1. A computer implemented method of producing a cross tabulation structure, the method comprising:
issuing by the computer a plurality of queries to a database in communication with the computer, the queries being for multiple sub-levels of data for multiple dimensions of data associated with records in the database to provide sub-lists of sorted record identifiers for the queries, the sub-lists having associated cursors pointing to entries in the sub-lists; and
determining by the computer occurrences of intersections of levels of a first dimension of the data associated with records in the database with levels of a second dimension of the data associated with records in the database, by traversing the sub-lists to determine matching record identifiers of sub-lists for the first and second dimensions and incrementing the cursors after the intersection is detected for the first and second dimensions to have the cursors point to subsequent record identifiers in each of the sub-lists until each cursor points to a last record identifier in the sub-lists; and
producing the cross tabulation structure from the determined occurrences of intersections.
2. The method of claim 1 further comprising: sorting by record identifiers results from the queries into the corresponding plurality of sub-lists.
3. The method of claim 1 wherein producing comprises computing an aggregate of the intersections and populating the cross-tabulation structure.
4. The method of claim 1 wherein the data has two dimensions and the two dimensions are the first and the second dimensions.
5. The method of claim 1 wherein determining produces a cross-tabulation of counts of occurrences of records in the database that have intersecting levels of data for different dimensions of records in the fields.
6. The method of claim 1 wherein issuing issues queries of the form \u201cSelect <Audience ID(s)> from<DB table> where <query condition> order by <Audience ID(s)>\u201d to the database to retrieve audience IDs that satisfy the query.
7. The method of claim 6 wherein the audience ID is a customer identifier and dimensions of data are attributes of customers.
8. The method of claim 1 wherein the audience ID’ are customer ID’s and attributes are age and income and the query searches the database to retrieve Customer ID’s over sub-levels of ages and sub-levels of income.
9. The method of claim 1 wherein determining provides values to indicate how many records exist in each combination of dimension sub-levels.
10. The method of claim 4 wherein issuing issues N queries to produce N sub-lists of audience ID’s that are in an first dimension bracket 1 to first dimension bracket N and issues M queries to produce M sub-lists of audience ID’s that are in second dimension bracket 1 to second dimension bracket M.
11. The method of claim 3 wherein computing an aggregate of occurrences comprises finding a cross tabulation between the first dimension and the second dimension to populate a N\xd7M cross-tabulation structure.
12. The method of claim 11 wherein computing an aggregate further comprises:
merging each sub-list using corresponding cursors to track an occurrence of a audience ID in the sub lists that matches a current audience ID in a master list of audience ID’s, and for each occurrence of a matching audience ID accumulating in a corresponding cell of the cross-tabulation structure a count of audience ID’s forms an intersection of first and second dimension sub-levels.
13. The method of claim 11 wherein each cell of the structure is an intersection corresponding to the sub-level under each dimension of the N\xd7M structure, and the cell is populated with a value that represents the number of times that there was an intersection common audience r ID between a sub-level of the first dimension and a sub-level of the second dimension.
14. The method of claim 1 wherein determining is performed over groups of cells.
15. The method of claim 1 wherein sub-lists of sorted record identifiers for the same dimension are periodically pre-computed for the entire population.
16. The method of claim 1 wherein determining further comprises calculating sums, average counts, minimum counts, maximum counts, or a standard deviation of another intersecting dimension.
17. The method of claim 16 wherein a variable that calculating is performed on, is returned as part of a master list and is referenced for subsequent computations.
18. The method of claim 1 wherein if the levels are mutually exclusive determining an occurrence in one sub-list allows the process to skip remaining sub-list in dimension and move to finding an occurrence in a succeeding dimension.
19. The method of claim 1 wherein if a dimension has multiple hierarchical levels that can be rolled up from lower levels, only queries for the lowest level of granularity are executed.
20. The method of claim 1 wherein the dimensions of data are recency of purchase, frequency of purchase and an aggregate of amount of purchases so called \u201cRFM\u201d characteristics of customer historical behavior.
