Abstract: A processor performs constraint-based parsing of a natural language communication including an ordered sequence of a plurality of word spellings of a natural human language by reference to a consistent meaning framework (CMF) graph including a plurality of meaning nodes each corresponding to a respective word meaning. Each of the plurality of meaning nodes is linked by a respective edge to another one of the plurality of meaning nodes serving as a parent node. The parsing includes scanning the natural language communication in different parse scan directions and determining a meaning associated with a particular word spelling in a phrase of the natural language communication by reference to a constraint provided by a particular meaning node in the CMF graph that corresponds to the particular word spelling. Determining the meaning includes verifying satisfaction of the constraint by examining, within the CMF graph, parent node(s) linked to particular meaning node.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes parsing the natural language communication and selecting, for each of multiple word spellings in the natural language communication, a selected word meaning from among the word meanings provided by the CMF graph. The selected word meaning for each of the multiple word spellings in the natural language communication is recorded in data storage.

Abstract: A method for processing a natural language communication includes a processor receiving a natural language communication and identifying, in the natural language communication, an ordered sequence of a plurality of word spellings of a natural human language. The processor performs constraint-based parsing of the natural language communication by reference to a consistent meaning framework (CMF) graph including a plurality of nodes each corresponding to a respective word meaning. The parsing includes scanning the phrase in multiple different parse scan directions and determining a respective meaning associated with each of multiple word spellings in a phrase of the natural language communication by reference to multiple constraints provided by multiple nodes in the CMF graph respectively corresponding to the word meanings.

Abstract: A method for processing a natural language communication includes a processor receiving a natural language communication and identifying, in the natural language communication, an ordered sequence of a plurality of word spellings of a natural human language. The processor performs constraint-based parsing of the natural language communication by reference to a consistent meaning framework (CMF) graph including a plurality of nodes each corresponding to a respective word meaning. The parsing includes scanning the phrase in multiple different parse scan directions and determining a respective meaning associated with each of multiple word spellings in a phrase of the natural language communication by reference to multiple constraints provided by multiple nodes in the CMF graph respectively corresponding to the word meanings.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes parsing the natural language communication and selecting, for each of multiple word spellings in the natural language communication, a selected word meaning from among the word meanings provided by the CMF graph. The selected word meaning for each of the multiple word spellings in the natural language communication is recorded in data storage.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes selecting, for a word in the natural language communication, a selected word meaning from among the multiple word meanings based on which of the plurality of associated constraints is satisfied by the natural language communication. An indication of the selected word meaning is stored in data storage.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes selecting, for a word in the natural language communication, a selected word meaning from among the multiple word meanings based on which of the plurality of associated constraints is satisfied by the natural language communication. An indication of the selected word meaning is stored in data storage.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes selecting, for a word in the natural language communication, a selected word meaning from among the multiple word meanings based on which of the plurality of associated constraints is satisfied by the natural language communication. An indication of the selected word meaning is stored in data storage.

Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.

Abstract: A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes selecting, for a word in the natural language communication, a selected word meaning from among the multiple word meanings based on which of the plurality of associated constraints is satisfied by the natural language communication. An indication of the selected word meaning is stored in data storage.

Abstract: A method for emulating human cognition in electronic form is disclosed. Information is received in the form of a textual or voice input in a natural language. This is parsed into pre-determined phrases based on a stored set of language rules for the natural language. Then, the parsed phrases are determined as to whether they define aspects of an environment and, if so, then creating weighting factors to the natural language that are adaptive, the created weighting factors operable to create a weighted decision based upon the natural language. Then it is determined if the parsed phrases constitute a query and, if so, then using the weighted factors to make a decision to the query.

Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.

Abstract: A method for parsing the flow of natural human language to convert a flow of machine recognizable language into a conceptual flow includes, first, recognizing the lexical structure and then, a basic semantic grouping is determined for the language flow in the lexical structure. The basic semantic grouping is then determined that denotes the main action, occurrence or state of being for the language flow. The responsibility of the main action, occurrence or state of being for the language flow is then determined within the lexical structure followed by semantically parsing the lexical structure.

Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.

Abstract: A method for parsing the flow of natural human language to convert a flow of machine recognizable language into a conceptual flow includes, first, recognizing the lexical structure and then, a basic semantic grouping is determined for the language flow in the lexical structure. The basic semantic grouping is then determined that denotes the main action, occurrence or state of being for the language flow. The responsibility of the main action, occurrence or state of being for the language flow is then determined within the lexical structure followed by semantically parsing the lexical structure. Thereafter, any ambiguities in the responsibilities are resolved in a recursive manner by applying a predetermined set of rules thereto.

Abstract: A method for effecting a dialogue with an emulated brain. The method includes the step of receiving a query in the form of a semantic string. The semantic string is then parsed into basic concepts of the query. The basic concepts are then clumped into a clump concept. If the clump concept constitutes part of a dialogue, then the dialogue thread is activated by determining the context of the clump concept and assessing a potential reply from a group of weighted replies, which expected replies are weighted based on the parsed concepts produced in the step of parsing. The heaviest weighted one of the expected replies is selected and the weight of the selected reply after it is selected is downgraded. The selected reply is then generated for output in a sentence structure.

Abstract: A method for effecting a dialogue with an emulated brain. The method includes the step of receiving a query in the form of a semantic string. The semantic string is then parsed into basic concepts of the query. The basic concepts are then clumped into a clump concept. If the clump concept constitutes part of a dialogue, then the dialogue thread is activated by determining the context of the clump concept and assessing a potential reply from a group of weighted replies, which expected replies are weighted based on the parsed concepts produced in the step of parsing. The heaviest weighted one of the expected replies is selected and the weight of the selected reply after it is selected is downgraded. The selected reply is then generated for output in a sentence structure.

Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.

Abstract: A method for emulating human cognition in electronic form is disclosed. Information is received in the form of a textual or voice input in a natural language. This is parsed into pre-determined phrases based on a stored set of language rules for the natural language. Then, the parsed phrases are determined as to whether they define aspects of an environment and, if so, then creating weighting factors to the natural language that are adaptive, the created weighting factors operable to create a weighted decision based upon the natural language. Then it is determined if the parsed phrases constitute a query and, if so, then using the weighted factors to make a decision to the query.

Abstract: A method for emulating human behavior and actions in an expert mode to control and execute a defined task. The first step is to define a task based application having a task associated therewith that is operable to receive goals and conditions and which goals define the desired results to be achieved when the task is performed. A brain emulation is represented by a plurality of nodes each representing a concept, and interconnecting relationships between select ones of the concepts, which brain emulation is operable to receive information from the task based application and process such information and capable controlling the task based application with the outcome of such processing to achieve the goal of the task based application.