355 results about "Symbolic artificial intelligence" patented technology

The invention discloses a man-machine interaction method and system based on artificial intelligence. The method includes the following steps of receiving input information input by a user through an application terminal, obtaining the intent information of the user according to the input information of the user, distributing the input information to at least one interaction service subsystem according to the intent information, receiving the return result returned by the interaction service subsystems, generating a user return result according to the return result through a preset decision strategy, and providing the user return result to the user. By means of the method and system, the man-machine interaction system is virtualized instead of being instrumentalized, and the user can obtain the relaxed and pleasure interaction experience in the intelligent interaction process through chat, research and other service. The search in the form of keywords is improved into the search based on natural languages, the user can express demands through flexible and free natural languages, and the multi-round interaction process is closer to the interaction experience among humans.

This invention generally relates to a process, system and computer code for updating of computer applications based on collecting automation information related to a current application such as processing power, load, footprint, and performance attributes, determining a system automation profile; using an artificial intelligence based modeler for analyzing data, applying the data to an artificial intelligence model for training and predicting performance, adjusting the artificial intelligence model to achieve an updated automation criteria with optimal values, wherein the optimal values provide input to an automation criteria library for storing and updating a prior automation criteria, and exporting the upgraded automation criteria values for incorporation in a computer-to-be-updated, to achieve a reliable automatic update.

User authentication apparatus controlling access to systems, inputs owner's login name and password and then extracts the owner's timing vectors from keystroke characteristics with which the owner forms a training set. A semantic network uses multiple links to indicate that different pattern components of user's behavioral access create different kinds of relationships and “symbolic representations”. A neural network is trained by using each of the owner's timing vectors in the training set as an input. When a user inputs the owner's login name and password, it's checked and the user's timing vector is extracted to type the user's password if checked and demoted in confidence level if otherwise. The user's timing vector is applied to neural network and difference between the input / output is compared with a predetermined threshold; and if the difference is greater than the threshold, is prohibited. Preferably this is aided by response time to personal questions.

The invention provides an artificial intelligence-based object pushing method and apparatus. The method comprises the steps of inputting historical click behaviors of a target user to a built user model for performing learning to obtain multi-dimensional preference eigenvectors of a target user; obtaining eigenvectors of all to-be-pushed objects; inputting the eigenvectors of the to-be-pushed objects and the multi-dimensional preference eigenvectors to a trained deep neural network model for performing prediction to obtain prediction probabilities of the to-be-pushed objects; and pushing the to-be-pushed objects to the target user according to the obtained prediction probabilities. According to the method and the apparatus, the preferences of the target user are obtained through the user model built by a neural network, and the probability of possibly purchasing to-be-pushed group orders by the target user is obtained based on the deep neural network and the preferences of the target user, so that the pushing is more effective; and preference features are selected through training by the user model, so that a large amount of manpower does not need to be consumed for selection and the pushing efficiency is improved.

The invention belongs to the field of vehicle intelligence design, and in particular relates to a driving assistance system based on artificial intelligence. The system comprises a driving environment sensing unit and a wireless communication unit, wherein the driving environment sensing unit is used for identifying the ambient environment of a vehicle; the wire communication unit is used for communicating between the vehicle and surrounding vehicles and a server terminal; information acquired by the driving environment sensing unit and the wireless communication unit is output to an artificial intelligence unit for processing; and a driving assistance unit realizes the functions of vehicle speed adjustment, vehicle distance adjustment, lane change, overtaking and parking according to processed output control signals. The system can realize the functions of self-adaptive cruise control and automatic parking to relieve the driving fatigue of drivers, and can monitor the ambient environment of the vehicle to actively evade dangers so as to improve the driving safety.

A method includes obtaining an image of text. The text in the image includes one or more words in one or more sentences. The method also includes providing the image of the text as first input to a set of trained machine learning models, obtaining one or more final outputs from the set of trained machine learning models, and extracting, from the one or more final outputs, one or more predicted sentences from the text in the image. Each of the one or more predicted sentences includes a probable sequence of words.

