174 results about "Conceptual model" patented technology

A distributed virtual environment includes one or more entities represented in the virtual environment by at least a conceptual entity-model, a dynamic entity-model and a visual entity-model each of the entity models being mutually independent. A server provides a conceptual-model manager, arranged to provide conceptual entity-models, one or more dynamic-model managers arranged to provide dynamic entity-models, and one or more client apparatuses arranged to provide a visual-model manager arranged to provide visual entity-models. Communications is arranged to allow transmission of messages between the conceptual-model manager, one or more dynamic-model managers and one or more visual-model managers.

A method and apparatus for extracting a model vector representation from multimedia documents. A model vector provides a multidimensional representation of the confidence with which multimedia documents belong to a set of categories or with which a set of semantic concepts relate to the documents. A model vector can be associated with multimedia documents to provide an index of its content or categorization and can be used for comparing, searching, classifying, or clustering multimedia documents. A model vector can be used for purposes of information discovery, personalizing multimedia content, and querying a multimedia information repository.

The invention relates to the field of distributed combat simulation,and provides a battle simulation training system and method of attack drone formation. According to physical nodes,the battle simulation training system is divided into a drone and launch platform simulation node,a drone formation command node,a ground plan control node,a neighbour equipment simulation node,an enemy troop simulation node,a tactical communication simulation node,a situation display node,a train control node and a data record analyze node; according to battle simulation modeling,an environment simulation model,amodel system which comprises a simulation entity model and a military conceptual model is established. The battle simulation training system has good supporting effects on tactical cooperative training,operational plan deduction and equipment improvement and optimization of the attack drone formation.

The present invention relates to processing of textual information in order to automatically answer user-submitted questions pertaining to a given knowledge domain. A proposed system (500) includes a user input interface (510) adapted to receive a user-formulated question (QU) on a natural language format. A transforming module (520), on one hand, converts the user formulated question (QU) into a question template format (QUT) including at least one entity term indicative of a respective main concept embodied in the user formulated question (QU), and on the other hand, converts the user formulated question (QU) into a data instance matching format (QUD) adapted to query a structured database (570), which represents at least a part of a conceptual model of the knowledge domain. A lexicon database (540) contains a multitude of concepts (C) which each is related to a specific question template. A template-matching engine (550) matches the question-template formatted user question (QUT) against the lexicon database (540) to retrieve a matching template cluster (CTQ<m>) associated with a matching query template (TY<m>) and a matching answer template (alphaT<m>), and including at least one matching question template. This template, in turn, has at least one entity slot which is linked to the structured database (570). A data instance-matching engine (560) matches the data-instance-matching formatted user question (QUD) against the structured database (570) to identify at least one matching data instance (Di). A central processing unit (530) fills at least one particular entity slot of the at least one matching question template with the identified at least one matching data instance (Di). A search engine (580) queries the structured database (570) with the matching query template (TY<m>) to retrieve information ([i]) to complete the matching answer template (alphaT<m>). A presentation interface (590) presents an answer (alpha) based on the retrieved information ([i]) and the matching answer template (alphaT<m>).

A method and program product for integrating different data sources has steps of obtaining semantic information from each of the different data sources (200, 202, 210), creating a conceptual model of (218, 220, 22) the data source using the semantic information, and accessing one or more secondary knowledge sources. The secondary information sources contain information regarding the relations of data from different of the databases, so that an integrated semantic model of all of the databases (200, 202, 210) may be created. Queries can then be processed using the integrated semantic model.

Methods, systems, and articles of manufacture for context insensitive model entity searching are provided. A model entity is used to identify to a central entity or concept modeled by a database abstraction model. Instances of a model entity may be defined in reference to an identifier in an underlying database. Model entity relationships specify relationships between the model entity and other datasets in the database (e.g., tables of a relational database). A database abstraction model provides an interface to both the model entity and the data in the underlying database. Rather than creating a query of the database using a series of restrictive conditions, or selecting individual the tables or datasets to search, a user may specify search term(s). Instances of the model entity containing the search term(s), regardless of where the search term(s) occur in the underlying database, are returned for the search. Thereafter, a user may select individual instances of the model entity to view in greater detail.

