Abstract: The present disclosure provides a method and apparatus for update processing of a question answering system, relates to the technical field of artificial intelligence and specifically to big data and natural language processing technologies. A specific implementation solution is: acquiring an updated question-answer set; comparing blocks of the updated question-answer set with blocks of an original question-answer set in terms of question-answer pairs to determine an unchanged block and a changed block; acquiring feature data of questions included in the changed block, and creating an index file corresponding to the block, and adding the feature data to an updated training output set; and retaining the index file and feature data corresponding to the unchanged block, and adding the feature data to the updated training output set. The present disclosure can reduce the time consumed in the updating process and occupation of resources.

Abstract: The present disclosure provides a text error-correcting method, apparatus, electronic device and readable storage medium and relates to the field of natural language processing and deep learning. In the present disclosure, an implementation solution employed when performing text error correction is: obtaining a text to be processed, and an error-correcting type of the text to be processed; selecting a target error-correcting model corresponding to the error-correcting type; processing the text to be processed using the target error-correcting model, and regarding a processing result as an error-correcting result of the text to be processed. The present disclosure can enhance the flexibility and accuracy of text error correction.

Abstract: Provided are a data storage method, a device, and a storage medium. The implementation scheme is as follows: target data to be stored is divided into data fragment original texts, and storage nodes are allocated for the data fragment original texts; in a trusted execution environment, the data fragment original texts are encrypted according to node information of the storage nodes to obtain data fragment cipher texts associated with the storage nodes; and the data fragment cipher texts are stored to the storage nodes.

Abstract: The present disclosure provides a method, apparatus, device and storage medium for training a dialogue understanding model, and relates to technical field of computers, and specifically to the technical field of artificial intelligence such as natural language processing and deep learning. The method for training a dialogue understanding model includes: obtaining dialogue understanding training data; performing joint training for a dialogue understanding pre-training task and a general pre-training task by using the dialogue understanding training data, to obtain a dialogue understanding model. According to the present disclosure, a model specially adapted for a dialogue understanding task may be obtained by training.

Abstract: A network convergence method and device, an electronic apparatus, a storage medium are provided. The method includes: taking online information obtained at least from network data as first nodes, and constructing a first network with the first nodes based on an association among the online information, the online information including at least one account and at least one piece of network media information; taking offline information obtained at least from mobile communication data as second nodes, and constructing a second network with the second nodes based on an association among the offline information, the offline information including at least one terminal identifier and location information of a terminal corresponding to the at least one terminal identifier; and converging the first network and the second network by using an association between the account in the online information and the terminal identifier in the offline information, to construct a heterogeneous network.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for commenting a video, and relate to the field of cloud computing. The method may include: acquiring content information of a to-be-processed video frame; constructing text description information based on the content information, the text description information being used to describe a content of the to-be-processed video frame; importing the text description information into a pre-trained text conversion model to obtain commentary text information corresponding to the text description information, the text conversion model being used to convert the text description information into the commentary text information; and converting the commentary text information into audio information.

Abstract: Embodiments of the present disclosure relate to a method and a device for writing data. The method may include: determining a target block for storing to-be-written data from a plurality of blocks divided in advance for a solid state disk in response to receiving a data write instruction, where the data write instruction includes information of the to-be-written data, and the solid state disk is divided into a plurality of blocks according to a band parameter; determining the to-be-written data based on the information of the to-be-written data; writing the to-be-written data into the target block using a single thread.

Abstract: The objective of the present invention is to provide a method, apparatus, computing node and computer program product for fault handling in a stream computing system. Here, at a computing node, recording arrival sequences of respective original data from a upstream computing node; performing persistence operation on the respective original data according to a predetermined period; in the case of failure and restart, restoring to-be-computed data in internal storage from the original data subjected to the persistent operation and/or the upstream computing node, and replaying and computing the restored to-be-computed data according to the respective previous arrival sequences; continuing encoding each completely computed result data according to offset of the result data in the last persistent operation period before the failure and transmitting the encoded result data to a next node.

Abstract: A method for obtaining an answer to a question is provided. The method may include: acquiring a question; determining at least a part of articles in a preset article database as candidate articles, and determining first scores of the candidate articles respectively, the first score of any of the candidate articles representing a matching degree between the candidate article and the question; determining at least a part of texts in each of the candidate articles as candidate texts, and determining second scores of the candidate texts respectively, the second score of any of the candidate texts representing a matching degree between the candidate text and the question; and determining at least a part of the candidate texts as the answer based on a score set of each of the candidate texts, the score set of any of the candidate texts including the second score and the first score.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for updating a digital certificate. A specific embodiment of the method includes: receiving digital certificate data, the digital certificate data including a number of times of forwarding and a first forwarding moment; determining whether the following conditions are satisfied: the number of times of the forwarding being less than a preset threshold, or a time length between a current moment and the first forwarding moment being less than a preset time length; and increasing, in response to determining at least one of the conditions being satisfied, the number of times of the forwarding by a preset number, and forwarding the digital certificate data to another proxy server.

