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    USE OF STATISTICAL FLOW DATA FOR MACHINE TRANSLATIONS BETWEEN DIFFERENT LANGUAGES
    13.
    发明申请
    USE OF STATISTICAL FLOW DATA FOR MACHINE TRANSLATIONS BETWEEN DIFFERENT LANGUAGES 审中-公开
    使用不同语言之间的机器翻译统计流量数据

    公开(公告)号：US20160188575A1

    公开(公告)日：2016-06-30

    申请号：US14584925

    申请日：2014-12-29

    Applicant: EBAY INC.

    Inventor： Hassan Sawaf

    IPC: G06F17/28

    Abstract: In a flow of computer actions, a computer system (110) receives a request involving a machine translation. In performing the translation (160, 238), or in using the translation in subsequent computer operations (242, 1110), the computer system takes into account known statistical relationships (310), obtained from previously accumulated click-through data (180), between a machine translation performed in a flow, the flow's portions preceding the translation, and success indicators pertaining to the flow's portion following the translation. The statistical relationships are derived by data mining of the click-through data. Further, normal actions can be suspended to use a random option to accumulate the click-through data and/or perform statistical AB testing. Other features are also provided.

    Abstract translation: 在计算机动作的流程中，计算机系统（110）接收涉及机器翻译的请求。 在执行翻译（160,238）中或在随后的计算机操作（242,1110）中使用翻译时，计算机系统考虑从先前累积的点击数据（180）获得的已知统计关系（310） 在流程中执行的机器翻译，翻译之前的流程部分以及与翻译之后的流程部分有关的成功指示。 统计关系是通过点击型数据的数据挖掘获得的。 此外，可以暂停正常操作以使用随机选项来累积点击数据和/或执行统计AB测试。 还提供其他功能。

    AUTOMATIC MACHINE TRANSLATION USING USER FEEDBACK
    16.
    发明申请
    AUTOMATIC MACHINE TRANSLATION USING USER FEEDBACK 审中-公开

    公开(公告)号：US20170154074A1

    公开(公告)日：2017-06-01

    申请号：US15430773

    申请日：2017-02-13

    Applicant: eBay Inc.

    Inventor： Hassan Sawaf

    IPC: G06F17/30 ,  G06Q30/06

    CPC classification number: G06F16/2452 ,  G06F16/3337 ,  G06F17/2818 ,  G06F17/289 ,  G06Q30/0282 ,  G06Q30/0613 ,  G06Q30/0625

    Abstract: Publication system, such as ecommerce system, machine translation translates a query in a first language to a second language to query an ecommerce database maintained in the second language and obtain a result set responsive to the query. Human feedback relating to the result set is detected. If the feedback is positive the system increases the probability that the translation is correct. If the feedback is negative the system decreases the probability that the translation is correct. For positive feedback, the system detects whether a clue is recognized in the query. If a clue is recognized the system increases the value of the clue for making the translation. The system detects the identity of the product in the query, accesses the product vendor website that is maintained in the query language, and detects information that is in the query language for use in the translation process.

    Automatic extraction of multilingual dictionary items from non-parallel, multilingual, semi-structured data
    17.
    发明授权
    Automatic extraction of multilingual dictionary items from non-parallel, multilingual, semi-structured data 有权
    从非并行，多语言，半结构化数据自动提取多语言字典项目

    公开(公告)号：US09530161B2

    公开(公告)日：2016-12-27

    申请号：US14194606

    申请日：2014-02-28

    Applicant: eBay Inc.

    Inventor： Hassan Sawaf

    IPC: G06F17/27 ,  G06Q30/06 ,  G06F17/28

    CPC classification number: G06F17/289 ,  G06F17/28 ,  G06F17/2809 ,  G06F17/2818 ,  G06F17/2827 ,  G06F17/2845 ,  G06F17/2854 ,  G06F17/30964 ,  G06N99/005 ,  G06Q30/0601 ,  G06Q30/0609

    Abstract: User interfaces receive a first plurality of user queries and result sets that are in a category, exhibit a constraint, and exhibit user behavior. Also received are a second plurality of user queries and result sets that that are in the category, exhibit the constraint, and exhibit user behavior. The second user queries and results are received either from a plurality of user interfaces coupled to a second system, or from the second system itself. Responsive to detecting that the first plurality of user queries and result sets and the second plurality of user queries and result sets satisfy respective thresholds, a signal indicates that at least one of the first plurality of user queries and at least one of the second plurality of user queries are translations of each other.