A method, information processing system, and computer readable medium for generating a plurality of candidate database schemas including relational and mark-up language elements. An information model comprising a plurality of entities and at least one relationship defined there between is received. The information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic. The information model that has been annotated is analyzed. A score is associated with each entity based at least in part on attributes associated with each entity. Each entity is classified as one of a relational element and a mark-up language element. The information model that has been annotated is partitioned into a plurality of relational element mappings and a plurality of mark-up language element mappings. A plurality of database schemas associated with the information model that has been annotated is generated.

The invention provides a multi-subject extracting method based on semantic categories. The multi-subject extracting method based on the semantic categories comprises the following steps that firstly, a document is preprocessed according to a traditional method and a vector composed of feature words is obtained preliminarily; secondly, synonyms are merged by the utilization of the corresponding relation between word meanings and concepts of 'HowNet', polysemic word disambiguation is carried out according to the correlation between the semantic categories and the context, and a concept vector model is constructed to represent the document; then the concept vector model is converted to be a semantic category model according to the one-to-one corresponding relation between the concepts and the semantic categories; the concept similarity is calculated by the utilization of the related semantic information in the concepts in 'HowNet' and then the semantic similarity is obtained; the semantic categories are clustered by improving the K-means algorithm according to the method of presetting seeds, and a plurality of subject semantic category clusters are formed; finally, a plurality of sub-subject word sets are obtained in a reverse mode according to the corresponding relations between the semantic categories and the concepts and between the concepts and words. The method considers the semantic information, overcomes the defect that the sensibility to the initial center by the K-means algorithm and time-and-space cost are not stable, and improves the quality of extracted subjects.

A method and system for developing a conceptual model to facilitate generating a business-aligned information technology (IT) solution. Requirements of the IT solution are defined. A conceptual model is developed by business and IT stakeholders. The conceptual model represents an IT solution design and includes systems, conceptual components and operational concepts. The conceptual components represent hardware components and software components of the IT solution. The operational concepts indicate interactions among the conceptual components that are needed to perform business functions. A computing system generates documentation of the conceptual model. The documentation is available and accessible to the business and IT stakeholders and includes documentation of the operational concepts. The architecture and design of the IT solution is developed along with related documentation.

A method of synchronizing data between multiple endpoints each storing a copy of the data in accordance with different underlying schemas. An application model that provides a logical representation of an underlying schema is extended with a synchronization model that provides a logical representation of changes made to the data. The synchronization model comprises functions that provide synchronization information on the changes in a common format. Using such synchronization information, changes in a copy of the data stored in a first underlying schema on a first endpoints are applied to another copy of the data stored in a second underlying schema on a second endpoint in synchronization relationship with the first endpoint.

An electronic method for parametric modeling of a conceptual vehicle design. The method includes (a) receiving dimensional input including one or more vehicle level parameters and one or more component level parameters; (b) receiving geometrical input including one or more non-dimensional design inputs; and (c) generating a parametric concept model based on dimensional input and the geometrical input.

The invention discloses a method for quantitatively recognizing an oil deposit dominant flow channel adopting a zero dimension comparison plate. The method includes the following steps: firstly collecting geological parameters and fluid parameters of an oil field to draw a parameter distribution cumulative frequency curve and obtain corresponding distribution intervals and distribution characteristics; according to the parameter distribution characteristics of a target oil deposit, calculating a water drive development dynamic through the combination with corresponding figure conceptual models; finding out the water absorption parameters and liquid production parameters of layers with the maximum and minimum water absorption capability and liquid production capability for zero dimension treatment through the statistics of conceptual model results; drawing a zero dimension parameter distribution plate, and dividing a dominant channel developing space through the cluster analysis method and obtaining a quantitative plate; and performing the single-well zero dimension parameter treatment, and judging the developing condition of the dominant flow channel through the zero dimension comparison plate. According to the invention, the analysis data source is wide, the cost is low, the spend time is short, personnel at an ore yard can use the method conveniently, the individual judgment on each injection and production well in the oil deposit is realized, the quantitative judging standard is given, and the specific developing layer of the dominant flow channel can be confirmed.

