Abstract: A container system monitors one or more activities of an application container in a container system by intercepting data from the one or more activities of the application container. The application container includes computer-readable instructions and initiated via a container service and isolated using operating system-level virtualization. The monitoring is performed at a layer between the app container and the container service. The container system also transmits a report of the intercepted one or more activities to a designated source. The container system inspects the intercepted one or more activities, and in response to the intercepted one or more activities violating a policy in a policy store, triggers an action specified in the policy.

Abstract: A container system monitors one or more activities of an application container in a container system by intercepting data from the one or more activities of the application container. The application container includes computer-readable instructions and initiated via a container service and isolated using operating system-level virtualization. The monitoring is performed at a layer between the app container and the container service. The container system also transmits a report of the intercepted one or more activities to a designated source. The container system inspects the intercepted one or more activities, and in response to the intercepted one or more activities violating a policy in a policy store, triggers an action specified in the policy.

Abstract: The present disclosure relates to systems and methods for providing Online-to-Offline services. The method may include obtain first information associated with a first service request having been allocated to a service provider and having been accepted by the service provider. The method may also include obtaining second information associated with a second service request initiated via an application executed by a second requester terminal. The method may also include determining a matching parameter based on the first information and the second information by using at least one trained matching model and determining whether the matching parameter is larger than a threshold. The method may also include transmitting data associated with the second service request based on a result of the determination that the matching parameter is larger than the threshold.

Abstract: A method for user mining is provided. The method may include obtaining a plurality of first feature vectors of a plurality of positive samples and a plurality of second feature vectors of a plurality of negative samples, and generating a plurality of expanded first feature vectors based on the plurality of first feature vectors and second feature vectors and expanded second feature vectors. Each first feature vector may include first feature information that describes a plurality of features of a corresponding positive sample. Each second feature vector may include second feature information that describes a plurality of features of a corresponding negative sample. The method may further include determining one or more core features related to the plurality of positive samples among the plurality of features corresponding to the plurality of first feature vectors based on a trained binary model.

Abstract: A method for issuing coupons to a plurality of target users is provided. For each of the plurality of target users, the method may include determining a predicted value of a group indicator of the target user in a predetermined period. The method may further include grouping the plurality of target users using a plurality of grouping strategies. For each of the grouping strategies, the method may further include determining a candidate coupon issuing strategy. For each of the candidate coupon issuing strategies, the method may further include obtaining user feature information of one or more target users in each group corresponding to the candidate coupon issuing strategy. For each of the candidate coupon issuing strategies, the method may further include predicting an ROI of the candidate coupon issuing strategy based on an RO prediction model and the corresponding user feature information.

Abstract: A method for querying data is provided. The method may include determining a characteristic value of a selected feature dimension among feature values of the selected feature dimension of plurality of entities and establishing a corresponding relationship between the characteristic value and the selected feature dimension. The method may also include caching the corresponding feature value into a cache memory for each entity having a feature value of the selected feature dimension being unequal to the characteristic value, and leaving the corresponding feature value without caching for each entity having a feature value of the selected feature dimension being equal to the characteristic value. The method may further include performing a first search in the cache memory to produce a first search result in response to a query request related to the plurality of entities, and generating a query result based on the corresponding relationship and the first search result.

Abstract: A method for user mining is provided. The method may include obtaining a plurality of first feature vectors of a plurality of positive samples and a plurality of second feature vectors of a plurality of negative samples, and generating a plurality of expanded first feature vectors based on the plurality of first feature vectors and second feature vectors and expanded second feature vectors. Each first feature vector may include first feature information that describes a plurality of features of a corresponding positive sample. Each second feature vector may include second feature information that describes a plurality of features of a corresponding negative sample. The method may further include determining one or more core features related to the plurality of positive samples among the plurality of features corresponding to the plurality of first feature vectors based on a trained binary model.

Abstract: A method for querying data is provided. The method may include determining a characteristic value of a selected feature dimension among feature values of the selected feature dimension of plurality of entities and establishing a corresponding relationship between the characteristic value and the selected feature dimension. The method may also include caching the corresponding feature value into a cache memory for each entity having a feature value of the selected feature dimension being unequal to the characteristic value, and leaving the corresponding feature value without caching for each entity having a feature value of the selected feature dimension being equal to the characteristic value. The method may further include performing a first search in the cache memory to produce a first search result in response to a query request related to the plurality of entities, and generating a query result based on the corresponding relationship and the first search result.

