Abstract: In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.

Abstract: Processing natural language user inputs into a more formal, machine-readable, structured query representation used for making an item recommendation. Analyses of user inputs are coordinated via a knowledge graph constructed from categories, attributes, and attribute values describing relatively frequently occurring prior interactions of various users with an electronic marketplace. The knowledge graph has directed edges each with a score value based on: the conditional probabilities of category/attribute/attribute value interactions calculated from user behavioral patterns, associations between user queries and structured data based on historical buyer behavioral patterns in the marketplace, metadata from items made available for purchase by sellers used to better define buyers' requirements, and/or world knowledge of weather, locations/places, occasions, and item recipients that map to inventory-related data, for generating relevant prompts for further user input.

Abstract: In various example embodiments, techniques for querying a product in a database of a publication system using a tail query are presented. An application interface module receives, from a device of a user, a tail query for a product in the publication system. The tail query has a common term and an uncommon term. A data storage interface module can access, from a search metrics database, a plurality of product categories associated with the common term, and access user behavior data, with the user behavior data including product views corresponding to past search queries in the publication system. A category predictor can determine a first product category from the plurality of product categories for the tail query based on the user behavior data and information derived from the search metrics database. A listing generator can generate an ordered list of product listings associated with the first product category based on the user behavior data.

Abstract: Images of items often include a significant amount of information that can be used in categorizing the item (e.g., as a book, a phone, or an accessory) or in identifying attributes of the item (e.g., the item's color or style). A user provides a search query for listings of items. Images of items in listings previously selected by users providing the same search query are analyzed to identify the category or attributes of the depicted items. The identified category or attributes are added to the user's search query. Listings matching the modified search query are provided to the user.

Abstract: In various example embodiments, a system and method for determining a spam publication using a spam detection system are presented. The spam detection system receives, from a device, an image of an item and an item attribute for the item. Additionally, the spam detection system extracts an image attribute based on the received image, and compares the item attribute and the image attribute. Moreover, the spam detection system calculates a confidence score based on the comparison. Furthermore, the spam detection system determines that the item attribute is incorrect based on the confidence score transgressing a predetermined threshold. In response to the determination that the item attribute is incorrect, the spam detection system causes presentation, on a display of the device, of a notification.