Abstract: In various example embodiments, a system and method for using camera metadata for making recommendations are presented. At least one image file having camera metadata is received. The camera metadata of the at least one image file is analyzed to determine improvements to image capture aspects associated with the at least one image file. Feedback related to the improvements to the image capture aspects associated with the at least one image file is generated. In some embodiments, the feedback may be used to generate camera and other product upgrade recommendations.

Abstract: An inventory prediction system is described that outputs a predicted inventory item not included in a user's known inventory using a cross-category directional graph that represents item categories as nodes. The inventory prediction system implements a prediction model trained using machine learning to output the predicted inventory item using the graph and at least one item from the user's known inventory. The inventory prediction system is further configured to generate a listing recommendation for the predicted inventory item. To do so, the inventory prediction system implements a logistic regression model trained using machine learning to calculate a probability that the listing recommendation should be generated using attributes of the predicted inventory item and attributes of currently trending items.

Abstract: Software is increasingly being developed as a collection of loosely coupled applications. Loosely coupled applications exchange data by publishing data to and retrieving data from a data store, such as a database, a file located on a storage cluster, etc. Data produced by one application and consumed by another is referred to as a data dependency. In some embodiments, an application's data dependencies are identified by analyzing cached query plans associated with the application. Query plans include a hierarchical representation of a query, where non-leaf nodes represent commands and leaf nodes identify data dependencies. An application's data dependencies are identified by traversing the hierarchical representation of the query. Data dependencies consumed by the application are identified by finding leaf nodes that descend from a read command, while data dependencies produced by the application are identified by finding leaf nodes that descend from a write command.

Abstract: Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Abstract: Technologies are shown for trust delegation that involve receiving a first request from a subject client and responding by sending a first token having first permissions to the subject client. A second request from a first partner actor is received that includes the first token, and in response, the first partner actor is linked to the subject client in a trust stack and a second token is sent to the first actor with second permissions, the second token identifying the subject client and the first partner actor. A third request from a second partner actor is received that includes the second token, and in response, the second partner actor is linked to the first partner actor in the trust stack and a third token is sent to the second partner actor with third permissions, the third token identifying the first partner actor and the second partner actor.

Abstract: Various embodiments described herein assist in identifying one or more product items of interest (e.g., high demand product items) based on surge activity, such as user buying surges, user selling surges, and user product listing (e.g., electronic or online listing) surges on an online marketplace system, and can further notify one or more users of selling opportunities of the identified products items of interest.

Abstract: Methods, apparatus, and systems to determine a niche market of items or services, the first phase of which identifies a gap between demand and supply for a set of items. Session logs may be evaluated to compare transactions involving a specific item to those of a larger group of items. The resultant information identifies areas of high demand, but with low availability. The niche market information may be provided as direct merchandising items for sellers. In one example, the method generates niche market item web pages in specific categories. Additional methods, apparatus, and systems are disclosed.

Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.

Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.

Abstract: In various example embodiments, a system and method for smart recurrent orders are presented. An inventory indicator corresponding to an inventory level of a first item may be received. An order schedule for the first item may be identified. An adjustment to the order schedule based on the inventory indicator may be determined. The adjustment to the order schedule for the first item may be facilitated.

Abstract: Methods and systems for protecting seller privacy during an ecommerce transaction are disclosed. In one aspect, a method includes, receiving, via an online listing configuration interface for a first session, one or more candidate pick up times and specific pick up locations for an item, determining a generalized version of the one or more specific pick up locations, displaying, via a second session, an online listing for the item, displaying, via the second session, the one or more candidate pick up times and the generalized versions of the one or more specific pick up locations, receiving, via the second session, a selection of one of the candidate pick up times and one of the generalized versions of one of the specific pick up locations, in response to receiving payment for the item, displaying a specific pick up location corresponding to the selected one generalized version.

Abstract: Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Abstract: An automated encryption system to: store a first key policy in association with a first key, and a second key policy in association with a second key; determine that a remote machine stores a first application that is affected by the first key policy and a second application affected by the second key policy, wherein the first application utilizes the first key to encrypt first data, and the second application utilizes the second key to encrypt second data; determine that the first key of the first application is non-compliant with the first key policy; send a request to deploy a third key in response to determining that the first key of the first application is non-compliant with the first key policy; and receive a response that includes a result of the request to deploy the third key.

Abstract: Storage space is reclaimed by cleaning and compacting data objects where data objects are stored by immutable storage. A storage area of which space needs to be reclaimed is identified. Active and stale data objects stored in a storage area are identified, and only active data objects are transferred to a shadow storage area from the storage area when recovering storage space. I/O operations can be fulfilled from the storage area and the shadow storage area. Compaction requests and I/O requests are throttled according to QOS parameters. Recovery of storage space does not cause a failure to meet performance requirements for any storage volume.

Abstract: Systems and methods of improving the functioning of a streaming platform system by managing database change stream offsets using a time series database are disclosed. In some example embodiments, a computer system retrieves an offset value from a plurality of offset values stored in a time series database, with the plurality of offset values being indexed in the time series database in time order, and the retrieved offset value being retrieved using a time parameter, and then the computer system transmits a data request to a stream-processing platform, with the data request comprising the retrieved offset value, and the data request being operable to retrieve a data record stored in association with the retrieved offset value in a storage layer of the stream-processing platform using the offset value.

Abstract: A machine is configured to automatically generate listings for multiple items. For example, the machine receives, from a client device, two or more images and two or more descriptions. The two or more images depict two or more items. The two or more descriptions pertain to the two or more items. The machine matches one or more images of the two or more images to a description of the two or more descriptions. The one or more images depict an item of the two or more items. The description pertains to the item. The machine, based on the matching, generates a listing of the item. The listing includes the one or more images depicting the item, and the description pertaining to the item. The machine causes display of the listing of the item in a user interface.

Abstract: In various example embodiments, a system and method for modifying images are presented. The system receives a user interface selection initiating an image capture and detects a first image capture parameter. The system identifies an object of interest within a field of view of an image capture device and identifies a set of object characteristics of the object of interest. The system generates a parameter notification indicating a suggested modification of the first image capture parameter based on one or more object characteristics of the set of object characteristics. The system causes presentation of the parameter notification at the image capture device.

Abstract: In various example embodiments, a system and method for determining a crowd response for a crowd are presented. One method is disclosed that includes receiving an audio signal that includes concurrent responses from two or more respondents, determining the concurrent responses from the audio signal without regard to the identity of the respondents, and generating a crowd based on the concurrent responses.

Abstract: Various implementations described herein are able to leverage the interaction from one or more potential buyers relative to a digital image to automatically create a sales listing for items that appear to be of interest to the buyers. This reduces or eliminates all together the manual effort previously required of sellers in researching and collecting data on each item they wish to sell. Because of their technical nature, the innovative solutions described herein are also readily scalable which, in turn, greatly improves the seller's experience. Based on buyer interaction experiences, sales listings for each item for sale can be automatically created and listed.

Abstract: In various exemplary embodiments, a system and an associated method to retrieve information related to marketplace items within an electronic environment are disclosed. A network architecture comprises a listing module to store the information related to the marketplace items. The related information includes one or more user-created items such as an image of a model with one or more tagged items worn by the model. Each of the one or more tagged items has associated descriptive metadata. A communications module is arranged to receive a query including search terms related to social fashion items from an end-user. A query engine is coupled to the communications module to match the search terms contained within the query to the associated descriptive metadata of the tagged items in the listing module. A processing module then displays to the end-user the model and the one or more tagged items.