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An apparatus (20) and method (22) for transparently accessing and interpolating data are provided. Consecutive data values (24) of a function are generated and indexed. Even-indexed data values (24) are stored in an even-indexed table (30) and odd-indexed data values (24) are stored in an odd-indexe

An apparatus (20) and method (22) for transparently accessing and interpolating data are provided. Consecutive data values (24) of a function are generated and indexed. Even-indexed data values (24) are stored in an even-indexed table (30) and odd-indexed data values (24) are stored in an odd-indexed table (32). Adjacent-indexed data values (24) are acquired substantially simultaneously from even- and odd-indexed tables (30,32) with the first-indexed value (Gn) extracted from the even-indexed table (30) when an integral portion (A[N]) of a memory address (A[N+F]) is even and from the odd-indexed table (32) when the integral portion (A[N]) is odd. A fractional portion (A[F]) of the memory address (A[N+F]) is converted into an incremental value (&Dgr;). An interpolation circuit (102) then produces an output data value (GOut) as a sum of the first-indexed value (Gn) plus a product of the incremental value (&Dgr;) times a difference of the second-indexed value (Gn+1) less the first-indexed value (Gn).

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An apparatus (20) and method (22) for transparently accessing and interpolating data are provided. Consecutive data values (24) of a function are generated and indexed. Even-indexed data values (24) are stored in an even-indexed table (30) and odd-indexed data values (24) are stored in an odd-indexe

