초록 ▼

A computer system is provided that includes a database storing user histories of selected products, and a database associating products with assessments of their content in a number of different categories. The computer system generates user profile data reflecting the underlying characteristics of

A computer system is provided that includes a database storing user histories of selected products, and a database associating products with assessments of their content in a number of different categories. The computer system generates user profile data reflecting the underlying characteristics of user preferences by identifying categories and groups of categories corresponding to products in the user histories whose content assessments are one of an extremely high and low evaluation. In the user profile data, larger groups of categories having extremely high or low content evaluations are weighted more heavily than smaller groups of categories and singly identified categories having extremely high or low content evaluations. The generated user profile data can be utilized to provide targeted advertising and/or to automatically select products are identified with similar underlying characteristics of the user. preferences. In one example, a television recording apparatus is provided that automatically records television programs based on a correspondence between program profile data associated with the television programs and user profile data that has been generated based on a past history of the user's viewing habits.

대표청구항 ▼

A computer system is provided that includes a database storing user histories of selected products, and a database associating products with assessments of their content in a number of different categories. The computer system generates user profile data reflecting the underlying characteristics of

A computer system is provided that includes a database storing user histories of selected products, and a database associating products with assessments of their content in a number of different categories. The computer system generates user profile data reflecting the underlying characteristics of user preferences by identifying categories and groups of categories corresponding to products in the user histories whose content assessments are one of an extremely high and low evaluation. In the user profile data, larger groups of categories having extremely high or low content evaluations are weighted more heavily than smaller groups of categories and singly identified categories having extremely high or low content evaluations. The generated user profile data can be utilized to provide targeted advertising and/or to automatically select products are identified with similar underlying characteristics of the user. preferences. In one example, a television recording apparatus is provided that automatically records television programs based on a correspondence between program profile data associated with the television programs and user profile data that has been generated based on a past history of the user's viewing habits. ion retrieval module, the deduction retrieval module comprising: a deduction input, wherein the deduction input comprises an element identified as language data of the at least one first memory segment; and, at least one deduction output representing at least one element identified as language data of the at least one first memory segment, the at least one deduction output corresponding to the distinct second memory segment elements reciprocally associated with the deduction input and different from the deduction input. 5. The system of claim 1, further comprising at least one of: an export module to transfer elements of the at least one first memory segment and reciprocally associated elements of the distinct second memory segment, to a computer readable medium; an import module to read from a computer readable medium, elements compatible with the at least one first memory segment, the distinct second memory segment, and the reciprocal associations therein, and transfer the compatible elements to the at least one first memory segment and the distinct second memory segment; and, an adoption module to read a database and convert the database to the at least one first memory segment and the distinct second memory segment, and create the reciprocal associations. 6. The system of claim 1, further comprising an execution module, the execution module further comprising: an execution input module to accept data from the at least one first memory segment and the distinct second memory segment; an execution storage module to store data from the at least one first memory segment and the distinct second memory segment; an execution association algorithm to generate relationships between data in the execution storage module and generate an action information; and, an execution output module to output the action information. 7. The system of claim 1, further comprising: at least one input interface to accept at least one of: auditory data, visual data, language data, motion data, and sensor data; and, at least one output interface to provide at least one of: auditory data, visual data, language data, motion data, and sensor data. 8. The system of claim 7, wherein: auditory data comprises sound data, further comprising data compatible with a microphone; language data comprises words from written, typed, scanned, FAXed, or computer readable medium, and a graphical user interface; visual data comprises pictorial data, further comprising graphical data and image data; motion data comprises data compatible with a motion sensor, farther comprising radar data, sonar data, and other positional information data; and, sensor data comprises data compatible with a sensor device, further comprising data received from an electronic measurement device. 9. The system of claim 1, wherein the at least one first memory segment and the distinct second memory segment further comprise a database. 10. The system of claim 1, wherein the at least one first memory segment further comprises at least one of: a first, first memory segment to exclusively store auditory data; a distinct second, first memory segment to exclusively store visual data; a distinct third, first memory segment to exclusively store language data; a distinct fourth, first memory segment to exclusively store motion data; and, a distinct fifth, first memory segment to exclusively store sensory data. 11. The system of claim 1, further comprising a recognition retrieval algorithm, the recognition retrieval algorithm comprising: a recognition input, wherein the recognition input comprises at least one first memory segment element identified as visual data, auditory data, sensor data, or motion data; and, at least one recognition output representing at least one element of the at least one first memory data segment, and corresponding to at least one distinct second memory segment element: reciprocally associated with the recognition input, and, differ ent from the recognition input. 12. The system of claim 1, further comprising a reduction retrieval algorithm, the reduction retrieval algorithm comprising: a reduction input, wherein the reduction input comprises an element of the distinct second memory segment; and, at least one reduction output representing at least one first memory segment element identified as language data and corresponding to at least one first memory segment element reciprocally associated with the reduction input. 