16 results about "User knowledge" patented technology

This invention discloses an intelligent knowledge extraction system based on natural language processing, comprising: a text data acquisition module that acquires unstructured text and forms raw data; a text data preprocessing module that removes noise and standardizes the format of the raw data, outputting standardized text data; a text feature encoding module that converts the standardized text data into feature vectors that satisfy the input of an improved W2NER model; a knowledge extraction module that processes the feature vectors based on the improved W2NER model to obtain entity extraction results; an entity normalization module that performs ontology mapping and normalization on the entity extraction results; a knowledge fusion module that performs deduplication and fusion on the entity knowledge set; a knowledge storage module that stores the fused knowledge data in a structured manner; and a knowledge application service module that provides user knowledge query and reasoning services. This invention improves the accuracy of knowledge extraction and the efficiency of data application.

To facilitate the formation of a shared understanding among stakeholders with different areas of expertise, and to enable work efficiency and cost optimization through optimal evaluation tailored to the characteristics of each component. [Solution] The user interface provider unit 51 provides the user terminal 2 with a user interface having a function to select an operation mode according to multiple user knowledge levels, a function to acquire target building information, and a function to present output information. The classification unit 52 classifies the components of the target building according to their location and arrangement based on the target building information. The evaluation unit 53 compares the evaluations of multiple evaluation methods for each classified component and selects an evaluation result using an appropriate evaluation method based on the comparison results. The output control unit 55 generates output information indicating the selected evaluation result for each classified component and executes control to present it from the user interface.

A recommendation system and method based on an e-commerce coupon field knowledge graph, and relate to the technical fields of knowledge graphs and recommendations.The present application is to solve the problem that the existing business coupon recommendation method cannot recommend for new users, and has low reliability and accuracy.The present application comprises: constructing a knowledge graph corresponding to the current e-commerce platform user to obtain a knowledge graph library;obtaining current user information and determining whether the current user is a new user;obtaining the knowledge graph corresponding to the current user, using the knowledge graph corresponding to the current user to obtain a user-coupon list, and thus performing coupon recommendation information;obtaining the old user information input by the new user, and obtaining the knowledge graph corresponding to the old user in the knowledge graph library;using the knowledge graph corresponding to the old user and the scoring situation of the popular goods of the e-commerce platform for the new user to construct a new user knowledge graph, and then obtaining coupon recommendation information.The present application is used for recommending e-commerce coupons.

This invention discloses a method for digital creative content recommendation and user profile construction based on knowledge graphs, belonging to the field of data processing technology. The method includes first collecting multi-source heterogeneous user behavior data to construct a time-series sequence; then, after multimodal feature extraction, building an initial knowledge graph centered on the user, with interests as leaf nodes and timestamps as edge attributes; next, using a time-series graph neural network to achieve dynamic evolution of the graph, generating an evolving user knowledge graph; extracting explicit and implicit subgraphs from it and analyzing temporal changes in emotions, and fusing them to construct a multi-dimensional user profile; simultaneously, building a digital creative content knowledge graph containing multi-dimensional features; optimizing and filtering content for recommendation through multi-objective matching; and then pushing the content to the user after sorting by comprehensive score. This invention, by introducing a dynamic evolution mechanism and multi-objective optimization, achieves accurate capture of changes in user interests and multi-dimensional matching of creative content.

The application discloses a format contract generation method and system based on a knowledge base and a contract template, and relates to the technical field of format contract generation. The application aims to improve contract generation efficiency and solve the problem that users need to manually modify contract templates to meet specific contract requirements. The method comprises the following steps: obtaining user demand text, a user knowledge base and a contract template; analyzing the composition elements, format and blank position of the contract template to reconstruct a format template containing format information; retrieving associated information in the knowledge base based on the composition elements; combining the retrieved associated information, the format template and the demand text to form a prompt word, and submitting the prompt word to a large model; obtaining the text with format information returned by the large model, and analyzing and generating a contract with format. This process aims to constrain the large model output to meet the requirements of the contract template and generate a format contract carrying user knowledge. In this way, the efficiency and quality of contract generation can be effectively improved.

