Abstract: A pipeline includes a pipeline body, a sealing member, and a sleeve. The pipeline body includes a connection end; the connection end includes a first section and a second section adjacent to the first section; and the first section includes an end face perpendicular to the axis of the pipeline body. The sealing member includes a first annular part and a second annular part; the first annular part and the second annular part are disposed coaxially; the second annular part includes a first surface oriented toward the first annular part; an axial projection of the first annular part falls within the first surface; the first surface includes a first region and a second region; the first region is enclosed by the axial projection of the first annular part, and the second region surrounds the axial projection of the first annular part.

Abstract: The present disclosure discloses a method and apparatus for processing a dataset. The method includes: obtaining a first text set meeting a preset similarity matching condition with a target text from multiple text blocks provided by a target user; obtaining a second text set from the first text set, in which each text in the second text set does not belong to a same text block as the target text; generating a negative sample set of the target text based on content of a candidate text block to which each text in the second text set belongs; generating a positive sample set of the target text based on content of a target text block to which the target text belongs; and generating a dataset of the target user based on the negative sample set and the positive sample set, and training a matching model based on the dataset.

Abstract: The present disclosure discloses a method and apparatus for processing a dataset. The method includes: obtaining a first text set meeting a preset similarity matching condition with a target text from multiple text blocks provided by a target user; obtaining a second text set from the first text set, in which each text in the second text set does not belong to a same text block as the target text; generating a negative sample set of the target text based on content of a candidate text block to which each text in the second text set belongs; generating a positive sample set of the target text based on content of a target text block to which the target text belongs; and generating a dataset of the target user based on the negative sample set and the positive sample set, and training a matching model based on the dataset.

Abstract: The disclosure provides a processing method and an apparatus of a neural network model, and relates to a field of computer technologies. The method includes: obtaining and converting input data of the ith processing layer into a plurality of capsule nodes; performing affine transformation on the plurality of the capsule nodes to generate a plurality of affine nodes; determining an initial activation input value according to the plurality of the affine nodes, and inputting the initial activation input value into an activation function to generate an initial activation output value; re-determining the initial activation input value according to an affine node corresponding to the initial activation output value, and inputting the re-determined initial activation input value into the activation function to regenerate the initial activation output value; repeating the acts for a preset number of times to determine the latest initial activation output value as an activation output value.

Abstract: A method and an apparatus are provided. The method may include: determining a service scenario based on a query sentence; entering the service scenario, and entering a first dialog node tree corresponding to the service scenario; storing, in response to determining that a common scenario needs to be entered based on a verification of a related parameter by the each parameter verification dialog node, the each parameter verification dialog node and jumping to the common scenario, and entering a second dialog node tree; collecting user information using the second dialog node tree, and in response to determining that the user information is collected successfully, determining whether a processing result of the second dialog node tree meets a backtracking condition; and returning to the service scenario based on the stored parameter verification dialog node and continuing to execute other dialog logic processing of the service scenario.

Abstract: A method, an apparatus, a device and a storage medium for intelligent response are provided. The method may include: acquiring a current to-be-responded sentence, and determining a current to-be-collected entity corresponding to an intention of the current to-be-responded sentence; acquiring, if a pre-set entity clarification condition is met according to the current to-be-responded sentence, an entity clarification sentence corresponding to the current to-be-collected entity, where the entity clarification sentence is used to clarify an entity value of the current to-be-collected entity; and outputting the entity clarification sentence as a reply sentence of the current to-be-responded sentence.

Abstract: The present invention provides a method and device for identifying URL legitimacy. Through obtaining a URL to be identified, and then obtaining, based on the URL to be identified, a legitimate URL corresponding to the URL to be identified as a comparison object, and calculating a degree of similarity between the URL to be identified and the comparison object, the present invention makes it possible to identify the legitimacy of the URL to be identified based on the degree of similarity, enabling timely discovering of illegitimate URLs and thus improving the safety of information processing.