21. A computer program product residing on a computer readable medium for producing a cross tabulation structure, the computer program comprising instructions for causing a computer to:
issue a plurality of queries to a database, the queries being for multiple sub-levels of data for multiple dimensions of data associated with records in the database to provide sub-lists of sorted record identifiers for the queries, the sub-lists having associated cursors pointing to entries in the sub-lists;
determine occurrences of intersections of levels of a first dimension of the data associated with records in the database with levels of a second dimension of the data associated with records in the database, by traversing the sub-lists to determine matching record identifiers of sub-lists for the first and second dimensions, and incrementing the cursors after the intersection is detected for the first and second dimensions to have the cursors point to subsequent record identifiers in each of the sub-lists until each cursors points to a last record identifier in the sub-lists; and
produce the cross-tabulation structure from the determined occurrences of intersections, the cross-tabulation structure indicating each time an intersection of the first dimension with levels of the second dimension of the data is found.
22. The method of claim 21 further comprising instructions to: sort by record identifiers results from the queries into the corresponding plurality of sub-lists.
23. The computer program product of claim 21 wherein instructions to produce comprise instructions to compute an aggregate of the intersections and populate the cross-tabulation structure with the aggregate.
24. The computer program product of claim 21 wherein the data has two dimensions and the two dimensions are the first and the second dimensions.
25. The computer program product of claim 21 wherein instructions to issue queries issues queries of the form \u201cSelect<Audience ID(s)> from <DB table> where <query condition> order by <Audience ID(s)>\u201d to the database to retrieve audience IDs that satisfy the query.
26. The computer program product of claim 21 wherein the audience ID is a customer identifier and dimensions of data are attributes of customers.
27. The computer program product of claim 21 wherein the audience ID’ are customer ID’s and attributes are age and income and the query searches the database to retrieve Customer ID’s over sub-levels of ages and sub-levels of income.
28. The computer program product of claim 21 wherein instructions to issue, issues N queries to produce N sub-lists of audience ID’s that are in an first dimension bracket 1 to first dimension bracket N and issues M queries to produce M sub-lists of audience ID’s that are in second dimension bracket 1 to second dimension bracket M.
29. The computer program product of claim 23 wherein instructions to compute, further comprise instructions, to compute an aggregate of occurrences to find a cross tabulation between the first dimension and the second dimension to populate a N\xd7M cross-tabulation structure.
30. The computer program product of claim 29 wherein instructions to compute an aggregate further comprises instructions to:
merge each sub-list using corresponding cursors to track an occurrence of a audience ID in the sub-lists that matches a current audience ID in a master list of audience ID’s, and for each occurrence of a matching audience ID accumulating in a corresponding cell of the cross-tabulation structure a count of audience ID’s forms an intersection of first and second dimension sub-levels.
31. The computer program product of claim 21 wherein instructions to determine are performed over groups of cells.
32. The computer program product of claim 21 wherein sub-lists of sorted record identifiers for the same dimension arc periodically pre-computed for the entire population.
33. The computer program product of claim 21 wherein instructions to determine further comprise instructions to calculate sums, average counts, minimum counts, maximum counts, or a standard deviation of another intersecting dimension.
34. The computer program product of claim 33 wherein a variable that calculating is performed on is returned as part of a master list and is referenced for subsequent computations.
35. The computer program product of claim 21 wherein if the levels are mutually exclusive instructions to determine an occurrence in one sub-list allows the process to skip remaining sub-lists in the dimension and move to find an occurrence in a succeeding dimension.
36. The computer program product of claim 21 wherein if a dimension has multiple hierarchical levels that can be rolled up from lower levels, only queries for the lowest level of granularity are executed.
37. The computer program product of claim 21 wherein the dimensions of data are recency of purchase, frequency of purchase and an aggregate of amount of purchases so called \u201cRFM\u201d characteristics of customer historical behavior.
