Abstract: The present invention relates to an online search method and device that accounts for relevance and difference, wherein the method comprises: determining an initial search result set according to a query request input by a user, and selecting a plurality of search results with the greatest degrees of difference from the initial search result set, as a final search result set. The specific process comprises: initially obtaining a plurality of candidate results according to the query request submitted by the user; using a semantic matrix to describe the attribute characteristics of documents corresponding to the candidate results; calculating similarities among the documents according to the attribute characteristics of the documents, and then clustering the candidate results into a plurality of cluster blocks; selecting a representative from each cluster block; and constructing the final search result set according to the selected representatives.

Abstract: Provided are a HEK293T cell strain having high dispersibility and a screening method therefor. Specifically, the present application relates to a method for screening a HEK293T cell strain suitable for serum-free suspension culture, a cell strain screened by using the method, and a method for producing a viral vector by using the cell strain.

Abstract: The present invention relates to a trustworthy search method for a search engine based on a knowledge graph, which includes: acquiring a search keyword input by a user to construct a keyword pool; selecting a keyword according to a keyword selection policy, and respectively inputting the keyword to a search engine in sequence for searching to obtain a result returned by the search engine; constructing a knowledge graph of a Web page in sequence; selecting a specific knowledge mode; matching the knowledge graph with an existing semantics reliable knowledge graph library, and then computing a content support degree of each Web page according to a matching result; sorting the search engine under the same keyword by using a content support degree expectation of the Web page; and completing trustworthy search of the search engine based on the knowledge graph.

Abstract: The present invention relates to a place change driven software update method and apparatus, and a readable storage medium. The method includes: modeling a software architecture SA and an evolution rule set L?R through Bigraph; acquiring a software architecture SAt after movement and before evolution of the SA; computing a place ?P that changes between the SA and the SAt, thereby acquiring a corresponding evolution rule Lj?Rj; and cutting a matching subgraph GL on a link graph SAL and replacing with a link graph RjL to obtain a new SA link graph SAL,e; and merging the new SA place graph and the new SA link graph, thereby implementing update of the software architecture. Compared with the prior art, the present invention may describe place change information and system change information at the same time, and avoid the complexity, risk, unreliability and the like of conversion between different models.

Abstract: The invention relates to a graph clustering method based on perception application algorithm semantics and a computer readable medium. The graph clustering method includes: acquiring original graph data G and a graph’s application algorithm A; initializing a subgraph Gi; randomly selecting a vertex v and a corresponding connecting edge thereof from the graph G, and deleting the v and the corresponding edge thereof from the graph G; computing a semantic serial degree after adding the vertex v into the subgraph Gi; determining a clustering block with the maximum semantic serial degree, and adding the vertex v and the corresponding connecting edge into the subgraph; repeating the steps until the graph G is empty; and completing graph clustering, and outputting a clustering result. Compared with the prior art, the method provided by the invention has the advantages of being able to greatly accelerate application analysis and mining of big graph data.

Abstract: The present invention relates to an online search method and device that accounts for relevance and difference, wherein the method comprises: determining an initial search result set according to a query request input by a user, and selecting a plurality of search results with the greatest degrees of difference from the initial search result set, as a final search result set. The specific process comprises: initially obtaining a plurality of candidate results according to the query request submitted by the user; using a semantic matrix to describe the attribute characteristics of documents corresponding to the candidate results; calculating similarities among the documents according to the attribute characteristics of the documents, and then clustering the candidate results into a plurality of cluster blocks; selecting a representative from each cluster block; and constructing the final search result set according to the selected representatives.

Abstract: The present invention relates to a place change driven software update method and apparatus, and a readable storage medium. The method includes: modeling a software architecture SA and an evolution rule set L?R through Bigraph; acquiring a software architecture SAt after movement and before evolution of the SA; computing a place ?P that changes between the SA and the SAt, thereby acquiring a corresponding evolution rule Lj?Rj; and cutting a matching subgraph GL on a link graph SAL and replacing with a link graph RjL to obtain a new SA link graph SAL,e; and merging the new SA place graph and the new SA link graph, thereby implementing update of the software architecture. Compared with the prior art, the present invention may describe place change information and system change information at the same time, and avoid the complexity, risk, unreliability and the like of conversion between different models.

Abstract: The present invention relates to a trustworthy search method for a search engine based on a knowledge graph, which includes: acquiring a search keyword input by a user to construct a keyword pool; selecting a keyword according to a keyword selection policy, and respectively inputting the keyword to a search engine in sequence for searching to obtain a result returned by the search engine; constructing a knowledge graph of a Web page in sequence; selecting a specific knowledge mode; matching the knowledge graph with an existing semantics reliable knowledge graph library, and then computing a content support degree of each Web page according to a matching result; sorting the search engine under the same keyword by using a content support degree expectation of the Web page; and completing trustworthy search of the search engine based on the knowledge graph.