the communication module, the microphone, the memory, and the display. The processor is configured to calculate a specified numerical value associated with the operation of the speech recognition service, to transmit information about the numerical value to a first external device processing the voice input, and to transmit a request for a function, which corresponds to the calculated numerical value, of at least one function associated with the speech recognition service stepwisely provided from the first external device depending on a numerical value, to the first external device to refine a function of the speech recognition service supported by the electronic device.

Abstract: A method for authoring and displaying a virtual tour of a three-dimensional space which employs transitional effects simulating motion. An authoring tool is provided for interactively defining a series of locations in the space for which two-dimensional images, e.g., panoramas, photographs, etc., are available. A user identifies one or more view directions for a first-person perspective viewer for each location. For pairs of locations in the series, transitional effects are identified to simulate smooth motion between the pair of locations. The authoring tool stores data corresponding to the locations, view directions and transitional effects for playback on a display. When the stored data is accessed, a virtual tour of the space is created that includes transitional effects simulating motion between locations. The virtual tour created can allow a viewer to experience the three-dimensional space in a realistic manner.