Abstract: The disclosure provides a method and an apparatus for extracting content from a document, an electronic device, and a storage medium, which relates to the field of artificial intelligence (AI) technologies such as natural language processing (NLP), deep learning (DL), knowledge graph (KG). The detailed implementation scheme is: obtaining the document; performing anchor search on the document to obtain anchor information corresponding to the document; determining region information of content to be extracted based on the anchor information; and extracting the content to be extracted from the document based on the region information.

Abstract: A panorama rendering method, an electronic device and a storage medium are provided, and relates to the field of panoramic technology. The method includes: segmenting a panoramic picture to obtain segmented panoramic tile pictures; determining a target tile picture under a current screen and a target spherical patch in a panoramic picture sphere model, according to the panoramic picture sphere model and the segmented panoramic tile pictures; and performing drawing on the target spherical patch by using the target tile picture, to obtain a target scene. In this way, time consumption of panorama loading can be reduced and loading performance can be improved.

Abstract: The present disclosure provides a data processing method, apparatus, electronic device and readable storage medium and relates to the technical field of data processing and particularly to the technical field of big data. In the present disclosure, the data repetition judgment processing is performed on the raw data according to the address information of each object in the address information of at least two objects in the acquired raw data provided by the user, and then the POI information of the electronic map is obtained according to the data repetition judgment processing result of the data repetition judgment processing, so that the repeated data in the raw data can be output according to the POI information of the electronic map and the data repetition judgment processing result.

Abstract: Provided is a training method for a character generation model, and a character generation method, apparatus and device, which relates to the technical field of artificial intelligences, particularly, the technical field of computer vision and deep learning. The specific implementation schemes are: a source domain sample word and a target domain style word are input into the character generation model to obtain a target domain generation word; the target domain generation word and a target domain sample word are input into a pre-trained character classification model to calculate a feature loss of the character generation model; and a parameter of the character generation model is adjusted according to the feature loss.

Abstract: A method of data interaction, a data interaction apparatus, an electronic device and a non-transitory computer readable storage medium are provided, related to field of computer technologies, and in particular to the field of artificial intelligence technologies. When the method of data interaction is applied to the first data platform, the method includes: sending a data request to a second data platform based on a first resource server provided by a cloud or based on a local server; acquiring response data fed back by the second data platform based on a second resource server provided by the cloud; at least one of the first resource server and the second resource server is dynamically created by the cloud.

Abstract: A method for processing data includes: obtaining initial data; extracting data characteristics of the initial data; generating, based on the data characteristics, an initial memory consumption value required by a graphics processing unit (GPU) for processing the initial data; generating a recommendation processing parameter based on the initial memory consumption value; and obtaining target data by processing the initial data based on the recommendation processing parameter.

Abstract: The disclosure discloses a method for processing map data, a device, and a storage medium. The detailed implementing solution includes: determining POI data of bound points of interest (POI) of a road to be marked in response to obtaining a road marking instruction; selecting target POI data from the POI data of the bound POIs based on a scene where a user is located; and rendering a map interface based on road information of the road to be marked and the target POI data, and displaying the map interface rendered.

Abstract: Embodiments of the present disclosure provide a method and apparatus for optimizing a tag of a point of interest. The method includes: acquiring a set of points of interest and a set of tags of points of interest in the set of points of interest; generating a point of interest-tag matrix based on the set of points of interest and the set of tags of points of interest in the set of points of interest; extracting a feature of a point of interest-tag in the point of interest-tag matrix; inputting the feature of the point of interest-tag in the point of interest-tag matrix into a pre-trained ternary self-adaptive collaborative learning model, to obtain a point of interest-tag score matrix; and optimizing the set of tags of points of interest in the set of points of interest based on the point of interest-tag score matrix.

Abstract: The disclosure discloses a method and an apparatus for recognizing an entity word. The method includes: obtaining an entity word category and a document to be recognized; generating an entity word question based on the entity word category; segmenting the document to be recognized to generate a plurality of candidate sentences; inputting the entity word question and the plurality of candidate sentences into a question-answer model trained in advance to obtain an entity word recognizing result; and obtaining an entity word set corresponding to the entity word question based on the entity word recognizing result.

Abstract: A method for video frame interpolation, a related electronic device and a storage medium is disclosed. A video is obtained. An (i?1)th frame and an ith frame of the video are obtained. Visual semantic feature maps and depth maps of the (i?1)th frame and the ith frame are obtained. Frame interpolation information is obtained based on the visual semantic feature maps and the depth maps. An interpolated frame between the (i?1)th frame and the ith frame is generated based on the frame interpolation information and the (i?1)th frame and is inserted between the (i?1)th frame and the ith frame.