A computer system for generating a diagnostic tool by applying artificial intelligence to an instrument for diagnosis of a disorder, such as autism. For autism, the instrument can be a caregiver-directed set of questions designed for an autism classification tool or an observation of the subject in a video, video conference, or in person and associated set of questions about behavior that are designed for use in a separate autism classification tool. The computer system can have one or more processors and memory to store one or more computer programs having instructions for generating a highly statistically accurate set of diagnostic items selected from the instrument, which are tested against a first test using a technique using artificial intelligence and a second test against an independent source. Also, a computer implemented method and a non-transitory computer-readable storage medium are disclosed.

The invention discloses a man-machine interaction method and system for online education based on artificial intelligence, and relates to the digitalized visual and acoustic technology in the field ofelectronic information. The system comprises a subsystem which can recognize the emotion of an audience and an intelligent session subsystem. Particularly, the two subsystems are combined with an online education system, thereby achieving the better presentation of the personalized teaching contents for the audience. The system starts from the improvement of the man-machine interaction vividnessof the online education. The emotion recognition subsystem judges the learning state of a user through the expression of the user when the user watches a video, and then the intelligent session subsystem carries out the machine Q&A interaction. The emotion recognition subsystem finally classifies the emotions of the audiences into seven types: angry, aversion, fear, sadness, surprise, neutrality,and happiness. The intelligent session subsystem will adjust the corresponding course content according to different emotions, and carry out the machine Q&A interaction, thereby achieving a purpose ofenabling the teacher-student interaction and feedback in the conventional class to be presented in an online mode, and enabling the online class to be more personalized.

An avatar having artificial intelligence for identifying and providing relationship or wellbeing recommendations is provided. The avatar acts as an electronic representation of a user. The avatar searches available information and makes recommendations to the user based on information received from the user or other sources regarding the user's relationship with another person or the user's wellbeing. In this way, the avatar continually learns more about the user to improve future recommendations to enhance the user's wellbeing and relationship with the other person.

The application discloses a man-machine interaction method and device based on artificial intelligence; the method comprises the following steps: forming multi-dimensional structured analysis results according to historical interaction information between a preset analysis strategy and a user and present multi-mode input information; using characteristic resources of a plurality of dialogue sources to obtain a plurality of results matched with the analysis results; determining the multi-mode output information matched with the multi-mode input information from the plurality of results according to a preset screening strategy, and pushing same to the user. The man-machine interaction method and device can improve dialogue content richness, thus satisfying user customized, interest and intellectual dialogue demands.

This invention relates to a knowledge question quick speed process system based on artificial intelligence including a user, a network station interaction system, a communication platform including an instant communication platform, a mobile communication platform and an E-mail platform, a knowledge library used in storing large numbers of knowledge data information, a user library used in storing user data information, an artificial intelligent server set between the network interaction system, the communication platform and the knowledge library, at least 4 engines: one for judgment, one for intelligent sort, one for searching for similar questions and one for summing up solutions and an information transmission engine set between the communication platform and the user library to be associated with the artificial intelligent server.

The invention discloses a searching method and device based on artificial intelligence and electronic equipment. The searching method based on the artificial intelligence comprises the steps of obtaining an input query sentence; segmenting the query sentence to obtain split word sentences composed of multiple split words; conducting structuralized analysis on the split word sentences to generate atext structure; based on the text structure, conducing knowledgeable analysis on the split word sentences to generate a semantic analysis result; according to the text structure and the semantic analysis result, determining an understanding result corresponding to the query sentence. By means of the searching method and device based on the artificial intelligence and the electronic equipment, byconducting structuralized analysis and knowledgeable analysis on the query sentence, the text structure and the semantic analysis result are obtained, thus the understanding result corresponding to the query sentence is determined, erroneous recalling of the searching result is lowered, the accuracy is improved, and the user requirements are met.

