73 results about "Automated reasoning" patented technology

Methods, systems, and computer program products for identifying computer source code constructs are disclosed. According to one method, computer source code is converted to a format suitable for an automated inference engine. The automated inference engine receives as inputs the converted source code, a set of elemental design patterns defining patterns to be identified, and a set of rules defining relationships between patterns. The automated inference engine outputs proofs indicative of patterns present in the source code. The proofs may be converted to a source code pattern report.

A system and method that translates sentences of natural language text into sets of axioms of formal logic that are consistent with parses resulting from NLP and acquired constraints as they accumulate. The system and method further present these axioms so as to facilitate further disambiguation of such sentences and produces axioms of formal logic suitable for processing by automated reasoning technologies, such as first-order or description logic suitable for processing by various reasoning algorithms, such as logic programs, inference engines, theorem provers, and rule-based systems.

Methods, systems, and computer program products for identifying computer source code constructs are disclosed. According to one method, computer source code is converted to a format suitable for an automated inference engine. The automated inference engine receives as inputs the converted source code, a set of elemental design patterns defining patterns to be identified, and a set of rules defining relationships between patterns. The automated inference engine outputs proofs indicative of patterns present in the source code. The proofs may be converted to a source code pattern report.

Disclosed is a system and method for classifying units of control and concomitant model units from a larger physical system model. The system enables model-based simulation of decoupled system units for improved simulation efficiency. Further, the system allows for automated reasoning about the classification of said units, producing both machine-interpretable and human-readable, natural language descriptions of the decisions and reasons for said decisions made during the classification process, for use in heuristics and user feedback.

In a method for dynamically optimizing resource utilization in a system over time according to one or more objectives, data including information indicative of current environmental conditions, upcoming environmental conditions, a current state of a system configuration, and current system operating conditions is dynamically updated. Automatic analysis of the data using a probabilistic model based on conditional relationships is performed periodically. For each periodically generated set of possible system control actions, a probabilistic model is used to automatically analyze each possible system control action and an optimal system control action is selected based on a set of current utility functions. For each periodically generated set of possible system control actions, control of the system according to the optimal system control action selected from the possible system control actions. Resource optimization couples condition-based and environmental monitoring with automated reasoning and decision making technologies, to develop real time optimal control and decision strategies.

Tools that provide quality assurance to improve the efficiency of developing software using a Finite Input Output Semantic Model (FIOSM, or herein referred to as a Semantic Model (SM) or Semantic Model Program) and automated reasoning services compatible with a semantic model. Exemplary embodiments of the tools allow a user to validate a semantic model and its related source software system and executable, while providing the enormous benefit of automating the quality assurance process. Instead of rigorous manual analysis of code to determine where a problem resides, the tools, through their relationship with the semantic model, visualize for the user on a display or in another tangible media where in the source software system a problem(s) resides.

The invention discloses a method and device for inferring a decision result of a legal document based on logic rules, and relates to the field of judicature. According to the method, key contents areextracted from the decision document and segmented into semantic fragments according to semantics, events are extracted from the semantic fragments and indicated into event units, according to a contextual relationship, each event unit is correlated to form an event logic atlas, and a logic atlas generation model is learned. Weights of each rule are calculated according to the winning frequency ofeach logic rule. Aiming at a new file, the event logic atlas is generated by using the generation model, and the decision result is automatically inferred according to the weights of each logic in the logic atlas. According to the method, key elements and an internal logical relationship of a case are presented in a visualized manner by a generated event logic atlas, the logic thinking manner ofa judge dealing with cases is converted into the logic rules to predetermine a result, and the evaluation of a litigation outcome, the selection of a reconciliation manner and the like of litigants oftwo sides are convenient.

The presently disclosed method and system includes a network of computer devices, sensors, and actuators operating in concert with application software to actively detect, identify, and localize threats and generate real-time countermeasures designed to delay and / or mitigate damage that may be caused by the threats. Application software, in the form of automated reasoning and logic control, initiates preparatory and countermeasure sequences automatically, which may be used by users or automatically executed by the system to at least delay an attack to a physical asset / area by adversaries with use of non-lethal actuators. Learned scenarios are generated and continuously adapted via feedback loops and decision rules to provide preparatory and countermeasure sequences that maximize results with minimal expenditure of assets.

