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公开(公告)号：EP3848808A1
公开(公告)日：2021-07-14
申请号：EP19808665.4
申请日：2019-08-02
发明人： SHAO, Bingyang , FAN, Wei , SHEN, Changda , WU, Shaohua
IPC分类号： G06F11/14
摘要： A method and system for recovering deleted files based on a FAT32 file system is disclosed. A first root directory FDT information set is formed by reading FDT information of each directory entry R i ; FDT information of each directory entry Ri in the first root directory FDT information set F DT S = {R 1 , R 2 , ..., R N } is parsed to obtain attributes of the FDT information of a current directory entry R i , and whether each directory entry R i in the first root directory FDT information set represents a directory entry of a file or a directory entry of a folder is determined from the attributes; a starting sector number of the directory entry R i is calculate to obtain an actual physical position of the current file, and information of the current file directory entry R i is recursively parse out; and the FDT information of the directory entry R i of all directories in the current file system is parsed to obtain the actual physical position of the current file or folder and information of the directory entry R i . Fast recovery of the deleted file is effectively realized using a file feature-combined algorithm of dynamically calculating FDT cluster higher bits and a directory entry feature and information match-combined algorithm of dynamically calculating FDT cluster higher bits.
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公开(公告)号：EP4020253A1
公开(公告)日：2022-06-29
申请号：EP21209193.8
申请日：2021-11-19
发明人： Chen, Lou , Yehui, An , Fengnian, Wang , Lei, Zhang , Xinsheng, Du
IPC分类号： G06F16/25
摘要： Disclosed are a method and terminal of data model creation, which comprise receiving multiple types of data source for creating a data model, generating the corresponding wide table according to the data source and its type; generating a corresponding data model according to the wide table; processing the received multiple data sources in a configuration manner corresponding to the data sources, and generating the processed data sources into a corresponding wide table, generating a corresponding data model that needs to be displayed through the generated wide table. When the business changes, the business display can be updated by modifying the wide table of the data model. Interface reconfiguration and secondary development are not required for the update, which improves the large screen user experience.
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公开(公告)号：EP3798842A1
公开(公告)日：2021-03-31
申请号：EP19797973.5
申请日：2019-08-02
发明人： LIANG, Derong , SHEN, Changda , WU, Shaohua
IPC分类号： G06F11/14
摘要： The present disclosure provides a method, a system and computer storage medium for recovering deleted records of a database. The method includes steps of obtaining a slot pointer value; obtaining at least one deleted record according to the slot pointer value and the current offset address; parsing and recovering at least one deleted record. According to the method, system and computer storage medium of the present disclosure, deleted records could be recovered fast and completely based on the changes of the actual data after the deletion of records.
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4.发明公开
公开(公告)号：EP4024263A1
公开(公告)日：2022-07-06
申请号：EP21209157.3
申请日：2021-11-18
发明人： YUAN, Quan , WANG, Dian , GUO, Guifeng , QIAO, Sheng , FU, Jinzheng
IPC分类号： G06F40/247 , G06F40/284 , G06F40/30 , G06F16/35 , G06F16/36 , G06N5/02
摘要： The present application relates to a method of dynamic maintenance of a knowledge graph, a terminal device and a storage medium. The method comprises: S1: acquiring business data; S2: loading a thesaurus file, and extracting knowledge from the business data according to the thesaurus file; S3: converting the thesaurus into concepts in ontologies and relationships between concepts; S4: classifying the extracted knowledge into specific concepts in the thesaurus; S5: establishing new knowledge ontologies and relationships between knowledge ontologies according to the knowledge and concepts associated with the knowledge in the thesaurus; S6: merging new knowledge ontologies and relationships with existing knowledge ontologies and relationships; S7: updating the knowledge graph and the thesaurus according to the knowledge ontologies after merging; S8: for new business features, codes or non-formatted descriptions, extracting descriptors according to semantic analysis, extending the thesaurus constitution following the classification principle of the thesaurus, and then repeating step S2 ~ S7. The present application solves the problems of lag, inflexible expansion and low efficiency in a knowledge map update.
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公开(公告)号：EP3690700A1
公开(公告)日：2020-08-05
申请号：EP19797155.9
申请日：2019-08-02
发明人： NIE, Zhiqiao , YAN, Chenjia , LIN, Shuqiang , ZHANG, Yongguang , WU, Hongwei , ZHOU, Chengzu
IPC分类号： G06K20060101
摘要： The present disclosure provides a method for calculating image similarity, including S1: extracting feature points and corresponding feature vectors from a first image and a second image, respectively; S2: pairing all the feature points in the first image with all the feature points in the second image according to similarity by comparing first distances between the feature vectors in the first image and the feature vectors in the second image; S3: sorting the paired feature points according to the similarity from high to low, and selecting top N feature point pairs in the first image and the second image; S4: randomly selecting n reference points from the top N feature point pairs in the first image and the second image, and respectively calculating X-direction and Y-direction relative positions of remaining feature points in the first image or the second image with respect to the reference points; and S5: calculating an X-axis distance according to the X-direction relative positions of the remaining feature points in the first image and the second image with respect to the reference points, calculating a Y-axis distance according to the Y-direction relative positions of the remaining feature points in the first image and the second image with respect to the reference points, calculating the X-axis distance and the Y-axis distance and setting a threshold range to determine whether the first image and the second image are a same image. Detection errors resulting from mismatch of the feature points can be overcome.
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