Determining collaboration recommendations from file path information

    公开(公告)号:US11928083B2

    公开(公告)日:2024-03-12

    申请号:US16264357

    申请日:2019-01-31

    Applicant: Box, Inc.

    Abstract: Methods, systems and computer program products for recommendation systems. Embodiments commence by gathering a set of pathnames that refer to content objects of a collaboration system. A tokenizer converts at least some of the pathnames into vectors. The vectors comprise hierarchical path components such as folder names or file names, which vectors are labeled with an indication as to whether or not the folder or file referred to in a particular vector had been clicked on by one or more users. Some portion of the labeled vectors are used to train a predictive model. Another portion of the vectors are used to validate the predictive model. When the model exhibits sufficient precision and recall, the predictive model is then used to predict the probability that a particular user would have an interest in a particular folder or file. The folder name or file name is presented as a collaboration recommendation.

    DETERMINING COLLABORATION RECOMMENDATIONS FROM FILE PATH INFORMATION

    公开(公告)号:US20190163671A1

    公开(公告)日:2019-05-30

    申请号:US16264357

    申请日:2019-01-31

    Applicant: Box, Inc.

    Abstract: Methods, systems and computer program products for recommendation systems. Embodiments commence by gathering a set of pathnames that refer to content objects of a collaboration system. A tokenizer converts at least some of the pathnames into vectors. The vectors comprise hierarchical path components such as folder names or file names, which vectors are labeled with an indication as to whether or not the folder or file referred to in a particular vector had been clicked on by one or more users. Some portion of the labeled vectors are used to train a predictive model. Another portion of the vectors are used to validate the predictive model. When the model exhibits sufficient precision and recall, the predictive model is then used to predict the probability that a particular user would have an interest in a particular folder or file. The folder name or file name is presented as a collaboration recommendation.

    PRIORITIZING OPERATIONS OVER CONTENT OBJECTS OF A CONTENT MANAGEMENT SYSTEM

    公开(公告)号:US20240314135A1

    公开(公告)日:2024-09-19

    申请号:US18439680

    申请日:2024-02-12

    Applicant: Box, Inc.

    Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

    PRIORITIZING OPERATIONS OVER CONTENT OBJECTS OF A CONTENT MANAGEMENT SYSTEM

    公开(公告)号:US20220086518A1

    公开(公告)日:2022-03-17

    申请号:US17163222

    申请日:2021-01-29

    Applicant: Box, Inc.

    Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

    Prioritizing operations over content objects of a content management system

    公开(公告)号:US11936656B2

    公开(公告)日:2024-03-19

    申请号:US17163222

    申请日:2021-01-29

    Applicant: Box, Inc.

    Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

    AVOIDING USER SESSION MISCLASSIFICATION USING CONFIGURATION AND ACTIVITY FINGERPRINTS

    公开(公告)号:US20200092298A1

    公开(公告)日:2020-03-19

    申请号:US16553106

    申请日:2019-08-27

    Applicant: Box, Inc.

    Abstract: Methods, systems and computer program products for computing system security. Techniques for classifying a potentially unauthorized user as an authorized user involve comparisons of two or more access request times that occur at different computing devices in different geographical locations. Based on those comparisons and the distance between the geographical locations of the different computing devices, a determination is made as to whether or not travel (e.g., via overland travel, via air travel, etc.) between those different geographical locations can be reasonably accomplished within a given time period. If it is determined that the required time for travel between the different geographical locations is greater than the time between the access request times—thus suggesting a spoofing attack or other malfeasance—then the potentially unauthorized (i.e., only potentially malfeasant) access can still be deemed as an authorizable access request by analyzing browser configurations and activity patterns of the potentially unauthorized user.

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