Abstract: A method for issuing coupons to a plurality of target users is provided. For each of the plurality of target users, the method may include determining a predicted value of a group indicator of the target user in a predetermined period. The method may further include grouping the plurality of target users using a plurality of grouping strategies. For each of the grouping strategies, the method may further include determining a candidate coupon issuing strategy. For each of the candidate coupon issuing strategies, the method may further include obtaining user feature information of one or more target users in each group corresponding to the candidate coupon issuing strategy. For each of the candidate coupon issuing strategies, the method may further include predicting an ROI of the candidate coupon issuing strategy based on an RO prediction model and the corresponding user feature information.

Abstract: A method for querying data is provided. The method may include determining a characteristic value of a selected feature dimension among feature values of the selected feature dimension of plurality of entities and establishing a corresponding relationship between the characteristic value and the selected feature dimension. The method may also include caching the corresponding feature value into a cache memory for each entity having a feature value of the selected feature dimension being unequal to the characteristic value, and leaving the corresponding feature value without caching for each entity having a feature value of the selected feature dimension being equal to the characteristic value. The method may further include performing a first search in the cache memory to produce a first search result in response to a query request related to the plurality of entities, and generating a query result based on the corresponding relationship and the first search result.

Abstract: A container system monitors one or more activities of an application container in a container system by intercepting data from the one or more activities of the application container. The application container includes computer-readable instructions and initiated via a container service and isolated using operating system-level virtualization. The monitoring is performed at a layer between the app container and the container service. The container system also transmits a report of the intercepted one or more activities to a designated source. The container system inspects the intercepted one or more activities, and in response to the intercepted one or more activities violating a policy in a policy store, triggers an action specified in the policy.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: The present disclosure relates to systems and methods for providing Onlin-to-Offline services. The method may include obtain first information associated with a first service request having been allocated to a service provider and having been accepted by the service provider. The method may also include obtaining second information associated with a second service request initiated via an application executed by a second requester terminal. The method may also include determining a matching parameter based on the first information and the second information by using at least one trained matching model and determining whether the matching parameter is larger than a threshold. The method may also include transmitting data associated with the second service request based on a result of the determination that the matching parameter is larger than the threshold.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: Systems and methods are provided for group tagging. Such system may comprise processors accessible to platform data that comprises a plurality of users and a plurality of associated data fields, and a memory storing instructions that, when executed by the processors, cause the system to perform a method. The method may comprise obtaining a first subset users and associated first tags; determining, respectively for the associated data fields, at least a difference between the first subset users and at least some of the plurality of users; responsive to determining the difference exceeding a first threshold, determining the data field as a key data field; determining data of the corresponding key data fields associated with the first subset users as positive samples; obtaining, based on the key data fields, a second subset users and associated data as negative samples; and training a rule model with the positive and negative samples.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: A system and method for temporal-based professional similarity are provided. In example embodiments, a request to identify, from among a plurality of member profiles of a social network service, a profile that is similar to a source profile, is received. Profile data of the source profile and a candidate profile are accessed from the social network service. Profile features are extracted from the profile data. The profile features include source features extracted from the profile data of the source profile and candidate features extracted from the profile data of the candidate profile. Respective profile features correspond to temporal data included in the profile data. Data structures are generated by structuring the profile features according to the temporal data. The data structures include a source data structure generated using the source features and a candidate data structure generated using the candidate features.

Abstract: Embodiments of the invention relate to automatically configuring a Transparent Interconnection of Lots of Links (TRILL) device port in an edge virtual bridging (EVB) network environment. One embodiment includes sending, by a virtual machine (VM) in an EVB network, a message to a device that implements TRILL protocol. The device communicates with a table using the message. Network information is obtained from the table by the device. A port for the device is automatically configured based on the network information. The device has the TRILL protocol either enabled or disabled.

Abstract: A method and system are shown for identifying the most influential members of a social network. The social networking system receives a request to rank a plurality of members of a social networking system based on the influence held by each of the plurality of members. For a respective member in the plurality of members of the social networking system, the social networking system analyzes member interactions of the respective member on the social networking system and generates an influencer score for the respective member based on the analysis of member interactions through the social networking system. The social networking system orders two or more members in the plurality of members of the social networking system based on the influencer scores associated with the two or more members.

Abstract: In an example embodiment, information about one or more Customer Relationship Management (CRM) entities is received from a CRM system, the information including an identification of each of the one or more CRM entities and usage information about how a user interacted with each of the one or more CRM entities. Then, at a software tool distinct from the CRM system, one or more actionable insights related to the one or more CRM entities are identified. The relevance of the one or more actionable insights to the user is then determined based on the usage information. One or more of the one or more actionable insights are then presented to the user based on the determined relevance via the software tool.