The invention discloses a method and a system used for searching for entities in the internet of things. The method comprises the steps of processing a query statement of a user and generating an unambiguous intermediate language; analyzing the intermediate language into a system internal query statement through a knowledge graph; constructing a knowledge tree in a self-learning or manual training mode through a construction method; and performing distributed query on the system internal query statement through servers and a sensing network through distributed query method and protocol. The system comprises a search service system for performing analysis and result feedback on user query, an artificial intelligence system for maintaining the knowledge graph and providing analysis, and a server cluster and a sensing network system for retrieving the entities according to the system internal query statement. Through the method and the system, the user can search for the entities in the internet of things by using a natural language; the abstractness and divergence of the knowledge graph ensure that a search target can be any describable objective entity or virtual object; and the sensing network system and the protocol described in the system split a search task level by level and perform delegation, so that the system has the characteristics of high concurrency and strong compatibility.

The embodiment of the invention discloses a searching method and device based on artificial intelligence. The method comprises the steps of obtaining at least one candidate document related to a searching sentence; determining a searching word vector sequence corresponding to a segmented word sequence of the searching sentence and determining a candidate document word vector sequence corresponding to the segmented word sequence of each candidate document in the at least one candidate document; executing the step of similarity calculation on each candidate document in the at least one candidate document; selecting a preset number of candidate documents as searching results from the at least one candidate document according to the sequence of the similarity with the searching sentence from large to small. According to the searching method and device based on the artificial intelligence, the candidate documents and the searching sentence are represented into a semantic vector through a neural network model, then according to similarities between a candidate document semantic vector and a searching sentence semantic vector, the candidate document is ranked, and the relevance of the searching results which are called back and the searching sentence input by a user is improved.

The invention discloses an active distribution network dynamic topology reconstitution method based on mixed artificial intelligence. Multiple improved artificial intelligence methods are adopted for optimizing solving, the superiority of various algorithms can be integrated, meanwhile the various artificial intelligence methods are improved during the process of combining various optimization algorithms, furthermore the astringency of the algorithms is improved, the defects such as locally optimal solution are avoided, three object functions are integrated in the optimization process, three different optimization objects are considered, and a corresponding Pareto optimal solution set is solved out; Since measurements of indexes such as on-off operation times and power supply volume are not constant, in order to establish a unified measurement model, all the indexes are converted into loss indexes according to respective conversion relations, and finally a dynamic analytic hierarchy process is adopted for deciding solutions in the Pareto optimal solution set, so that the optimal solution representing an optimal distribution network structure is obtained.

The invention provides a child user searching method and device based on artificial intelligence. The method comprises the following steps: according to obtained search voice, and through a voiceprint recognition mode, identifying the type of a user sending the search voice; and when the identified type of the user is a child user, carrying out voice recognition on the search voice through a child speech recognition model to obtain search requirements described in the search voice; searching a target resource matched with the search requirements in a multimedia resource library; and on a search result page, presenting the target resource in a multimedia manner, thereby solving the technical problem that since children's language habits are greatly different from adult's language habits, in the voice search process, the presented search results are greatly different from the user requirements, and the child users read with difficulty.

A composite AI system and method for advanced reasoning and automation that integrates symbolic knowledge graphs and algorithms with non-symbolic, or connectionist, models such as neural embeddings. A hierarchical architecture enables dynamically distributed, cooperative reasoning through layperson and expert-led challenge-based verification, model blending, model fitness and retraining and selection, comprehensive feedback loops at individual model or model blend or process flow with or without supervision, and specialized routing of processing to account for various operational risk, regulatory, legal, privacy, or economic considerations. Models, datasets, knowledge bases, simulations and simulation components, and embeddings are iteratively refined using knowledge graph elements and model, process, simulation or flow / process optimal hyperparameters which are recorded and tracked. Extraction of symbolic representations from connectionist models links them to curated ontologies of facts and principles.

In some embodiments, affective-state-based artificial intelligence may be facilitated. One or more growth or decay factors for a set of affective attributes of an artificial intelligence entity may be determined, and a set of affective values, which are associated with the set of affective attributes, may be continuously updated based on the growth or decay factors. An input may be obtained, and a response related to the input may be generated based on the continuously-updated set of affective values of the artificial intelligence entity. In some embodiments, the growth or decay factors may be updated based on the input and subsequent to the updating of the decay factors, the affective values may be updated based on the updated growth or decay factors.