This invention discloses a service recommendation method and system based on knowledge graphs, belonging to the field of knowledge graph service recommendation technology. The method includes: responding to the cold start state of a target new user, acquiring basic attribute data and constructing an initial user knowledge graph; semantically expanding through intent anchor diffusion to mine potential user needs; inputting the expanded graph into a preset service recommendation model to generate a service demand subgraph, and aligning it with the service domain knowledge graph through topology-preserving joint subgraph embedding, calculating joint loss to obtain highly matched recommended services; and optimizing model parameters using an asymmetric update strategy based on real-time user feedback. This invention accurately characterizes and deeply mines the potential needs of new users through user knowledge graphs, effectively solving the problems of low recommendation accuracy and result generalization caused by data scarcity in traditional methods during cold start scenarios, significantly improving the recommendation success rate and user experience for new users.

The application relates to the technical field of computer information processing, in particular to a multi-modal video structured analysis and intelligent playing system and method based on a semantic time axis, aiming at the problems of insufficient video structured analysis capability, separation of playing and knowledge content, low processing efficiency and the like, a distributed asynchronous task architecture is constructed, audio and video preprocessing, speech recognition, time sequence semantic segmentation, subtitle generation and summary extraction are completed through a multi-modal analysis engine, and structured knowledge data accurately bound with a video time axis are generated. After automatic verification and manual review are completed through a quality control module, the structured knowledge base realizes associated storage of original videos and structured data and multi-dimensional index construction, and an intelligent interactive player realizes chapter navigation, subtitle synchronization and knowledge card linkage display in dependence on the semantic time axis. The application realizes standardized and structured conversion of unstructured videos, improves video processing efficiency and resource utilization, and reduces user knowledge acquisition cost.

The present invention relates to a user knowledge tracing method with more improved accuracy, and an operating method for a user knowledge tracing system including a plurality of encoder neural networks and a plurality of decoder neural networks includes: inputting exercise information to a k-th encoder neural network and inputting response information to a k-th decoder neural network; generating query data, which is information on an exercise for which a user is to predict a correct answer probability, by reflecting a weight to the response information and generating attention information to be used as a weight for the query data by reflecting the weight to the exercise information; and training the user knowledge tracing system by using the attention information as the weight for the query data.

The application relates to a method for implementing semantic chain retrieval enhancement generation processing for long document knowledge question answering, mainly including knowledge base construction and user knowledge question answering. The user knowledge question answering is based on the knowledge base construction, and the knowledge base construction involves long document preprocessing, semantic chain storage, information compression, knowledge extraction and storage. When the user performs knowledge question answering, fine-grained semantic coding is first performed into a retrieval vector, and then relevant document vectors and knowledge graphs are matched from the knowledge base through vector similarity calculation. If the document length exceeds the context scale of the model, static information compression after document information is indexed through information compression, and then it is evaluated whether dynamic compression is performed, and the document segment related to the task is returned through dynamic compression. Otherwise, the relevant original document is directly returned as the background knowledge of the generator. The model generator generates an answer based on the relevant document information / information after information compression, knowledge graph information, the user question and the model prompt.