One embodiment of the present invention provides a system that facilitates filtering outbound content via inference detection. During operation, the system identifies content sent to a first address and extracts keywords from the identified content. The system then issues queries based on these keywords and extracts expected-content keywords from the hits returned in response to the queries. The system then searches the outbound content for occurrences of the expected-content keywords and produces a result which allows a user to determine whether the outbound content is proper. In a further embodiment, the system extracts keywords from a piece of outbound content, and issues queries based on these keywords. The system then extracts keywords from the hits, and present at least one keyword to a user, thereby allowing the user to determine whether the outbound content is proper.

An e-commerce real estate marketplace and platform includes one or more systems and methods for facilitating all aspects of cross-border real-estate transactions. Included are one or more unique machine learning techniques that together with multiple data processing steps perform mathematical calculations and / or automated reasoning tasks that allow buyers, sellers, and third parties to execute satisfactory transactions in a secure and confidential environment with complete certainty.

The invention belongs to the technical field of information services, and particularly provides semantic Web service ontology and an application thereof, a method for achieving the generation of SaaS (Software-as-a-Service) and the transition and regeneration of service semantization from the application software that is released to the public and operated on the Web and Web services to semantic Web services by constructing the following ontology semantics in the semantic Web service ontology: service behavior semantics, credible evaluation semantics and coordination relation semantics, and amethod for achieving the semantic Web service evolution comprising the automatic discovery, credible evaluation and automatic combination of the semantic Web services on the basis of the automatic reasoning of the three types of ontology semantics. The specific implementation framework of the method of the invention comprises a semantic Web service ontology constructor, a semantic Web service ontology converter and a semantic Web service ontology reasoning machine, thus achieving the generation, evolution and application of the semantic Web services oriented to the requirements for the specific application field and interdisciplinary cross application and characterized by high-credibility intelligentization.

A system is provided to detect email spam. During operation, the system receives an email, extracts a set of keywords from the email body, and constructs a first search query based a keyword extracted from the email body. The system further constructs a second search query based on the keyword in the first query and one additional word which pertains to a known spam word or to the subject of the email. Next, the system receives a first number of hits and a second number of hits in response to the first and second search queries, respectively. The system then determines whether the email is spam based on the first number and the second number. The system can also perform Website filtering using inference detection which is based on search results received in response to search queries formulated with keywords extracted from Websites.

Aspects of the disclosed technology present a workspace window responsive to a relationship data structure that represents a comprehension state including a presentation set of an ordered set of text strings from an electronic document. The presentation set includes one or more identified strings. The workspace window can then receive a quick-click command invocation on the one or more identified strings and modifies the relationship data structure by adding an entity / relationship object to the relationship data structure responsive to the quick-click command invocation and the one or more identified strings. The application relates to sensemaking or maintaining a comprehension state of a document collection, by recording evidence, spatial hypertext, automatic highlighting, automating inferencing, reading recommendations, and reading through multiple documents.

The invention relates to an intelligent judging method for a court. The method includes the steps that a judgment document of the court is utilized for establishing an auxiliary judgment model with intelligent analysis and automatic reasoning; court hearing records of a pending case are input into the established auxiliary judgment model, the model is matched with court hearing records of existingsimilar cases, and the content of the part 'the court is of the opinion' corresponding to the court hearing records of the existing similar cases is found; according to the content, the part 'the court is of the opinion' of the case is automatically generated; according to the content of the part 'the court is of the opinion' of the case, a judgment result in the existing judgment document is matched, and a judgment suggestion of the case is obtained by summarizing judgment results of similar cases. By establishing an auxiliary judgment system, the judgment fairness is improved for judges, generation of unjust, false and erroneous cases is reduced, and the case-handling efficiency is improved for the judges.

An information technology (IT) architecture upper merged ontology which includes an upper merged ontology that is a representation framework for combined knowledge sources that are used in business and information technology; an upper merged ontology knowledge base containing information derived from an analysis of business and technical services pertaining to the IT architecture application; a plurality of semantic web application programming interfaces (APIs) that allow access to the upper merged ontology as a semantic web; a reasoning and constraint language (RaCL) that is a scripting language having the capabilities of model creation, automated reasoning and search and query operations such that scripts developed in the reasoning and constraint language can execute using the semantic web APIs; and a computer processor for representing and performing execution tasks.

