Abstract: A system includes one or more processors and a non-transitory machine-readable storage device comprising processor executable instructions that, when executed, cause the one or more processors to perform a set of operations comprising receiving a search request for one or more database records of a network based publication system, and identifying a first database record corresponding to at least a portion of the search request, where the database record having a first element. The set of operations also include selecting a second element of a second database record based on the first database record and adjusting the first element of the database record based on the second element. The set of operations then includes generating a formatted user interface comprising a representation of the database record and the adjusted first element, and causing, in response to the search request, presentation of the formatted user interface on the remote computing device.

Abstract: In various example embodiments, a system and method for retrieving database records are presented. A method includes receiving an access request for database records, identifying a primary database record corresponding to the access request, and selecting a set of secondary database records corresponding to a portion of the access request. The method determines a set of differentiating elements within records of the set of secondary database records. Each differentiating element distinguishes at least one record of the set of secondary database records from one or more of the primary database record and a portion of the records included in the set of secondary database records. The method generates a formatted search interface including a set of selectable interface icons representing one or more differentiating elements and causes presentation of the formatted search interface at a client device associated with the access request.

Abstract: Systems and methods for improving a search process are provided. A networked system accesses, from online sources, fashion trend information including pictures illustrating fashion trends. The networked system determines a plurality of top fashion trends, and extracts, using an image detection algorithm, images of fashion items from a picture associated with each of the top fashion trends. Using the extracted images, the networked system performs an image search for matching inventory items. The networked system then generates and stored a plurality of fashion trend user interfaces, whereby the plurality of fashion trend user interfaces each comprise selectable elements that represent the plurality of top fashion trends. At runtime, the networked system receives an indication to initiate a search for fashion by trends, and in response, accesses the plurality of stored fashion trend user interfaces. One of the plurality of stored fashion trend user interfaces is presented on a user device.

Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.

Abstract: In various example embodiments, a system and method for retrieving database records are presented. A method includes receiving an access request for database records, identifying a primary database record corresponding to the access request, and selecting a set of secondary database records corresponding to a portion of the access request. The method determines a set of differentiating elements within records of the set of secondary database records. Each differentiating element distinguishes at least one record of the set of secondary database records from one or more of the primary database record and a portion of the records included in the set of secondary database records. The method generates a formatted search interface including a set of selectable interface icons representing one or more differentiating elements and causes presentation of the formatted search interface at a client device associated with the access request.

Abstract: In various example embodiments, a system and method for retrieving database records are presented. A method includes receiving an access request for database records, identifying a primary database record corresponding to the access request, and selecting a set of secondary database records corresponding to a portion of the access request. The method determines a set of differentiating elements within records of the set of secondary database records. Each differentiating element distinguishes at least one record of the set of secondary database records from one or more of the primary database record and a portion of the records included in the set of secondary database records. The method generates a formatted search interface including a set of selectable interface icons representing one or more differentiating elements and causes presentation of the formatted search interface at a client device associated with the access request.

Abstract: Systems, methods and media are provided for training a snippet extractor to create snippets based on information extracted from published descriptions. In one example, a computer-implemented method includes creating, based on a non-RNN (Recurrent Neural Network) extraction technique performed on the published descriptions, a plurality of base models, each base model including one or more sample description summaries; evaluating the base models using an evaluation technique; selecting an optimum base model; developing a classification model using RNN extraction, the classification model based on description summaries contained in the optimum base model; and using the classification model to train the snippet extractor by machine learning.

Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.

Abstract: Systems and methods for improving a search process are provided. A networked system accesses, from online sources, fashion trend information including pictures illustrating fashion trends. The networked system determines a plurality of top fashion trends, and extracts, using an image detection algorithm, images of fashion items from a picture associated with each of the top fashion trends. Using the extracted images, the networked system performs an image search for matching inventory items. The networked system then generates and stored a plurality of fashion trend user interfaces, whereby the plurality of fashion trend user interfaces each comprise selectable elements that represent the plurality of top fashion trends. At runtime, the networked system receives an indication to initiate a search for fashion by trends, and in response, accesses the plurality of stored fashion trend user interfaces. One of the plurality of stored fashion trend user interfaces is presented on a user device.

Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.

Abstract: Method for analyzing review content is described herein. The method starts by generating a helpfulness score for each review in the plurality of reviews. A first set of reviews is selected based on the helpfulness scores for each review in the plurality of review and a helpfulness score for each sentence in each review in the first set of reviews is generated. The review summary is then generated by selecting sentences in each review in the first set of reviews based on the helpfulness score of each sentence. The review summary includes the selected sentences. Other embodiments are also described.

Abstract: A system includes one or more processors and a non-transitory machine-readable storage device comprising processor executable instructions that, when executed, cause the one or more processors to perform a set of operations comprising receiving a search request for one or more database records of a network based publication system, and identifying a first database record corresponding to at least a portion of the search request, where the database record having a first element. The set of operations also include selecting a second element of a second database record based on the first database record and adjusting the first element of the database record based on the second element. The set of operations then includes generating a formatted user interface comprising a representation of the database record and the adjusted first element, and causing, in response to the search request, presentation of the formatted user interface on the remote computing device.

Abstract: In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.

Abstract: In various example embodiments, a system and method for retrieving database records are presented. A method includes receiving an access request for database records, identifying a primary database record corresponding to the access request, and selecting a set of secondary database records corresponding to a portion of the access request. The method determines a set of differentiating elements within records of the set of secondary database records. Each differentiating element distinguishes at least one record of the set of secondary database records from one or more of the primary database record and a portion of the records included in the set of secondary database records. The method generates a formatted search interface including a set of selectable interface icons representing one or more differentiating elements and causes presentation of the formatted search interface at a client device associated with the access request.

Abstract: Systems, methods and media are provided for training a snippet extractor to create snippets based on information extracted from published descriptions. In one example, a computer-implemented method includes creating, based on a non-RNN (Recurrent Neural Network) extraction technique performed on the published descriptions, a plurality of base models, each base model including one or more sample description summaries; evaluating the base models using an evaluation technique; selecting an optimum base model; developing a classification model using RNN extraction, the classification model based on description summaries contained in the optimum base model; and using the classification model to train the snippet extractor by machine learning.