38. Apparatus, comprising:
a processor,
a memory coupled to the processor, and
a computer storage medium, storing a computer program product for producing a cross tabulation structure, the computer program comprising instructions which when executed in memory by the processor, causing the apparatus to:
issue a plurality of queries to a database, the queries being for multiple sub-levels of data for multiple dimensions of data associated with records in the database to provide sub-lists of sorted record identifiers for the queries, the sub-lists having associated cursors pointing to entries in the sub-lists;
determine occurrences of intersections of levels of a first dimension of the data associated with records in the database with levels of a second dimension of the data associated with records in the database, by traversing the sub-lists to determine matching record identifiers of sub-lists for of the first and second dimensions, and incrementing the cursors after the intersection is detected for the first and second dimensions to have the cursors point to subsequent record identifiers in each of the sub-lists until each cursor points to a last record identifier in the sub-lists; and
produce the cross-tabulation structure from the determined occurrences of intersections, the cross-tabulation structure indicating each time an intersection of the first dimension with levels of the second dimension of the data is found.
39. The apparatus of claim 38 wherein instructions to produce comprise instructions to compute an aggregate of the intersections and populate the cross-tabulation structure with the aggregate.
40. The apparatus of claim 38 wherein instructions to issue, issues N queries to produce N sub-lists of audience ID\u2032s that are in an first dimension bracket 1 to first dimension bracket N and issues M queries to produce M sub-lists of audience ID’s that are in second dimension bracket 1 to second dimension bracket M.
41. The apparatus of claim 39 wherein instructions to compute, further comprise instructions to compute an aggregate of occurrences to find a cross tabulation between the first dimension and the second dimension to populate a N\xd7M cross-tabulation structure.
42. The apparatus of claim 41 wherein instructions to compute an aggregate further comprises instructions to:
merge each sub-list using corresponding cursors to track an occurrence of a audience ID in the sub-lists that matches a current audience ID in a master list of audience ID’s, and for each occurrence of a matching audience ID accumulating in a corresponding cell of the cross-tabulation structure a count of audience ID’s forms an intersection of first and second dimension sub-levels.
43. The apparatus of claim 38 wherein instructions to determine are performed over groups of cells.
44. The apparatus of claim 38 wherein sub-lists of sorted record identifiers for the same dimension are periodically pre-computed for the entire population.
45. The apparatus of claim 38 wherein instructions to determine further comprise instructions to calculate sums, average counts, minimum counts, maximum counts, or a standard deviation of another intersecting dimension.
46. The apparatus of claim 45 wherein a variable that calculating is performed on is returned as part of a master list and is referenced for subsequent computations.
47. The apparatus of claim 38 wherein if the levels are mutually exclusive instructions to determine an occurrence in one sub-list allows the process to skip remaining sub-lists in the dimension and move to find an occurrence in a succeeding dimension.
48. The apparatus of claim 38 wherein if a dimension has multiple hierarchical levels that can be rolled up from lower levels, only queries for the lowest level of granularity are executed.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of fabricating an image sensor device, comprising:
providing a substrate having a first side and a second side, the substrate containing a silicon material;
forming a radiation-sensitive element in the substrate, the radiation-sensitive element being configured to detect radiation that enters the substrate through the second side;
thereafter thinning the substrate from the second side;
implanting a dopant to the thinned substrate from the second side; and
after the implanting, performing an annealing process to form recrystallized silicon in a first portion of the thinned substrate near the second side.
2. The method of claim 1, wherein the annealing process comprises melting the silicon material in the first portion of the substrate and causing the melted silicon material to recrystallize, thereby forming the recrystallized silicon.
3. The method of claim 1, wherein the implanting is performed using:
an implantation energy between about 0.1 KeV and about 10 KeV; and
an implantation dosage between about 1\xd71012 atomscm2 and about 1\xd71015 atomscm2.
