Abstract: Methods, systems, computer program products for determining the source of activity during interaction with a user interface are provided. The method comprises selecting one or more input devices from a plurality of available input devices coupled to the user interface and receiving respective measurements for the selected one or more input devices. Based on the received respective measurements, respective feature vectors for the one or more input devices are generated and then inputted to a pre-defined regression model. Then, the source of activity is determined based on a result received from the regression model.

Abstract: Provided is a method, computer program product, and system for classifying a set of data items based on format organizations. A processor may determine at least one format organization of a set of data items. The format organization of a data item indicates a symbol type of at least one continuous symbol in the data item and a number of the at least one continuous symbol. The processor may determine at least one candidate data class for the set of data items from a plurality of predetermined data classes based on the at least one format organization. The processor may classify the set of data items into at least one target data class selected from the at least one candidate data class. In this way, the set of data items can be efficiently classified.

Abstract: A computer-implemented method includes: reading a vector of a first table in a database, the vector including counts of a plurality of keywords in the first table, the plurality of keywords including a first keyword and a second keyword; determining a first custom attribute describing the first table, the first custom attribute having a vector including counts of at least a first portion of the plurality of keywords in the first table; determining a multiplier of the first custom attribute, the multiplier being a number of other tables that reference the first custom attribute; and revising the vector of the first table based on the first custom attribute.

Abstract: Managing multiple chain transaction rollback on a native cloud environment in a Kubernetes distributed system which extends API capabilities to build compensate API mappings which are used to reverse the invocation chain and stores the mappings in a key value store. An embodiment of the present invention extracts the reverse invocation chain from a framework of libraries and mapping API to check whether rollback is necessary when a service fails. An embodiment of the present invention executes an entire whole rollback.

Abstract: Provided is a method, computer program product, and system for classifying a set of data items based on format organizations. A processor may determine at least one format organization of a set of data items. The format organization of a data item indicates a symbol type of at least one continuous symbol in the data item and a number of the at least one continuous symbol. The processor may determine at least one candidate data class for the set of data items from a plurality of predetermined data classes based on the at least one format organization. The processor may classify the set of data items into at least one target data class selected from the at least one candidate data class. In this way, the set of data items can be efficiently classified.

Abstract: Managing multiple chain transaction rollback on a native cloud environment in a Kubernetes distributed system which extends API capabilities to build compensate API mappings which are used to reverse the invocation chain and stores the mappings in a key value store. An embodiment of the present invention extracts the reverse invocation chain from a framework of libraries and mapping API to check whether rollback is necessary when a service fails. An embodiment of the present invention executes an entire whole rollback.

Abstract: A computer-implemented method includes: reading a vector of a first table in a database, the vector including counts of a plurality of keywords in the first table, the plurality of keywords including a first keyword and a second keyword; determining a first custom attribute describing the first table, the first custom attribute having a vector including counts of at least a first portion of the plurality of keywords in the first table; determining a multiplier of the first custom attribute, the multiplier being a number of other tables that reference the first custom attribute; and revising the vector of the first table based on the first custom attribute.

Abstract: Methods, systems, computer program products for determining the source of activity during interaction with a user interface are provided. The method comprises selecting one or more input devices from a plurality of available input devices coupled to the user interface and receiving respective measurements for the selected one or more input devices. Based on the received respective measurements, respective feature vectors for the one or more input devices are generated and then inputted to a pre-defined regression model.