152 results about "Knowledge element" patented technology

A virtual assistant learning system is presented. A monitoring device, a cell phone for example, observes user interactions with an environment by acquiring sensor data. The monitoring device uses the sensor data to identify the interactions, which in turn is provided to an inference engine. The inference engine leverages the interaction data and previously stored knowledge elements about the user to determine if the interaction exhibits one or more user preferences. The inference engine can use the preferences and interactions to construct queries targeting search engines to seek out possible future interactions that might be of interest to the user.

An interactive computer-implemented apparatus and method for capturing and monitoring performance in a call center, and for promoting competition in productivity and quality metrics among employees comprising: a relational database, for use by all employees in the call center, comprising a competencies module defining competency requirements for each job in the call center, an individual employee development plan module linked to the competencies module a performance appraisal module for automatically calculating an overall performance rating for each employee, and a query and reporting facility, a database of employee demographic information, functional knowledge database comprising pre-defined employee functional knowledge elements required across all job codes of the call center organization; a competencies database comprising the organization's pre-defined employee competencies, the competencies linked to strategic goals of the call center organization, each competency assigned one or more proficiency levels, each proficiency level comprising one or pre-defined milestones, each job code assigned a targeted competency proficiency level; a development plan database for capture of employee-inputted development goals for one or more competencies, development goals selected from milestones per the competencies database, the selected development goals reviewed by a supervisor; a performance appraisal database for capture of the employee's supervisor-inputted performance ratings for a specified period, the performance ratings comprising distinct components of quality, productivity, and behavior, the behavior component further comprising a development rating, the development rating based on the employee's attainment of one or more employee's development goals per the development plan database, the rating for each component assigned a weight, the weight being a percentage of the maximum merit increase rate, the overall performance rating being the sum of the performance ratings for each component, the overall performance rating used to calculate the employee's merit increase, a periodic performance review database for capture of supervisor-inputted information from periodic performance reviews held with an employee, and a reports facility comprising instructions enabling administrators, employees, and supervisors to query one or more databases, the reports facility generating viewable and printable reports on-demand.

The invention discloses a personalized network learning resource recommendation method which comprises the following steps: analyzing behavioral data of learners for visiting a network leaning system based on expanded theme pictures, acquiring leaning interest path changing patterns of the learners and groups of the learners on concepts and knowledge elements related to learning contents, and then realizing active personalized recommendation of proper learning resources to the learners according learning interest path changing patterns of the learner individuals and the groups of the learners individuals, sequence of learning objects of the expanded theme pictures and the like. The personalized network learning resource recommendation method can provide personalized learning service for network learners, thereby improving learning efficiency of the network learners.

The invention discloses a data mining method based on extraction of Web numerical value tables. The method is based on domain knowledge base, adopts generation of numerical value knowledge element base as a basic target, and mainly comprises construction of domain knowledge base basic set, positioning of Web numerical value tables, recognition of table structure, integration of table content, semantic representation of extract result, data retrieval, automatic learning of domain knowledge and data mining processing and the like. The invention is based on the method of extraction of Web numerical value tables in specific domain, can carry out extraction to data, information and knowledge included in numerical value tables in Web pages, converts semi-structured data into structured data and provides services of data retrieval, data mining analysis and the like. The data mining method can completely and accurately extract valuable numerical value knowledge in large amount of Web numerical tables dispersed on Web and meets the requirements of data query and data analysis of a user.

The invention relates to a structured report template-based medical image knowledge base establishment method and belongs to the field of medical information processing and application. For improving data availability, a multi-modal stored medical image is converted into structured big data, so that data innovation and value addition are realized and accurate data support is provided for medical research. The method comprises the steps of establishing characteristic noumena of the medical image; defining standards of disease syndromes; designing report templates by taking structured data as elements; forming knowledge elements and exchanging information; and establishing learning rules. Through noumenon library establishment, disease syndrome definition, a text report template, an image-text report template and a CDA document, a relationship between a diagnosis conclusion and image presentation is established, so that the retrieval efficiency is high and the accuracy is greatly enhanced; by establishing the learning rules, the knowledge elements are continuously perfected, so that the medical research is assisted and the medical image level of the whole industry is improved; and the method has extremely wide application values.