The invention belongs to the oil gas exploration exploitation field and particularly relates to a method capable of realizing quantitative prediction on a favorable oil gas accumulation area. The method comprises steps that, (1), parameters capable of representing oil gas accumulation influence factors and a mathematics calculation method thereof are determined; (2), a main control oil gas accumulation factor is determined; an influence factor of the main control oil gas accumulation factor is determined; (4), a mathematics model of the main control oil gas accumulation influence factor is established; (5), a mathematics model capable of comprehensively evaluating the oil gas accumulation potential is established; and (6), calculation result mapping and evaluation are carried out. According to the statistics relationship among oil gas distribution, output capacity and the main control factor, a conception model and the mathematics model of the main control factor influencing oil gas accumulation in a deposition basin are established, quantitative evaluation on oil gas accumulation under the control of multiple factors in a certain area is carried out, and evaluation on the oil gas accumulation condition is switched from a traditional qualitative mode to a quantitative mode .

The invention provides a road network modeling method which takes road as a fundamental element, aiming at describing a traffic network by utilizing mutual relation among the roads with substitutive characteristics of the road in the traffic network taken into account. A data model matched with a conceptual model is given on the basis of improving a road network model which takes the road as the fundamental element, and data redundancy is reduced by blending related traffic information. A path searching algorithm suitable for the road network model is proposed on the basis of the road network model, and the path searching optimization is realized by utilizing road relation and road traffic attribute.

The invention provides a domain-oriented Chinese text topic sentence generation method. The method is characterized by comprising the following steps of establishing a corresponding domain knowledge map for a domain-oriented text data set, using a deep neural network model for extracting semantic information from texts, classifying the texts according to topic sentence patterns, and finally generating topic sentences of the texts. A data set conceptual model and content narrative mode characteristics are obtained by creating the domain knowledge map, and a deep learning model is used for conducting labeling and classifying training on text data, so that the topic sentences of the texts are generated, and knowledge-based query and statistics are achieved. The method has high application applicability and a good topic sentence generation effect on the limited domain data set.

A system and method for software development and in particular runtime program verification. The system is capable of monitoring a computer program and maintaining an abstracted model of the computer program using an agent which monitors a plurality of execution points in the program during the running of the computer program. The abstract model of the computer program is updated upon execution of the computer program at at least one of the execution points. The agent may also be adapted to detect a pattern in the abstracted model and issue an alert upon detection of the pattern.

The invention discloses a semantic model based text message extraction method and device. The method comprises the steps that to-be-extracted text messages are obtained; the to-be-extracted text messages are subjected to message extraction according to extract expressions and semantic models corresponding to the extract expressions, and target messages are obtained, wherein the extract expressionscomprise a part of speech extract expression, a time extract expression and/or a rule extract expression, the semantic model corresponding to the part of speech extract expression is a statistical semantic model, the semantic model corresponding to the time extract expression is a time semantic conceptual model, and the semantic model corresponding to the rule extract expression is a rule semantic model. Accordingly, the corresponding extract expressions and the semantic models are set according to different extract requirements, message extraction is conducted on the to-be-extracted text messages, workers do not need to compile complex regular expressions one by one, the generation difficulty is lowered, the matching flexibility is improved, and therefore the method can not only improvethe extract efficiency but also lower the workload of the workers.

The invention discloses a method for generating a virtual scene and a system thereof. The method comprises the following steps of: expanding basic property information about a target scene to be designed so as to form detailed information about the target scene to be designed, hiring the detailed information about the target scene to generate a conceptive model of the target scene, instantiating the conceptive model of the target scene to obtain the target scene according to the resources for scene design. The system mainly comprises a conceptive model generating module and an instantiated module. The system can automatically design and generate virtual scene, thus greatly shortening the design period and ensuring that the design result has reusability to the utmost extent.