13. The system of claim 1, further comprising an imaging retrieval algorithm, the imaging retrieval algorithm comprising: at least one imaging input, the at least one imaging input comprising at least one element of the distinct second memory segment; and, at least one imaging output representing at least one first memory segment element identified as auditory data, motion data, sensory data, or visual data and corresponding to at least one first memory segment element reciprocally associated with all of the at least one imaging input. 14. The system of claim 1, further comprising a recall retrieval algorithm, the recall retrieval algorithm comprising: at least two recall inputs, the at least two recall inputs comprising at least two elements of the distinct second memory segment; and, at least one recall output representing at least one first memory segment element identified as language data of at least one first memory segment reciprocally associated with all of the at least two recall inputs. 15. The system of claim 1, further comprising a categorization retrieval algorithm, the categorization retrieval algorithm comprising: at least two categorization inputs, the at least two categorization inputs comprising at least least two first memory segment elements; and, at least one categorization output representing at least one element of the distinct second memory segment reciprocally associated with all of the at least two categorization inputs. 16. The system of claim 1, further comprising a reasoning retrieval algorithm, the reasoning retrieval algorithm comprising: a first reasoning input, the first reasoning input comprising a first memory segment element; a distinct second reasoning input, the distinct second reasoning input comprising a first memory segment element; and, at least one reasoning output representing all elements of the at least one first memory segment that are traversed in the reciprocally associated hierarchy connecting the first reasoning input and the distinct second reasoning input. 17. A knowledge acquisition and retrieval method, comprising: designating at least one first memory segment; designating a distinct second memory segment; and, reciprocally associating elements of the distinct second memory segment with elements of the at least one first memory segment, to create a hierarchical relationship between elements of the at least one first memory segment by traversing the reciprocal associations, and to create a hierarchical relationship between elements of the distinct second memory segment by traversing the reciprocal associations, the reciprocal associations formed by an associative module that accepts a first input and a distinct second input, and, searches the at least one first memory segment for the first input, and exits upon finding the first input in the at least one first memory segment, and otherwise stores the first input in the at least one first memory segment, creates a corresponding first abstract element in the distinct second memory segment, and reciprocally associates the at least one first memory segment element containing the first input, with the distinct second memory segment element containing the first abstract element; searches the at least one first memory segment for the distinct second input, and exits upon finding the distinct second input in the at least one first memory segment, and otherwise stores the distinct second input in the at lea st one first memory segment, creates a corresponding second abstract element in the distinct second memory segment, and reciprocally associates the at least one first memory segment element containing the second input, with the distinct second memory segment element containing the second abstract element; and, reciprocally associates the at least one first memory segment element containing the first input, with the distinct second memory segment element containing the second abstract element. 18. The method of claim 17, further comprising retrieving data from the at least one first memory segment. 19. The method of claim 17, further comprising retrieving data from the at least one first memory segment using at least one of a deduction retrieval algorithm, a recognition retrieval algorithm, a reduction retrieval algorithm, an imaging retrieval algorithm, a recall retrieval algorithm, a categorization retrieval algorithm, and a reasoning retrieval algorithm. 20. The method of claim 17, further comprising retrieving data from the at least one first memory segment based on a executing a deduction retrieval algorithm: where executing the deduction retrieval algorithm further comprises: obtaining a deduction input, wherein the deduction input comprises an element identified as language data of the at least one first memory segment; and, generating at least one deduction output representing at least one element identified as language data of the at least one first memory segment, the at least one deduction output corresponding to the distinct second memory segment elements reciprocally associated with the deduction input and different from the deduction input. 21. The method of claim 17, further comprising at least one of: exporting data by transferring elements of the at least one first memory segment and reciprocally associated elements of the distinct second memory segment, to a computer readable medium; importing data from a computer readable medium, elements compatible with the at least one first memory segment, the distinct second memory segment, and the reciprocal associations therein, and transferring the compatible elements to the at least one first memory segment and the distinct second memory segment; and, adopting data from a database and converting the database to the at least one first memory segment and the distinct second memory segment, and creating the reciprocal associations. 22. The method of claim 17, further comprising developing an execution module, developing an execution module further comprising: designing an execution input module to accept data from the at least one first memory segment and the distinct second memory segment; designing an execution storage module to store data from the at least one first memory segment and the distinct second memory segment; creating an execution association algorithm to generate relationships between data in the execution storage module and generate an action information; and, designing an execution output module to output the action information. 23. The method of claim 17, further comprising at least one of: providing at least one input interface for accepting at least one of auditory data, visual data, language data, motion data, and sensory data; and, providing at least one output interface for providing at least one of: auditory data, visual data, language data, motion data, and sensory data. 24. The method of claim 23, wherein: accepting auditory data comprises accepting sound data, further comprising accepting data compatible with a microphone; accepting language data comprises accepting words for written, typed, scanned, FAXed, or computer readable medium, and a graphical user interface; accepting visual data comprises accepting pictorial data, further comprising accepting graphical data and image data; accepting motion data comprises accepting data compatible with a motion sensor, further comprising accepting radar data, sona