    Abstract translation: 用户界面接收处于类别中的第一组多个用户查询和结果集，展示约束并呈现用户行为。 还接收的是第二组用户查询和结果集，它们在类别中，表现出约束，并呈现用户行为。 从与第二系统耦合的多个用户界面或从第二系统本身接收第二用户查询和结果。 响应于检测到所述第一多个用户查询和结果集以及所述第二多个用户查询和结果集合满足相应的阈值，信号指示所述第一多个用户查询中的至少一个和所述第二多个用户查询 用户查询是彼此的翻译。

    METHOD FOR PERFORMING SEQUENCE LABELLING ON QUERIES
    18.
    发明申请
    METHOD FOR PERFORMING SEQUENCE LABELLING ON QUERIES 有权
    在QUERIES上执行序列标签的方法

    公开(公告)号：US20160188670A1

    公开(公告)日：2016-06-30

    申请号：US14584483

    申请日：2014-12-29

    Applicant: eBay Inc.

    Inventor： Jean-David Ruvini ,  Sunil Mohan ,  Smruthi Mukund ,  Hassan Sawaf

    IPC: G06F17/30 ,  G06Q30/06

    CPC classification number: G06Q30/0623 ,  G06F17/30525 ,  G06F17/30604 ,  G06F17/30867

    Abstract: A method of propagating annotations of content items to a search query is disclosed. A strength of a correspondence between a search query and a title of a listing of an item on a network-based publication system is determined. The strength of the correspondence is based on an analysis of a set of actions by a set of users who submitted the search query. A set of annotations corresponding to the title is generated. The set of annotations is propagated to an additional search query such that the set of annotations and the strength of the correspondence are used by a search engine to enhance search results corresponding to the additional search query.

    Abstract translation: 公开了将内容项的注释传播到搜索查询的方法。 确定搜索查询和基于网络的出版系统上的项目的列表的标题之间的对应关系的强度。 通信的强度基于一组提交搜索查询的用户的一组操作的分析。 生成与标题对应的一组注释。 所述注释集合被传播到附加搜索查询，使得所述一组注释和所述对应的强度被搜索引擎用于增强与所述附加搜索查询相对应的搜索结果。

    DETECTING CROSS-LINGUAL COMPARABLE LISTINGS
    19.
    发明申请
    DETECTING CROSS-LINGUAL COMPARABLE LISTINGS 有权

    公开(公告)号：US20230079147A1

    公开(公告)日：2023-03-16

    申请号：US18055574

    申请日：2022-11-15

    Applicant: eBay Inc.

    Inventor： Sanjika Hewavitharana ,  Evgeny Matusov ,  Robinson Piramuthu ,  Hassan Sawaf

    IPC: G06Q30/06 ,  G06F40/58 ,  G06N20/00 ,  G06F16/50

    Abstract: In various example embodiments, a system and method for a Listing Engine that translates a first listing from a first language to a second language. The first listing includes an image(s) of a first item. The Listing Engine provides as input to an encoded neural network model a portion(s) of a translated first listing and a portions(s) of a second listing in the second language. The second listing includes an image(s) of a second item. The Listing Engine receives from the encoded neural network model a first feature vector for the translated first listing and a second feature vector for the second listing. The first and the second feature vectors both include at least one type of image signature feature and at least one type of listing text-based feature. Based on a similarity score of the first and second feature vectors at least meeting a similarity score threshold, the Listing Engine generates a pairing of the first listing in the first language with the second listing in the second language for inclusion in training data of a machine translation system.

    Method, medium, and system for detecting cross-lingual comparable listings for machine translation using image similarity
    20.
    发明授权
    Method, medium, and system for detecting cross-lingual comparable listings for machine translation using image similarity 有权

    公开(公告)号：US10319019B2

    公开(公告)日：2019-06-11

    申请号：US15264873

    申请日：2016-09-14

    Applicant: eBay Inc.

    Inventor： Sanjika Hewavitharana ,  Evgeny Matusov ,  Robinson Piramuthu ,  Hassan Sawaf

    IPC: G06Q30/00 ,  G06Q30/06 ,  G06F17/28 ,  G06F16/50

    Abstract: In various example embodiments, a system and method for a Listing Engine that translates a first listing from a first language to a second language. The first listing includes an image(s) of a first item. The Listing Engine provides as input to an encoded neural network model a portion(s) of a translated first listing and a portions(s) of a second listing in the second language. The second listing includes an image(s) of a second item. The Listing Engine receives from the encoded neural network model a first feature vector for the translated first listing and a second feature vector for the second listing. The first and the second feature vectors both include at least one type of image signature feature and at least one type of listing text-based feature. Based on a similarity score of the first and second feature vectors at least meeting a similarity score threshold, the Listing Engine generates a pairing of the first listing in the first language with the second listing in the second language for inclusion in training data of a machine translation system.

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