IDENTIFYING SOCIAL BUSINESS CHARACTERISTIC USER

    公开(公告)号:US20170140301A1

    公开(公告)日:2017-05-18

    申请号:US15353601

    申请日:2016-11-16

    CPC classification number: G06N20/00 G06F16/248 G06F16/285 G06Q50/01 H04L51/32

    Abstract: A method includes acquiring user data of candidate users; mining a social business characteristic user in some of the candidate users according to the first social attribute data; training a classifier by using second social attribute data and second business object attribute data of the social business characteristic user; and inputting first social attribute data and first business object attribute data of a neighboring user to the classifier, and outputting a result of whether the neighboring user, in a period of time after the first period of time, is a social business characteristic user, wherein the neighboring user is a candidate user other than the social business characteristic user. The present disclosure increases the volume of associated data, and improves the accuracy of the classifier, thus improving the accuracy of identification, so that potential social business characteristic users in the first period of time can be identified.

    Method and device for generating online question paths from existing question banks using a knowledge graph

    公开(公告)号:US10579654B2

    公开(公告)日:2020-03-03

    申请号:US15752939

    申请日:2016-08-10

    Abstract: The disclosure provides an information processing method and device. In one embodiment, an information processing method comprises receiving a request for generating questions inputted by a user, the request for generating questions includes a to-be-learned knowledge point; acquiring, from a knowledge graph for questions, a node path including a target node indicating the to-be-learned knowledge point, the nodes in the knowledge graph for questions indicating question-answering steps of existing questions, knowledge points tested in the question-answering steps, and questioning styles corresponding to the question-answering steps; and generating questions required by the user according to question-answering steps, knowledge points tested in the question-answering steps, and questioning styles corresponding to the question-answering steps indicated by nodes on the node path. The present disclosure enables generation of new questions and facilitates the expansion of a question bank.

    Time Series Based Data Prediction Method and Apparatus

    公开(公告)号:US20180322404A1

    公开(公告)日:2018-11-08

    申请号:US16034281

    申请日:2018-07-12

    CPC classification number: G06N5/04 G06Q30/0202 G06Q50/02

    Abstract: A method and an apparatus for data prediction based on time series are provided. The method includes obtaining historical time series data of a plurality of category objects, the category objects including one or more data objects; selecting feature category object(s) from the plurality of category objects, the feature category object(s) being category object(s) including a respective feature data object, and the respective feature data object being a data object having a life cycle less than a predetermined time threshold; and predicting a target data object from among data object(s) included in the feature category object(s) based on historical time series data corresponding to the feature category object(s), the target data object being a data object with future time series data that is generated in a future first predetermined time period and satisfies a predetermined growth trend.

    Data Processing Method and Apparatus
    6.
    发明申请

    公开(公告)号:US20180308152A1

    公开(公告)日:2018-10-25

    申请号:US16024517

    申请日:2018-06-29

    Abstract: Data processing methods and apparatuses are provided. For a recommendation request submitted by a user, A matching between property information of the user and application criteria of all object display environments is performed to select various object display environments that satisfy the property information of the user, and object display environment(s) matching a first object of the request is/are analyzed based on historical records of the various object display environments, such as historical records of transaction data of the first object, historical records of application data of various first objects, and respective numbers of display positions of the various object display environments. A display recommendation that is generated based on the object display environment(s) can then be returned to a client of the user for presentation.

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