A computer-implemented digital knowledge management system for institutional learning and decision support, comprising the following: A user interaction interface configured to receive structured institutional information from a variety of users connected to a university. This structured institutional information includes strategic issues, institutional goals, performance indicators, academic activity data, and decision-relevant input. an input processing unit that is operationally connected to the user interaction interface and is configured to capture, classify, and convert the received structured institutional information into machine-readable data sets; a collaborative culture assessment unit consisting of at least one processor and a memory in which executable instructions are stored, wherein the collaborative culture assessment unit is configured to collect and process organizational behavior data representing loyalty, engagement, cohesion, well-being and sense of community among members of the institutional leadership; a knowledge generation unit that is operationally linked to the collaborative culture assessment unit, wherein the knowledge generation unit is configured to analyze received knowledge records and generate new institutional knowledge by exploring alternative ideas, identifying new insights, and combining individual and collective institutional contributions; a knowledge exchange unit that is communicatively linked to the knowledge generation unit, wherein the knowledge exchange unit is configured to distribute the generated institutional knowledge to authorized users via controlled communication channels and structured knowledge dissemination procedures; a knowledge application unit designed to transform distributed institutional knowledge into decision support tools, including proposed strategic actions, operational recommendations, and measurable performance targets; an institutional learning repository consisting of a permanent digital storage system configured to store knowledge records, decision outcomes, institutional experiences, and insights gained from implemented decisions; a decision quality assessment processor that is operationally linked to the institutional learning repository and the knowledge application unit and is configured to evaluate generated decisions against predefined institutional criteria, including problem-solving effectiveness, strategic value contribution, achievement of institutional goals, and contribution to organizational learning; and a coordination processor configured to coordinate the operational interaction between the collaborative culture assessment unit, the knowledge generation unit, the knowledge sharing unit, the knowledge application unit, the institutional learning repository, and the decision quality assessment processor, such that the collaborative organizational conditions influence knowledge generation, knowledge distribution, knowledge utilization, and the subsequent evaluation of strategic decisions.

This invention provides a personalized search and recommendation method based on knowledge forests and user preferences, relating to the fields of recommendation knowledge representation and search technology. The method includes: collecting historical information from several users and constructing a knowledge pattern tree for each user according to their needs; using an entity relation extraction algorithm to extract entity relations from the user's historical information, and constructing a knowledge tree using the extracted entities and the knowledge pattern tree, and then constructing a knowledge forest using all users' knowledge trees; using graph embedding technology to assign weights to each knowledge tree in the knowledge forest, obtaining the final knowledge forest and saving it to a graph database; constructing a target user's knowledge tree according to the target user's needs, calculating the similarity between the target user's knowledge tree and each knowledge tree in the knowledge forest by calling the knowledge forest in the graph database, and generating a personalized recommendation list for the target user, thus improving the accuracy and efficiency of inference search.

This application provides a method and related equipment for generating a user knowledge graph. The method includes: acquiring user features, which include user data features, content data features, and background data features; and analyzing the user features to obtain a user knowledge graph. The technical solution of this application, by acquiring and integrating multi-dimensional user features such as user data features, content data features, and background data features, can obtain a richer and more comprehensive user knowledge graph that reflects the user's interests and needs. Analysis based on the user knowledge graph can more accurately describe the user's professional level and areas of genuine interest. Furthermore, since the user knowledge graph is obtained by acquiring user features, it can be updated in real time without user self-maintenance, ensuring that knowledge tags reflect the user's current situation.

Aspects of the subject disclosure may include, for example, registering one or more sensors in a database, receiving, from first respective sensors of the one or more sensors, data describing consumption of a first content item by a user in an environment, receiving, from second respective sensors of the one or more sensors, information about a creation, by the user, of a second content item, wherein the second content item is related to the first content item, and determining a predicted knowledge score based on the information about the creation by the user of the second content item. Other embodiments are disclosed.

Based on user knowledge, the system customizes specific tasks that users are asked to perform. [Solution] A program for operating a computer 20, which is equipped with a processor 29 and memories 25 and 26, causes the processor 29 to perform the following steps: a first step of acquiring knowledge information about the user; a second step of inputting at least a portion of the knowledge information acquired in the first step into a large-scale language model implemented on a different computer 40, and generating and acquiring a specific task from the large-scale language model to request the user to perform; a third step of presenting the specific task acquired in the second step to the user and obtaining the execution result of this specific task from the user; and a fourth step of associating the specific task acquired in the second step, the execution result of the specific task acquired in the third step, and the knowledge information input into the large-scale language model in the second step.

A server device (10-1) is an information processing device that provides a user with route guidance for traveling to a destination. The server device (10-1) utters a question related to a destination to the user at a timing different from the timing at which the destination was set, and on the basis of the response of the user to the uttered question, the server device (10-1) identifies a knowledge level indicating the degree of knowledge of the user as related to the destination, and provides destination-related information relating to the destination to the user on the basis of the identified knowledge level of the user.