Abstract: Computer implemented method for converting PDF documents into human readable and machine parsable HTML code. The method includes the use of a machine learning algorithm in order to automatically annotate the HTML code, said algorithm being trained with a set of manually annotated HTML code examples.

Abstract: A method, apparatus, device, and medium for processing a user task are provided. In one method, a user input represented in a natural language is received from a user. The user input indicates a task to be executed. A task type of the task is determined based on the user input. In response to determining that the task type indicates an execution result of the task is unable to be obtained within a predetermined time period, a subsequent task of the task is created to provide the execution result of the task by a machine learning model when a triggering condition for the task is met. With exemplary implementations of the present disclosure, user tasks that cannot obtain the execution result of the task within a predetermined time period can be processed in a more flexible and efficient manner.

Abstract: A resource management method applied to a computer system includes allocating first address space identifiers (ASIDs) from an ASID resource pool to processes run by a common core of the computer system; allocating a second ASID to a process of a critical service run by an isolated core of the computer system, and when the first ASIDs are exhausted, updating the first ASIDs in an ASID generation iteration manner, and refreshing a translation lookaside buffer (TLB) in the common core such that when the first ASIDs are exhausted, the second ASID allocated to the isolated core is not updated, and the TLB in the isolated core does not need to be refreshed.