184 results about "Relationship mining" patented technology

The invention discloses an entity relationship mining method based on biomedical literature, which comprises the following steps: (1) querying disease-related biomedical literature in a public database, and obtaining biomedical text data after data preprocessing; (2) performing biomedical named entity recognition on the obtained biomedical text data in combination with a regular matching templateand a deep learning model; and (3) based on the entity recognition result, mining the entity relationship by adopting transfer learning and reinforcement learning methods. The biomedical nouns entities in the literature can be effectively identified by acquiring the biomedical literature related to the disease from the network, extracting the abstract and the title and carrying out entity recognition and relationship mining, and the hidden relationship among various entities can be mined.

The invention relates to a relation searching device and a method thereof to search data of relations and events in time sequence of a number of texts with possibly spoken of relations in the form of news, blogs, industry reports, technical articles, and the like. According to the invention, the relation examples between entities of the number of texts from Internet and other media can be extracted automatically, and the time sequence relation, the degree of association between the entities and importance of the entities in each kind based on the extracted examples can be examined, and the important events can be extracted. Meanwhile, in the invention, to the company entities and commercial relations, the extracted time sequence relation can be calculated so as to acquire analysis of fivecompetitive forces of industries, moreover, the acquired result can be presented to the end users via visualization module.

The invention discloses a word relationship mining method and a word relationship mining device, which belong to the fields of computers and the Internet. The method comprises the following steps of: acquiring candidate relationships between two entries, the frequency of the candidate relationships and the word frequency of the entries; acquiring the statistic of mutual information and the statistic of a log likelihood ratio according to the candidate relationships, the frequency and the word frequency; acquiring a credibility normalization value according to the statistic of the mutual information and the statistic of the log likelihood ratio; and performing sequencing according to the credibility normalization value, and outputting the candidate relationships meeting a preset threshold as word relationships. The device comprises a first acquisition module, a second acquisition module, a third acquisition module and an output module. By the scheme provided by the embodiment of the invention, the accuracy of the mined word relationships is improved, and the user experiences are improved.

An enterprise relationship mining method belongs to the field of data mining, and comprises the following steps of defining the relationships , wherein the enterprise relationships comprise a legal person relationship, a shareholder relationship, a job relationship, a branch mechanism relationship, an external investment relationship and a competition relationship; acquiring the data, wherein theenterprise data comprises the business license information, the shareholder information, the employee information, the branch mechanism information and the business range labeling information; cleaning the data, checking the data consistency, and processing the invalid values and the missing values; multi-source data fusion, integrating all the information obtained by investigation and analysis, and performing unified evaluation on all the information; extracting the relationship. The enterprise relationship mining is a core for constructing an enterprise relationship graph, and the enterpriserelationship graph can display the enterprise relationships to the users in the form of structured graphs, so that the users can quickly understand and further explore the enterprise relationships. The enterprise social circles, the enterprise investment circles, the enterprise stock right structures, the enterprise actual controllers, the enterprise risk assessment and the like can be discoveredby mining the enterprise relations.

The invention discloses an information retrieval and potential relation mining method for bridge management and maintenance information, and the method comprises the steps: S1, defining sample data structure information which comprises sample data and the relation between the sample data; S2, constructing a bridge management and maintenance ontology knowledge base structure based on the sample data structure information, and importing the instance sample data into the bridge management and maintenance ontology knowledge base structure to generate a bridge management and maintenance ontology knowledge base; S3, establishing an inference rule based on the bridge management and maintenance ontology knowledge base; and S4, acquiring to-be-mined information, and retrieving the bridge managementand maintenance ontology knowledge base and / or generating potential relationship information between the to-be-mined information by utilizing a semantic logic reasoning machine based on the reasoningrule. According to the method, the reusability and interactivity of the BIM model on the bridge management and maintenance information are improved, and the intelligent management level of the bridgemanagement and maintenance field is greatly improved by adopting the semantic logic reasoning machine to explore the potential relationship information in the management and maintenance information.

The invention provides a high-resolution remote sensing image weak supervision building extraction method. The method comprises the steps of class activation image iterative optimization based on an iterative adversarial rising strategy, class activation image inter-pixel relation mining, class boundary detection, building pseudo label generation, semantic segmentation network training and building area extraction. Compared with an existing image-level weak supervision semantic segmentation method, the method has the advantages that an iterative adversarial rising strategy is used, a better building class activation graph can be generated, full mining of class activation graph information is achieved under the condition that extra supervision information is not introduced, and the class equivalence relation between pixels is obtained. Besides, the segmentation performance of the network on boundary processing is further improved by using a gated convolutional layer, so that an object region can be effectively expanded and covered in the boundary, and a high-quality building pseudo tag is generated, thereby enabling the semantic segmentation model to generate a building region with high accuracy and complete segmentation boundary.

The invention relates to a user relationship mining method and device, electronic equipment and a computer readable storage medium, relates to the technical field of big data analysis and mining. Theinvention can be applied to an application scene of analyzing user behaviors to complete user relationship mining. The user relationship mining method comprises the steps of obtaining user relationship data, and determining a user label of a to-be-processed user in the user relationship data; wherein the to-be-processed user comprises a target user and a neighbor user of the target user; obtainingthe maximum grouping number; performing label updating operation on the user label of the target user according to the maximum grouping number and the user label of the neighbor user so as to determine a result label of the target user; and determining a user group of the target user according to the result label. The user relationship can be analyzed through different dimensions, namely, coarse-grained analysis taking the community as the object and fine-grained analysis taking the user as the object.

The present invention discloses a non-limiting relationship mining method based on dependency syntax and a pattern rule. The method comprises the following steps: step one, performing word segmentation and part-of-speech tagging; step two, performing entity identification; step three, performing dependency syntax analysis; step four, performing entity relationship mining; and step five, obtaininga relationship mining comprehensive result. According to the method disclosed by the present invention, semantic information extraction of large-scale unstructured or semi-structured texts can be realized, automatic extraction of an entity relationship can be realized, entity relationship information can be effectively mined from a large number of texts, and business application value can be enhanced.

The invention provides a directory mapping relationship mining method. The method includes the following steps: taking a full-amount entry under single-class classification in an entry system as an entry to be mapped and taking annotation data and a synonym list as a mapping dictionary; respectively performing user directory name mapping and direction content mapping to determine a standard directory preliminarily corresponding to a user directory name; determining a standard directory finally mapped by the user directory name by means of empowerment voting. Correspondingly, the invention further provides a directory mapping relationship mining device. By directory mapping relationship mining, overall readability of the entry system can be effectively improved.