The invention discloses a bit error rate model-based unknown communication protocol identification method. According to the method, a multi-pattern matching algorithm and an association rule analysis algorithm are combined together to extract the protocol feature string of known protocols, so that a protocol feature library is constructed; when a protocol type adopted by identified data is identified, the maximum number of bit errors allowed by the identified data is calculated; a fuzzy matching algorithm is used to extract the feature string of the identified data within the range of the number of the bit errors; and the protocol type adopted by the identified data is obtained through automatic reasoning. Therefore, the identification method can improve a data identification rate and has a good identification effect for data having error codes.

The invention discloses a machine learning method for realizing ship anthropomorphic intelligent collision prevention decision. An analog source and an example source are generated by off-line artificial learning, and a collision prevention model for on-line acquiring new collision avoidance knowledge, and a database for storing ship parameters are constructed, and an automatic reasoning mechanism, a calculation unit and an evaluation system are designed. The collision prevention model and the automatic reasoning mechanism are used, knowledge discovery and approximate reinforcement learning strategies are realized through online machine learning, and new collision prevention knowledge is acquired, and a dynamic collision avoidance knowledge base is constructed. An inference engine is usedto invoke the ship parameters and the PIDVCA algorithm of the database through the automatic inference mechanism to realize the intelligent collision prevention decision of the machine. The machine iscapable of acquiring the information and the formalized collision prevention domain knowledge on site through the guidance of the automatic reasoning mechanism, is used to learn and solve new knowledge of collision prevention problems of any meeting scene, and has a perception target and a cognitive target to further formulate a scientific and reasonable collision prevention decision scheme, andfinally has a thinking mode for simulating and surpassing the human to solve complex collision prevention problems.

The invention relates to a DO-178C software test process orientated object verification and evidence model extracting method. A demonstration structure of objects associated with a software test process is established; corresponding evidence requirements are analyzed out and an evidence model is established according to the evidence requirements; and according to the evidence model, object demonstration automation is realized when project data is corresponding to the evidence model; and an auto-reasoning solution is disclosed for realizing objects in the DO-178 software test process. According to the DO-178C software test process orientated object verification and evidence model extracting method, the software test process conforms to airworthiness certification specifications better, and effective help is provided for determining the objects of the software test process which passes the airworthiness certification; the step of collecting evidence is completed in a more efficient mode, so that the cost is reduced; automatic reasoning of the object satisfiability is realized, so that the cost is reduced; and especially when a great deal of data needs to demonstrate, the efficiency is remarkably improved.

An information technology (IT) architecture upper merged ontology which includes an upper merged ontology that is a representation framework for combined knowledge sources that are used in business and information technology; an upper merged ontology knowledge base containing information derived from an analysis of business and technical services pertaining to the IT architecture application; a plurality of semantic web application programming interfaces (APIs) that allow access to the upper merged ontology as a semantic web; a reasoning and constraint language (RaCL) that is a scripting language having the capabilities of model creation, automated reasoning and search and query operations such that scripts developed in the reasoning and constraint language can execute using the semantic web APIs; and a computer processor for representing and performing execution tasks.

The embodiment of the invention provides a method and device for constructing a network security knowledge graph, and relates to the technical field of network security. The construction method of thenetwork security knowledge graph comprises the steps: firstly obtaining original relation data for constructing the network security knowledge graph, and constructing an original relation graph according to the original relation data; then performing relationship reasoning processing on an original relationship graph through a pre-constructed relationship reasoning model to obtain a missing relationship set; and finally, performing optimization processing on the original relationship graph according to the missing relationship set to obtain a network security knowledge graph. Visibly, in themethod, the missing relation can be automatically reasoned, the network security knowledge graph can be generated, manual participation is not needed, the accuracy is high, the speed is high, and theconstruction efficiency of the network security knowledge graph can be improved.

Disclosed is a system and method for classifying units of control and concomitant model units from a larger physical system model. The system enables model-based simulation of decoupled system units for improved simulation efficiency. Further, the system allows for automated reasoning about the classification of said units, producing both machine-interpretable and human-readable, natural language descriptions of the decisions and reasons for said decisions made during the classification process, for use in heuristics and user feedback.