Knowledge automation techniques may include selecting a knowledge element from a knowledge corpus of an enterprise for extraction of n-grams, and deriving a term vector comprising terms in the knowledge element. Based at least on a frequency of occurrence of each term in the knowledge element, key terms are identified in the term vector. Thereafter, the identified key terms are used to extract one or more n-grams from the knowledge element. Each of the extracted n-grams is scored as a function of at least a frequency of occurrence of each of the n-grams across the knowledge corpus of the enterprise, and based on the scoring, one or more of the n-grams is added to a collective term and phrase index.

The invention provides a knowledge graph construction method and system. The method comprises the following steps: acquiring corpus information of at least one domain of a to-be-constructed knowledgegraph; carrying out word segmentation and part-of-speech tagging on knowledge text content fragments included in the corpus information to obtain the key words in the knowledge text content fragments;matching the key words with the domain ontology according to the preset rules to obtain the knowledge element instances in the knowledge text content fragments, the attributes of the knowledge element instances and the association relation between the knowledge element instances, wherein the domain ontology includes a domain topic, at least one model included in the domain topic, attributes of the model, and associations between the models, and the model includes at least one knowledge element instance; and constructing the knowledge graph according to the knowledge element instances in the plurality of knowledge text content fragments, the attributes of the knowledge element instances and the association relation between the knowledge element instances. The automatic construction of theknowledge graph is realized, the construction cost of the knowledge graph is reduced, and the construction efficiency and accuracy of the knowledge graph are improved.

Knowledge automation techniques may include generating, for each user of a plurality of users, a user vector associated with the user, and grouping the generated user vectors into clusters based on a clustering distance metric between the user vectors. For each cluster, the techniques may include determining a centroid of the cluster, and associating with the cluster at least some of the knowledge elements that the users associated with the cluster has interacted with. The techniques may further include comparing a target user vector of a target user with the centroids of the clusters to determine a matching cluster for the target user, and providing one or more recommendations of the knowledge elements that are associated with the matching cluster to the target user.

The invention discloses a method for constructing a core symptom-differentiation relation based on a traditional Chinese medicine knowledge graph. The method comprises the steps of mining and extracting a case set formed of four diagnostic methods information and differentiation factor knowledge elements of medical records of traditional Chinese medicine and auxiliary knowledge elements such as a theory, a rule, a prescription and a drug from literature of traditional Chinese medicine and a disease diagnosis database, establishing a sample relation for each case corresponding to the four diagnostic methods information and differentiation factors through a deep learner; then converting the sample relation into a directed-weighted complex network; abstracting a knowledge element inference relation included by the sample corresponding to each symptom into a directed edge set; and outputting a visual topological graph in a manner of a knowledge map and a knowledge inference network. According to the method, effective information carried by traditional Chinese medicine cases can be fully utilized, feature extraction and self-learning is realized to the maximum extent by use of a deep neural network, the construction of the visual topological graph for the traditional Chinese medicine symptoms and differentiation factors greatly improves the finding efficiency of potential knowledge and lays a foundation for intelligent diagnostic aid decision making of traditional Chinese medicine and recommendation of medicare guiding service.

A cognitive information processing system comprising a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for: receiving data from a plurality of data sources, the plurality of data sources comprising a blockchain data source, the blockchain data source providing blockchain data; processing the blockchain data to generate a plurality of knowledge elements; processing the blockchain data to generate cognitive blockchain data; storing the plurality of knowledge elements and the cognitive blockchain data within a cognitive graph; and, processing the plurality of knowledge elements to generate a cognitive insight associated with a compliance requirement.

The invention discloses a construction method for a traditional Chinese medicine knowledge map and relates to the fields of medical big data and knowledge map technologies. Through the method, the problems that existing traditional Chinese medicine knowledge map technologies are inconsistent in evaluation standard, and obtained conclusions have redundancy or cannot be interpreted with traditional compatibility theories are solved. According to the method, knowledge elements and a sample relation are mined and extracted from traditional Chinese medicine literature and texts, the knowledge elements and the sample relation are converted into a directed network vector model through a deep learning machine, a directed/undirected network of the relation is made to visually display a knowledge map model, and then visual output is performed by means of the knowledge map and a knowledge reasoning network. On the basis of an existing map construction method, the deep learning technology is fused, coordinate mapping is performed on each knowledge element, distance information is fully utilized, relevancy between the knowledge elements is reflected, and the method has remarkable superiority in terms of association study of common medicine on semantic retrieval, visual traditional Chinese medicine community discovery, single medicine and basic prescriptions.

