LEARNING FACTS FROM SEMI-STRUCTURED TEXT
    1.
    发明公开
    LEARNING FACTS FROM SEMI-STRUCTURED TEXT 审中-公开
    借鉴FACTS从半结构化文本

    公开(公告)号:EP1891557A2

    公开(公告)日:2008-02-27

    申请号:EP06784449.8

    申请日:2006-05-18

    申请人: Google Inc.

    IPC分类号: G06F17/30

    摘要: A method and system of learning, or bootstrapping, facts from semi-structured text is described. Starting with a set of seed facts associated with an object, documents associated with the object are identified. The identified documents are checked to determine if each has at least a first predefined number of seed facts. If a document does have at least a first predefined number of seed facts, a contextual pattern associated with the seed facts is identified and other instances of content in the document matching the contextual pattern are identified. If the document includes at least a second predefined number of the other instances of content matching the contextual pattern, then facts may be extracted from the other instances.

    METHOD AND SYSTEM FOR DETECTING FRAUDULENT INTERNET MERCHANTS
    2.
    发明公开
    METHOD AND SYSTEM FOR DETECTING FRAUDULENT INTERNET MERCHANTS 审中-公开
    方法和系统检测欺诈互联网零售商

    公开(公告)号:EP2545507A2

    公开(公告)日:2013-01-16

    申请号:EP11753825.6

    申请日:2011-03-03

    申请人: Google Inc.

    摘要: Systems and methods for detecting fraudulent merchants using the content of orders completed by the merchants. A fraud detection engine of a fraud detection system generates a fraud detection model using feature data extracted from order content data for known fraudulent and known non-fraudulent merchants. The fraud detection engine executes the model using feature data extracted from order content data for a target merchant to determine a fraud risk associated with the target merchant. If the fraud risk of the merchant is indicative of a fraudulent merchant, the fraud detection system can issue a request to a fraud analyst to review the target merchant further. The results of the fraud analyst's review can be used to update the fraud detection model.