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4776results about "Knowledge representation" patented technology

Computational method and system to perform empirical induction

The present invention is an improved computational method and system of empirical induction that can be used to arrive at generalized conclusions and make predictions involving longitudinal associations between and among variables and events. Empirical induction is used to gain scientific knowledge, to develop and evaluate treatments and other interventions, and to help make predictions and decisions. The invention, which is distinct from and often complementary to the statistical method, is applied to repeated measures and multiple time-series data and can be used to quantify, discover, analyze, and describe longitudinal associations for individual real and conceptual entities. Major improvements include provisions to define Boolean independent events and Boolean dependent events and to apply analysis parameters such as episode length and episode criterion for both independent and dependent variables, persistence after independent events, and delay and persistence after Boolean independent events. These improvements are in addition to levels of independent and dependent variables, delay after independent events, and provision to quantify benefit and harm across two or more dependent variables. Additional improvements include provisions to quantify longitudinal associations as functions of period or time and to compute values of predictive indices when there are two or more independent variables. Major applications and uses of the invention include data mining, the conduct of clinical trials of treatments for the management or control of chronic disorders, health-effect monitoring, the quantification and analysis internal control in adaptive systems, analyses of serial functional images, analyses of behavior and behavior modification, and use to create computerized devices and systems whose behavior can be modified by experience. The present invention is best implemented on the Internet.

Ontology for database design and application development

A system and method lets a user create or import ontologies and create databases and related application software. These databases can be specially tuned to suit a particular need, and each comes with the same error-detection rules to keep the data clean. Such databases may be searched based on meaning, rather than on words-that-begin-with-something. And multiple databases, if generated from the same basic ontology can communicate with each other without any additional effort. Ontology management and generation tools enable enterprises to create databases that use ontologies to improve data integration, maintainability, quality, and flexibility. Only the relevant aspects of the ontology are targeted, extracting out a sub-model that has the power of the full ontology restricted to objects of interest for the application domain. To increase performance and add desired database characteristics, this sub-model is translated into a database system. Java-based object-oriented and relational application program interfaces (APIs) are then generated from this translation, providing application developers with an API that exactly reflects the entity types and relations (classes and methods) that are represented by the database. This generation approach essentially turns the ontology into a set of integrated and efficient databases.
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