The invention discloses an artificial intelligence-based query intention prediction method and apparatus. The method comprises the steps of analyzing a query intention of an original retrieval statement through log information of interaction of a user and a search engine; and training an intention classification model according to a corresponding relationship between the original retrieval statement and the query intention, thereby predicting a query intention corresponding to the retrieval statement input by the user according to the intention classification model. According to the method, the query intention of the user is accurately analyzed, so that a retrieval result conforming to the query intention of the user can be conveniently provided for the user and the retrieval performance is improved.

The invention provides an automatic trademark application success rate analysis method and system based on artificial intelligence. The method comprises the steps that 1, whether or not a to-be-applied trademark belongs to content specified by prohibitive terms of trademark application is judged on the basis of artificial intelligence querying, and the approximation degree is calculated, wherein the approximation degree is the probability Pjz; 2, the approximation degree between the to-be-applied trademark and an existing trademark is judged on the basis of artificial intelligence retrieval, wherein the approximation degree of the existing trademark is the probability Pjs; 3, the trademark application passing probability P is calculated through the formula P=(1-Pjz)+(1-Pjs). According to the method, success rate analysis before trademark application is conducted through an artificial intelligence technique, and therefore the trademark application success probability can be significantly increased.

The invention provides a man-machine interaction method and device based on artificial intelligence. The man-machine interaction method based on artificial intelligence comprises the steps that a problem input by a user is received; the problem is processed according to a pre-generated model to obtain an answer corresponding to the problem and having a human dialogue style; the model is generated according to human dialogue corpus data; the answer is fed back to the user. The method can make man-machine interaction have a real human dialogue and interaction effect.

The invention discloses a visual design system of the artificial intelligence of a game on the basis of an XML (Extensive Markup Language). The system comprises a system logic device, a graph editor, a function editor, a graph configurator and an integral actuator, wherein the system logic device comprises a connection assembly and a function assembly and is used for describing assembly logics; the graph editor is used for graphically expressing the assemblies and combining the assemblies into an artificial intelligence tree structure; the function editor is used for compiling corresponding attributes and functional interface functions for the assemblies; the graphic configurator is used for configuring the attributes and the functional interface functions to the assemblies; and the integral actuator is used for traversing, backtracking, interrupting and blocking the assemblies of the artificial intelligence tree to cause the artificial intelligence tree structure to own an integrated function. The visual design system has the beneficial effects that a development period of the artificial intelligence is obviously shortened, the maintainability and the reusability of codes are enhanced, game experience is improved, personnel on various posts can work in cooperation with a due division of labor, and a flow is optimized.

The invention provides a news rapid report generating method and device based on artificial intelligence. The news rapid report generating method includes the steps that a template base is pre-constructed based on history news rapid reports, wherein the template base comprises all news types for generating basis frameworks of news rapid reports; target news types of news events are determined, and according to the target news types, target basis frameworks of the target news types are obtained from the template base; structural data of the news events is obtained from a preset database, the target basis frameworks are filled with the content according to the structural data, and the texts of the news rapid reports of the news events are obtained; titles of the news rapid reports are generated according to the texts, and the titles and the texts are jointed to form the news rapid reports. In the news rapid report generating method and device based on artificial intelligence in the embodiment, basis frameworks of different news types can be constructed by learning the history news rapid reports, then the news rapid reports are intelligently generated based on the basis frameworks, and the reporting timeliness of the news events is improved.

A method for intelligently connecting seekers to advisors and providing recorded or synthesized answers to the seekers using artificial intelligence is provided. Receiving a topic of interest from a seeker or retrieving advisors with expertise in the topic from a database of advisors, filtering and sorting the advisors based on ratings associated with each of the advisors related to the topic using machine learning and a plurality of criteria specified by the seeker, routing and establishing a call between the seeker and advisor, when the advisor is unavailable the call is rescheduled for alternate time windows of the advisor or with an alternate advisor and recording and storing the call for automating the answers to the similar questions, obtaining feedback from the seeker for the advisor, and updating the intelligent call routing system and the rankings of the advisor based on the plurality of criteria.