A method for setting up a knowledge map comprises the steps that propositions are used as nodes, implication operators used for showing logical relations between the propositions are linked with the nodes, a special Boolean network is formed, and the knowledge map is set up. The logical relations are the relations between logical connectors and Boolean functions, and the implication operators comprise binary implication operators, ternary implication operators and multivariate implication operators. The method extends the working method of a propositional logic, and develops an undirected acyclic graph knowledge expressive method having nothing to do with specific application scenes, and automatic reasoning of knowledge of the mathematics and sciences can be more conveniently achieved.

The invention discloses a takeover cruising system based on an automatic reasoning mechanism. The takeover cruising system is mainly used in automatic driving, a multi-modal driving strategy network based on a hidden variable can be generated according to a given offline sample, and thus the general automatic driving function is achieved. Meanwhile, the takeover cruising system can further generate an automatic driving strategy matched with manual driving can further be automatically generated according to the style of manual driving when a user adopts manual driving, thus smooth conversion form a manual driving mode to an automatic driving mode on a highway is achieved, and thus automatic driving can perfectly simulate the driving style of manual driving. The takeover cruising system comprises a discriminator module, a driving strategy generating module and a driving style automatic reasoning module. A model is trained on given real expert demonstration, and thus reliability is achieved. Meanwhile, in the process of manual driving of the user, the model can be adjusted in real time according to a manual driving trajectory so as to enhance the flexibility of the model.

A system is provided to detect email spam. During operation, the system receives an email, extracts a set of keywords from the email body, and constructs a first search query based a keyword extracted from the email body. The system further constructs a second search query based on the keyword in the first query and one additional word which pertains to a known spam word or to the subject of the email. Next, the system receives a first number of hits and a second number of hits in response to the first and second search queries, respectively. The system then determines whether the email is spam based on the first number and the second number. The system can also perform Website filtering using inference detection which is based on search results received in response to search queries formulated with keywords extracted from Websites.

The invention discloses an artificial intelligence ethical rule implementation method, an expert system and a robot. The artificial intelligence ethical rule implementation method comprises the stepsof input acquisition, rule base construction; comprehensive database construction; fact recognition; rule reasoning; and conclusion performing. According to the artificial intelligence ethical rule implementation method, the expert system and the robot, automatic reasoning and automatic implementation of artificial intelligence ethical rules are realized in combination with the expert system and deep learning.

The invention discloses a method for automatically extracting knowledge points of mathematical problems and solving problems. The method comprises the following steps that: step S1, natural language understanding processing is conducted on mathematical question texts, and a processing result serves as an initial data set; S2, an initial data set is trained by using automatic reasoning in combination with a drools reasoning engine and a symbol calculation system to obtain a rule set; and S3, according to mapping between rules in the rule set and the knowledge points and the problem solving methods, the knowledge points and the problem solving methods contained in each mathematical problem are removed. The method can be used for providing accurate topic recommendation for students, a teachercan conveniently know knowledge points which are not mastered by the students and the types of the methods, and a tutoring plan can be made for the students in a more targeted mode.

The invention discloses a method for evaluating virtual assembly time of an engine through the BP algorithm. The method for evaluating the virtual assembly time of the engine through the BP algorithm comprises the following steps that a model of the engine is established through CATIA; a human-computer interaction mode and an automatic reasoning mode are combined under a virtual environment so that generation of an assembly constraint matrix can be achieved; based on a CATIA / DELMIA simulation trial detaching assembly path plan, a virtual assembly operation environment is established and a virtual assembly operation process is created; an assembly path is measured and the assembly time is calculated; an assembly time evaluation model is established and the assembly time is evaluated. The method has a profound meaning in support tools for assembly design, product automatic assembly, parallel design in the CIMS environment and parallel engineering and the method has a significant research value on research of the assembling ability evaluation technology of products.

The embodiment of the invention discloses an inference model training method and device, an electronic device and a storage medium, and the inference model training method comprises the steps: obtaining the current question state of a current question by aiming at the current question in a training sample; selecting a current to-be-executed action according to the current question state; executingthe current to-be-executed action to obtain a new topic state; taking the new topic state as the current topic state of the current topic; according to the technical scheme, the inference model can continuously accumulate the problem solving experience, the inference accuracy is optimized, and the trained inference model can achieve automatic inference of complex elementary mathematical problemsin actual use.