Abstract: The present invention relates to data processing technology and discloses a method for visualizing a personal resume, including: acquiring a personal resume information set, constructing an individual resume visualization graph based on an entity relationship of personal resume experience in the personal resume information set, performing person portrait modeling on different persons in the personal resume information set based on the individual resume visualization graph to obtain person portrait data, performing entity clustering on different persons in the personal resume information set based on the person portrait data, constructing an entity distribution visualization graph according to a clustering result, and constructing a person relationship visualization graph based on an entity relationship between different persons in the personal resume information set. The present invention also provides an apparatus, a device, and a computer-readable storage medium for visualizing a personal resume.

Abstract: The present invention relates to a data analysis technology and discloses a method for entity relationship recognition. The method for entity relationship recognition includes: performing sentence segmentation on a to-be-recognized text to obtain a statement text; performing entity recognition on the statement text, and screening all statement texts to obtain a target statement text; performing text fuzzing on the target statement text to obtain a to-be-recognized fuzzy text; acquiring all optional entity relationships and an example sentence text corresponding to each of the optional entity relationships, and likewise performing text fuzzing on the example sentence text to obtain a corresponding example sentence fuzzy text; and screening the example fuzzy text similar to the target statement text, and determining the optional entity relationship corresponding to the screened example sentence text as an entity relationship recognition result.

Abstract: The present disclosure discloses a method for identifying entity relationship pairs, including: acquiring a service text set, classifying service texts in the service text set based on text categories of the service texts to obtain a classified text set; performing entity identification and relationship identification on the classified texts in the classified text set to obtain an entity set and a relationship set; constructing a positive example sample set and a negative example sample set based on the entity set and the relationship set; and re-sampling the negative example sample set based on the positive example sample set to obtain a target entity relationship pair. The present disclosure also discloses an electronic device, an electronic apparatus, and a computer readable storage medium for identifying entity relationship pairs. The present disclosure can improve the accuracy of entity relationship identification.

Abstract: The present invention relates to artificial intelligence and discloses an entity relation mining method, including steps of acquiring enterprise text information, and extracting an enterprise relation instance in the enterprise text information; performing key entity extraction on the enterprise relation instance to obtain a key entity set; identifying an entity relation between key entities in the key entity set and a first relation weight corresponding to the entity relation, and performing weight calculation on the enterprise text information after deletion of the entity relation instance to obtain a second relation weight; and, using an entity relation having the first relation weight or the second relation weight satisfying a preset reference condition as a standard entity relation. The present invention further provides an entity relation mining apparatus, an electronic device and a storage medium. The present invention can improve the accuracy of entity relation mining.

Abstract: The present disclosure relates to an artificial intelligence technology, and discloses a method, an apparatus, a device, and a storage medium for clustering extraction of entity relationships. The method includes: capturing social relationship data of a user, performing entity recognition operation on the social relationship data to obtain an entity recognition result, and performing reverse marking operation on the social relationship data according to the entity recognition result to obtain a data marking sequence set; performing entity relationship recognition on various data marking sequences in the data marking sequence set to obtain a relationship recognition result, and constructing to obtain an entity-relationship group set; and calculating a character similarity between various entities and a semantic similarity between various entity relationships in the entity-relationship group set, and clustering various entity-relationship groups in the entity-relationship group set.

Abstract: Disclosed is a membership analyzing method, including: obtaining data information of all members of a target group; classifying members with same first type information into a data set based on predetermined keywords; obtaining the type of first type information and data sets on condition that all members have been successfully classified into a corresponding data set, otherwise, if there is any remaining member failed to be classified into any data set, inputting data information of the remaining member into a predetermined classification model, to obtain the type of first type information and a data set of each remaining member; determining a tree structure of data sets based on the type of the first type information, and producing a graph for the tree structure; setting a same identification for the nodes of the same data set, and displaying second type information of each member in a display area.

Abstract: Disclosed is an oral sustained-release composition for an insoluble drug, which is especially suitable for a low-dose insoluble drug, the oral sustained-release composition comprises a sustained-release granule part and a gel skeleton part, the sustained-release granule part comprises the insoluble drug, an enteric material, and a strong liquid sorbent, and the gel skeleton part comprises a hydrophilic gel skeleton material; and the sustained-release granules are obtained by preparing the insoluble drug and the enteric material into a suspension and then spraying the suspension onto the strong liquid sorbent, the sustained-release granules are wrapped by the gel skeleton to form a multiple sustained-release system technology, which prolongs a release time, and has a simple preparation process, high efficiency, uniform drug mixing, and less content loss.

Abstract: Disclosed is a membership analyzing method, including: obtaining data information of all members of a target group; classifying members with same first type information into a data set based on predetermined keywords; obtaining the type of first type information and data sets on condition that all members have been successfully classified into a corresponding data set, otherwise, if there is any remaining member failed to be classified into any data set, inputting data information of the remaining member into a predetermined classification model, to obtain the type of first type information and a data set of each remaining member; determining a tree structure of data sets based on the type of the first type information, and producing a graph for the tree structure; setting a same identification for the nodes of the same data set, and displaying second type information of each member in a display area.

Abstract: The present invention relates to a process for preparing a polyurethane foam by reacting a polyisocyanate with a polyol in the presence of a blow agent and a particular family of amine. The present invention also relates to a polyurethane foam thereof.

Abstract: A MOS transistor (60, 62) is provided. The structure of the transistor (60, 62) includes: a semiconductor substrate (10), a channel area (20, 24), source/drain regions (22, 26), a gate (30, 32), a gate insulating layer (11), a shallow trench isolation region (12), a passive layer (50, 52), and holes (40, 42) formed with a certain distance to the gate insulating layer (11). Wherein both the shapes of the holes (40, 42) and the Young's modulus' difference between the material in the holes (40, 42) and that around the holes (40, 42) contribute to the stress concentration effect, thus the stress in the channel area (20, 24) is enhanced. The structure of the transistor (60, 62) can greatly reduce the stress attenuation during the transmission from stress resource to the sensitive region, and concentrate the stress in the sensitive region. The structure can be involved in large size device, especially.