4. The method of claim 1, wherein the implanting and the annealing process are performed such that the first portion of the substrate is within a thickness range between about 5 nanometers and about 200 nanometers.
5. The method of claim 1, wherein the annealing process is performed:
at an annealing energy level in a range between about 0.5 Jcm2 to about 5 Jcm2; and
at a time duration between about 10 nanoseconds and about 1000 nanoseconds.
6. The method of claim 1, wherein the annealing process includes a laser annealing process.
7. The method of claim 1, further comprising, before the thinning:
forming an interconnect structure over the first side of the substrate; and
bonding the substrate to a carrier substrate such that the interconnect structure is disposed between the substrate and the carrier substrate.
8. The method of claim 1, further comprising, after the performing of the annealing process:
forming an anti-reflective layer over the second side of the thinned substrate;
forming a color filter over the anti-reflective layer; and
forming a microlens over the color filter.
9. A method of fabricating an image sensor device, comprising:
providing a substrate having a first side and a second side, the substrate containing a silicon material;
forming a light-sensing element in the substrate, the light-sensing element being configured to sense light that enters the substrate through the second side;
forming an interconnect structure over the second side of the substrate;
bonding the second side of the substrate to a carrier substrate;
thinning, after the bonding, the substrate from the second side;
implanting a dopant to the thinned substrate from the second side; and
thereafter performing a laser annealing an process to form melted and recrystallized silicon in a portion of the thinned substrate near the second side.
10. The method of claim 9, wherein the implanting is performed using:
an implantation energy between about 0.1 KeV and about 10 KeV; and
an implantation dosage between about 1\xd71012 atomscm2 and about 1\xd71015 atomscm2.
11. The method of claim 9, wherein the implanting and the annealing process are performed such that the portion of the substrate is within a thickness range between about 5 nanometers and about 200 nanometers.
12. The method of claim 9, wherein the annealing process is performed:
at an annealing energy level in a range between about 0.5 Jcm2 to about 5 Jcm2; and
at a time duration between about 10 nanoseconds and about 1000 nanoseconds.
13. A method of fabricating an image sensor device, comprising:
providing a substrate having a front side and a back side;
forming a radiation-sensing region in the substrate, the radiation-sensing region being operable to sense radiation projected toward the radiation-sensing region through the back side; and
thereafter annealing the substrate in a manner so that a portion of the substrate near the back side is melted.
14. The method of claim 13, further comprising: before the annealing, implanting a dopant into the substrate from the back side.
15. The method of claim 14, wherein the implanting and the annealing are carried out in a manner so that the portion of substrate that is melted has a thickness than is in a range from approximately 5 nanometers to approximately 200 nanometers.
16. The method of claim 14, wherein the implanting includes:
using an implantation energy that is in a range from approximately 0.1 KeV to approximately 50 KeV; and
using an implantation dosage that is in a range from approximately 1\xd71012 atomscm2 to approximately 1\xd71015 atomscm2.
17. The method of claim 14, wherein the implanting and the annealing are carried out in a manner so that:
the portion of the substrate is a first portion and has a first range of dopant concentration values;
a second portion of the substrate that is mutually exclusive from the first portion has a second range of dopant concentration values; and
each of the dopant concentration values in the first range is substantially greater than each of the dopant concentration values in the second range.
18. The method of claim 17, wherein each of the dopant concentration values in the first and second ranges is measured at, and associated with, a respective distance from the back side; and wherein:
the dopant concentration values of the first portion of the substrate are each free of correlation with their associated distances and are within approximately one order of magnitude of one another; and
the dopant concentration values of the second portion of the substrate are each inversely correlated with their associated distances.
19. The method of claim 13, wherein the annealing includes performing a laser annealing process at an annealing temperature that is greater than approximately 1414 degrees Celsius.
20. The method of claim 13, further comprising, before the annealing:
forming an interconnect structure over the front side;
bonding a carrier substrate to the interconnect structure; and
thinning the substrate from the back side.