The invention discloses an automatic generation method and system based on personalized learning process of mapping knowledge domains. The method includes: on the basis of personalized mapping knowledge domains described by a directed hypergraph, utilizing a relation between knowledge elements and learning activities, and automatically generating corresponding learning process frames according to personalized characteristics like learning performance targets, learning capability, learning habits and learning modes of learners; on the frames, automatically generating all possible supporting resources of activities according to characteristics of the learners, the knowledge elements learned by the activities and activity type; utilizing relation among learning resources, the learners and learning activity attributes, relation between the activity attributes and process attributes and the personalized objects of the learners for optimization of process structure and learning resources to generate optimized learning process. By the method, huge personalized learning process can be generated automatically; the method is used for optimizing the learning process structure and the learning resources according to specific conditions of the learners, and learning is analyzed and optimized globally. In addition, the automatic generation method and system is a foundation for formulating further personalized learning schemes.

A system comprising: a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus. The computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for: receiving data a data source, the data comprising a query and information relating to an answer to the query; processing the query, the processing the query identifying a plurality of query related knowledge elements; processing the information relating to the answer to the query, the processing the information relating to the answer to the query identifying a plurality of answer related knowledge elements; and, storing the plurality of query related knowledge elements and the plurality of answer related knowledge elements within the cognitive graph as a collection of knowledge elements.

A system comprising: a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus. The computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for: receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching to provide data enriched data streams; and, storing the data streams and the data enriched data streams within the universal knowledge repository as a collection of knowledge elements.

The invention relates to an emergency decision-making method of an emergency based on scenario analysis. The purpose of the invention is to solve the problem that the existing emergency response mechanism is unreasonable, Emergency management personnel directly relying on experience or using artificial neural network to carry out emergency decision-making methods cannot shorten the response time,which is not in line with the actual situation, resulting in low efficiency and low accuracy of emergency management. A method for emergency decision-making based on scenario analysis includes the following steps: step 1, constructing a basic scenario database; step 2, extracting feature element knowledge elements of that target scenario from the target scenario, input the feature element knowledge elements of the target scenario into a basic scenario database for searching and matching, and obtaining a corresponding emergency decision scheme; The invention belongs to the field of emergency traffic management.

A framework for supporting transition of one or more applications of an organization is provided. The one or more applications are transitioned from a first set of users to a second set of users. The framework includes a transition module, a knowledge capture module, a knowledge validation module, and a collaboration module. The transition module generates one or more transition plans based on information corresponding to the one or more applications. The knowledge capture module captures a plurality of knowledge elements corresponding to the one or more applications. The knowledge capture module further establishes association between the plurality of knowledge elements. The knowledge validation module validates the plurality of knowledge elements and their association. The collaboration module provides collaboration between the first set of users and the second set of users during the transition of the one or more applications.

The invention discloses a knowledge question-answer system established on basis of a Wiki semantic network, and an intelligent retrieval method and relates to the technical fields such as text semantic analysis, intelligent retrieval and machine learning. According to the invention, semi-structuralized text data grasped by vertical field Wiki in an oriented manner is used; knowledge elements are extracted automatically according to a pre-defined knowledge ontology; further, a deep learning algorithm can be used to train and establish an ontology semantic comprehension model; and thus, semantic comprehension of clustering relations and inference relations of the knowledge elements could be achieved. According to the invention, advantages of machine learning including automatic theme inference based on context semantic understanding and expert knowledge oriented optimization are synthesized; matched retrieval results matched through rational semantic association and expansion as well as inferred retrieval results are returned to a retrieval word input by a user; and in combination with definition of expert knowledge, accuracy and depth of the information retrieval can be increased effectively, and knowledge navigation can be achieved. The system and method are applicable to a medical-themed mapping knowledge domain, knowledge questioning and answering and a content recommendation system.

The invention discloses a knowledge map oriented network learning behavior and efficiency analysis method. According to the method, the difference between the traditional courseware oriented network learning and knowledge map oriented network learning is comparatively analyzed from the aspects of teaching resource organization, teaching activity design, user learning behavior characteristics and the like, and indexes, namely a knowledge element coverage rate F and effective click time length T calculation method, for embodying learning behaviors of learners in a knowledge map mode are given; analysis is carried out by combining the time length characteristic that users submit homework online on a network learning platform, a k-means clustering algorithm is adopted, and the learners are divided into three types, namely an active type, a general type and a dilatory type. The method has the advantages that network learning behavior characteristic extraction in a knowledge map oriented learning mode and the quantitative analysis of a relationship between a network learning behavior mode and learning efficiency are achieved, and basis and foundation for the personalized recommendation of network learning resources can be provided.