The invention discloses an artificial intelligence-based search recommendation method and device. The method comprises the following steps of: receiving query and obtaining entities related to the query; calculating correlation between the entities and the query, and screening the obtained entities according to the correlation; recognizing a user intention of the query and selecting entities according with the user intention in the screened entities; and sorting the selected entities, and selecting a preset number of entities from the sorted entities as recommended entities to display, wherein at least one reference factor in the correlation calculation and the entity sorting comprises semantic information of the query and of the entities. According to the method disclosed by the invention, the coverage and accuracy of the recommended entities can be improved.

An artificial-intelligence based, authorization data processing system and method that use networked electronic computers are provided. Included are one or more smart agent data structures tasked to individually follow past transaction data and behaviors, and to provide its artificial intelligence observations on the magnitude, type, and quality of payment card revenues and business routinely engaged in by the individual, e.g., a cardholder whose transaction request is pending. The computed level of acceptable transaction risk is raised in proportion to the cardholder's business value. As a further expedient, such quality cardholders may never be subject to a “declined transaction” if the requested payment transaction were less than some liberal minimum to meet an appropriate threshold level.

The invention provides an artificial intelligence assisted administrative examination and approval method based on a knowledge graph. The method comprises the steps of establishing an examination andapproval rule base; constructing an approval body based on an approval rule base; Extracting approval knowledge in the approval material; establishing a relationship between the approval ontology andknowledge from the extracted approval knowledge based on the approval ontology, and constructing an approval knowledge graph; based on the constructed approval knowledge graph, according to differentapproval items of approval materials, obtaining related approval knowledge by utilizing a query function of the knowledge graph, and performing automatic approval; outputting approval results. Meanwhile, the invention provides an artificial intelligence auxiliary administrative approval system and terminal based on the knowledge graph. Technical support is provided for high-efficiency and intelligent administrative approval, window workers are assisted in completing item auditing, the auditing speed of the workers is increased, and the auditing accuracy and the working efficiency are improved.

The application proposes a click predictor method and device based on artificial intelligence. And the method includes: according to the query user input, obtain attributes information of the entity to be recommended; make segmentation processing respectively to the query and attributes information of the entity to be recommended, determine the feature of the query and entity to be recommended; determine the clicking rate of the entity to be recommended using default deep neural network model, according to the query and the feature of entity to be recommended. Therefore, integrating the extracted features into the deep neural network model, predicting the click rate of entity to be determined, can improve the accuracy of the click rate prediction, so that the recommendation system can provide service to the user accurately, improving the service quality of the recommendation system and the user experience.

The invention relates to a method and a device for risk rating of an applicant based on artificial intelligence. The method comprises the following steps: receiving a loan request of an applicant; Collecting data associated with the applicant; Determining, based in part on the data, whether to accept the applicant's loan request; Under the condition that the loan request of the applicant is received, classifying the applicant into one client group in one or more client groups based on the data; Matching loans of corresponding loan types and corresponding risk scoring models for the applicantson the basis of the client group; And calculating a risk score for issuing the loan to the applicant based on the risk score model, wherein the risk score is used for indicating the risk rating of therisk generated when the loan of the loan type is issued to the applicant.

A computer-based method includes receiving health-related data at a computer-based processing system, via a network, wherein the health-related data is associated with each respective one of a plurality of individuals participating in a clinical trial. An artificial intelligence-based evaluation of each of the patients is applied, based on the health-related data, to identify patients for whom participation in the clinical trial should be altered. A notification is generated that, when rendered at a computer-based user interface device, reveals the identified information. Feedback is received at the computer-based processing system, via the network, that corresponds to the generated notification, after the clinical trial participation is altered, the artificial intelligence-based evaluation is altered at the computer-based processing system in view of the feedback received to improve the computer-based processing system's ability to accurately identify patients for whom participation in the clinical trial should be altered.