An apparatus (20) and method (22) for transparently accessing and interpolating data are provided. Consecutive data values (24) of a function are generated and indexed. Even-indexed data values (24) are stored in an even-indexed table (30) and odd-indexed data values (24) are stored in an odd-indexed table (32). Adjacent-indexed data values (24) are acquired substantially simultaneously from even- and odd-indexed tables (30,32) with the first-indexed value (Gn) extracted from the even-indexed table (30) when an integral portion (A[N]) of a memory address (A[N+F]) is even and from the odd-indexed table (32) when the integral portion (A[N]) is odd. A fractional portion (A[F]) of the memory address (A[N+F]) is converted into an incremental value (&Dgr;). An interpolation circuit (102) then produces an output data value (GOut) as a sum of the first-indexed value (Gn) plus a product of the incremental value (&Dgr;) times a difference of the second-indexed value (Gn+1) less the first-indexed value (Gn). claim 1, wherein the data includes only user data for the subobjects. ia content unit is specified in a language other than the language of a determined term of the structured vocabulary that was used to characterize the media content unit.8. The method of claim 1 wherein a term is ordered by implicitly associating the term with a plurality of other terms.9. The method of claim 1 wherein the search term is normalized to convert search term variants to a same search term.10. The method of claim 1 wherein the structured vocabulary comprises terms in a second language that correspond to terms expressed in a first language of the structured vocabulary.11. The method of claim 10 wherein the association of the identifier of a term in the first language with a media content unit results in the media content unit being automatically characterized by the corresponding term in the second language.12. The method of claim 1 wherein ambiguous search terms are disambiguated by presenting the relationship of the search term to a plurality of other terms.13. The method of claim 12 wherein the disambiguation of search terms may be optionally activated.14. The method of claim 12 wherein the disambiguated search term is used to locate media content units that are characterized by the disambiguated search term.15. The method of claim 1, further comprising, for each term of the structured vocabulary, creating an index from the term to a collection of media content units that are characterized by the term.16. The method of claim 15, further comprising using the created index to efficiently determine the collection of media content units that are characterized by the search term.17. The method of claim 1 wherein the media content units comprise digital images.18. The method of claim 1 wherein the media content units comprise sound recordings.19. The method of claim 1 wherein the media content units comprise text.20. A structured vocabulary stored in a computer memory usable with a computer system, comprising: a plurality of media content units; and a plurality of identifiers of terms, wherein the terms are ordered in the structured vocabulary according to inherent relationships between the terms, such that each media content unit is associated with an identifier of at least one term, and wherein each media content unit can be determined by matching a requested term with an identifier of a corresponding term. 21. The structured vocabulary of claim 20 wherein each term is stored in a vocabulary unit.22. The structured vocabulary of claim 21 wherein the vocabulary unit stores synonyms of the term stored in the vocabulary unit.23. The structured vocabulary of claim 20, wherein each identifier of a term also identifies synonyms of that term.24. The structured vocabulary of claim 23, wherein a synonym includes a translation of the term into another language.25. The structured vocabulary of claim 20 wherein each term is associated with a particular media content unit by storing an identifier of the term in a metadata structure associated with the media content unit.26. The structured vocabulary of claim 25 wherein the metadata structure is used to determine the media content unit when a request term is received by the computer system that specifies the term referred to by the metadata structure.27. The structured vocabulary of claim 20, further comprising a reverse index stored in the computer memory that stores, for each term, an identifier of each media content unit that is associated with the identifier of that term.28. The structured vocabulary of claim 27 wherein the reverse index is used to efficiently determine a set of media content units associated with a requested term.29. The structured vocabulary of claim 20 wherein the plurality of terms comprises terms in a plurality of languages.30. The structured vocabulary of claim 29 wherein two term in different languages that share a common meaning can be used interchangeably to locate a media content unit associated with the identifier of one of the two terms.31. T he structured vocabulary of claim 20 wherein the media content units comprise digital images.32. The structured vocabulary of claim 20 wherein the media content units comprise sound recordings.33. The structured vocabulary of claim 20 wherein the media content units comprise text.34. A media classification and retrieval system comprising: a structured vocabulary stored in a data repository and having a plurality of terms ordered such that the relationship of each term to each other term is inherent in the ordering; a plurality of media content units wherein each media content unit is associated with an identifier of a term of the structure vocabulary that represents a characteristic of the media content unit; and a search engine that receives a request to locate a media content unit based upon a search term and that uses the structured vocabulary and the associations between media content units and identifiers of terms in the structured vocabulary to determine a collection of media content units that are characterized by the search term. 35. The system of claim 34 wherein the ordering of one of the terms that represents a characteristic of a media content unit is modified so that its relationship to other terms is altered, the modification occurring in a manner that does not affect prior associations between the one term and a media content unit.36. The system of claim 34 wherein the ordering of the terms of the structured vocabulary is hierarchical such that terms located further down in the hierarchy provide more specificity.37. The system of claim 34 wherein the ordering of the terms of the structured vocabulary includes terms that are subordinated to a plurality of other terms.38. The system of claim 34 wherein a term and an identifier of the term are associated with a media content unit according to an objective classification.39. The system of claim 34 wherein a term and an identifier of the term are associated with the media content unit according to a subjective classification.40. The system of claim 34 wherein the search engine accepts a search term that is specified in a language other than the language of the term of the structured vocabulary whose identifier was associated with the media content unit.41. The system of claim 34 wherein a term is ordered by implicitly associating the term with a plurality of other terms.42. The system of claim 34 wherein the search engine normalizes the search term to convert search term variances to a same search term.43. The system of claim 34 wherein the structured vocabulary comprises terms in a second language that correspond to terms expressed in a first language of the structured vocabulary.44. The system of claim 43 wherein the association of an identifier of a term in the first language with a media content unit results in the media content unit being automatically characterized by a corresponding term in the second language.45. The system of claim 34 wherein the search engine disambiguates ambiguous search terms by presenting the relationship of the search term to a plurality of other terms.46. The system of claim 45 wherein the search engine may optionally activate the disambiguation of search terms.47. The system of claim 45 wherein the disambiguated search term is used to locate media content units.48. The system of claim 34, further comprising an index that associates a collection of media content units with a term that characterizes each of the media content units of the collection.49. The system of claim 48 wherein the search engine uses the index to efficiently determine the collection of media content units that are characterized by the search term.50. The system of claim 34 wherein the media content units comprise digital images.51. The system of claim 34 wherein the media content units comprise sound recordings.52. The system of claim 34 wherein the media content units comprise text.53. A method in a computer system for reclassifying media content using a