A computer system maintains a biological data structure having molecular feature data. The system receives data elements indicating biological molecular features and knowledge elements that represent biological concepts. The system individually associates unique identifiers with the elements. For individual elements, the system maintains an internal element set of the other unique identifiers for the other elements that are directly associated with that one individual element. For the individual elements, the system maintains an external element set of the other unique identifiers for the other elements that have that one individual element in their own internal element sets. Although not required, the computer system may process a query indicating a search scope and a molecular feature for an individual biological entity, and responsively process the molecular feature and the elements based on the search scope to induce a knowledge sub-graph for the individual biological entity.

An apparatus categorizes knowledge elements that an investigator derives from source materials into issue categories. The issue categories may be predefined based on the type or nature of the investigative matter or user-defined as circumstances dictate. The apparatus also allows for preparation of a narrative based on the knowledge elements and source materials. A hopper allows a user to view and access the categorized knowledge elements during preparation of the narrative. Accordingly, through this collaboration process, investigators may produce a narrative more accurately and efficiently. Further, the apparatus links the text in the narrative back to the knowledge elements and the source materials which may be easily accessed via the links to enable them to be reviewed to determine whether the relevant text in the narrative is firmly based thereon. Thus, review of the work product created with the apparatus may be simplified.

The invention discloses a questioning and answering method and device based on an atlas knowledge base, equipment and a storage medium. According to the method, voice detection is carried out; when the questioning voice of the user is detected; voice recognition is carried out on the questioning voice; obtaining questioning text information, artificial intelligence, performing element recognitionon the question text information through a preset element recognition model, obtaining questioning elements corresponding to the questioning text information, obtaining knowledge elements of a plurality of storage problems in a preset mapping knowledge base, and matching the questioning elements of the questioning text information with the knowledge elements of the storage questions, if matching succeeds, displaying answers corresponding to the successfully matched storage questions, and based on element matching, improving the accuracy of question matching, thereby improving the accuracy andefficiency of intelligent questioning and answering.

The present invention relates to a technical innovation process management method based on knowledge grid, belonging to the field of knowledge management (KM). Said method includes the following steps: firstly, analyzing enterprise information and extracting knowledge element, knowledge chain and knowledge point from said enterprise information, storing said knowledge element, knowledge chain and knowledge point into a knowledge base; utilizing grid technique, using knowledge chain as 'net wire', using knowledge element main body as 'net point' and making them be connected together, using knowledge point as 'entrance' of said grid; then combining the knowledge element, knowledge chain and knowledge point with 'network' mode so as to make technical innovation work.

The invention provides a fire emergency disposal process management method and system in a subway station. The method comprises the steps that the disposal measure primitive elements of subway station fire emergency are built, and the disposal measure primitive elements are used to generate a subway station fire emergency disposal process; the mapping relationship between the attributes of the disposal measure primitive elements and the elements of a random Petri net is established, and the logical relationship among the disposal measure primitive elements is transformed into the random Petri net; and the SPN model of the subway station fire emergency disposal process is established by using the mapping relationship and the random Petri net. According to the invention, the ideas of system decoupling and coupling and analogy reasoning are used to introduce knowledge elements, Petri net modeling and a random process theory into the generation and optimization of the subway station fire emergency disposal process; and the method and system relate to the construction of a subway station fire emergency scene, emergency disposal measure decoupling and emergency disposal link coupling, and can provide an important theoretical support for optimizing fire emergency disposal in different regions of the subway station.

The invention relates to the field of graph theory and network analysis techniques, and in particular to a shortest path query method, system, computer device and storage medium. The shortest path query method includes acquiring fund knowledge in information source and establishing fund knowledge element database; performing fusion of fund knowledge and storage in databases; the shortest paths between all entities in the whole graph and each sub-graph are calculated periodically and the shortest path matrix is established; acquiring query requests and searching corresponding results from a shortest path matrix; when there is no corresponding result in the shortest path matrix, the corresponding sub-graph is selected from the fund knowledge element database; calculating the shortest path for a particular pair of entities in the subgraph. Through the establishment and maintenance of the whole map and sub-map, the functions of real-time query and total query are realized. Through the further calculation of the path between entities in the map, it provides a basis for the further reasoning of the relationship between entities in the map.