Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.

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: Understanding emojis in the context of online experiences is described. In at least some embodiments, text input is received and a vector representation of the text input is computed. Based on the vector representation, one or more emojis that correspond to the vector representation of the text input are ascertained and a response is formulated that includes at least one of the one or more emojis. In other embodiments, input from a client machine is received. The input includes at least one emoji. A computed vector representation of the emoji is used to look for vector representations of words or phrases that are close to the computed vector representation of the emoji. At least one of the words or phrases is selected and at least one task is performed using the selected word(s) or phrase(s).

Abstract: Understanding emojis in the context of online experiences is described. In at least some embodiments, text input is received and a vector representation of the text input is computed. Based on the vector representation, one or more emojis that correspond to the vector representation of the text input are ascertained and a response is formulated that includes at least one of the one or more emojis. In other embodiments, input from a client machine is received. The input includes at least one emoji. A computed vector representation of the emoji is used to look for vector representations of words or phrases that are close to the computed vector representation of the emoji. At least one of the words or phrases is selected and at least one task is performed using the selected word(s) or phrase(s).

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: Various methods and systems for determining a dominant object of a query and employing the dominant object to provide enhanced search services are discussed. A query is segmented into a set of n_grams. Entity extraction and resolution (EER) methods are employed to determine implicit and explicit aspects for each n_gram. N_grams that include explicit aspects are pruned from the set of n_grams and a pruned set of candidate n_grams is generated from the non-pruned n_grams. Knowledge graphs are employed to generate a ranked list of associated categories for each candidate n_gram. A ranked list of categories associated with the un-segmented query is generated based on knowledge graphs. The candidate n_gram with the highest ranked associated category that is also a highly ranked category associated with the un-segmented query is selected as the dominant object of the query. Enhanced search results are provided based on the determined dominant object.

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: Understanding emojis in the context of online experiences is described. In at least some embodiments, text input is received and a vector representation of the text input is computed. Based on the vector representation, one or more emojis that correspond to the vector representation of the text input are ascertained and a response is formulated that includes at least one of the one or more emojis. In other embodiments, input from a client machine is received. The input includes at least one emoji. A computed vector representation of the emoji is used to look for vector representations of words or phrases that are close to the computed vector representation of the emoji. At least one of the words or phrases is selected and at least one task is performed using the selected word(s) or phrase(s).

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: Methods and systems for query segmentation are disclosed. In one aspects, a method includes receiving, by one or more hardware processors, a query string, the query string comprising a plurality of tokens, identifying, by the one or more hardware processors, a first token and a second token from the plurality of tokens, determining, by the one or more hardware processors, a first vector and a second vector associated with the first token and the second token respectively, determining, by the one or more hardware processors, whether to include the first and second tokens in a single query segment based on the first and second vectors, generating, by the one or more hardware processors, a plurality of query segments based on the determination; and processing, by the one or more hardware processors, the query based on the plurality of query segments.

Abstract: Various embodiments use a neural network to analyze images for aspects that characterize the images, to present locations of those aspects on the images, and, additionally, to permit a user to interact with those locations on the images. For example, a user may interact with a visual cue over one of those locations to modify, refine, or filter the results of a visual search, performed on a publication corpus, that uses an input image (e.g., one captured using a mobile device) as a search query.

Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.

Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest or selection of such an image. The selection acts an anchor for subsequently displayed item images.

Abstract: Example embodiments that analyze images to characterize aspects of the images rely on a same neural network to characterize multiple aspects in parallel. Because additional neural networks are not required for additional aspects, such an approach scales with increased aspects.

Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.

Abstract: In various example embodiments, a system and method for applying a quantitative range for qualitative terms. In one example, a method includes gathering user interactions, identifying a qualitative term included in the user interactions, building an electronic knowledge graph that associates the qualitative term with a quantitative range for the product identified using the qualitative term according to values in the user interactions that include the qualitative term, receiving a query for the product that includes the qualitative term, and performing, in response to receiving the query, a search that limits results according to the quantitative range stored in the knowledge graph.

Abstract: Systems, methods, and computer program products for identifying a candidate product in an electronic marketplace based on a visual comparison between candidate product image visual content and input query image visual content. Embodiments generate and store descriptive image signatures from candidate product images or selected portions of such images. A subsequently calculated visual similarity measure serves as a visual search result score for the candidate product in comparison to an input query image. Any number of images of any number of candidate products may be analyzed, such as for items available for sale in an online marketplace. Image analysis results are stored in a database and made available for subsequent automated on-demand visual comparisons to an input query image. The embodiments enable substantially real time visual based product searching of a potentially vast catalog of items.

Abstract: Systems, methods, and computer program products for identifying a relevant candidate product in an electronic marketplace. Embodiments perform a visual similarity comparison between candidate product image visual content and input query image visual content, process formal and informal natural language user inputs, and coordinate aggregated past user interactions with the marketplace stored in a knowledge graph. Visually similar items and their corresponding product categories, aspects, and aspect values can determine suggested candidate products without discernible delay during a multi-turn user dialog. The user can then refine the search for the most relevant items available for purchase by providing responses to machine-generated prompts that are based on the initial search results from visual, voice, and/or text inputs. An intelligent online personal assistant can thus guide a user to the most relevant candidate product more efficiently than existing search tools.

Abstract: In various example embodiments, a system and method for balancing implicit and explicit indicators is presented. In one example, a method includes a user's utterance that includes a user query, extracting user intent parameters from the user query, constructing a structured query in a machine readable format using user intent parameters, determining whether the user query includes an implicit indicator, determining a confidence rating for the implicit indicator, updating the structured query to include the implicit indicator in response to the confidence rating for the implicit indicator being above a threshold value, and submitting the structured query to a database of items.

Abstract: Systems and methods for transforming formal and informal natural language user inputs into a more formal, machine-readable, structured representation of a search query. In one scenario, a processed sequence of user inputs and machine-generated prompts for further data from a user in a multi-turn interactive dialog improves the efficiency and accuracy of automated searches for the most relevant items available for purchase in an electronic marketplace. Analysis of user inputs may discern user intent, user input type, a dominant object of user interest, item categories, item attributes, attribute values, and item recipients. Other inputs considered may include dialog context, item inventory-related information, and external knowledge to improve inference of user intent from user input. Different types of analyses of the inputs each yield results that are interpreted in aggregate and coordinated via a knowledge graph based on past users' interactions with the electronic marketplace and/or inventory-related data.