System, process and software arrangement for providing multidimensional recommendations/suggestions

• US 8,185,487 B2
• Filed: 02/12/2002
• Issued: 05/22/2012
• Est. Priority Date: 02/12/2001
• Status: Expired due to Term

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Tuzhilin, Alexander, Adomavicius, Gediminas
• Primary Examiner(s): LY, CHEYNE D
• Application Number:
  US10/468,509
• Publication Number:
  US 20040103092A1
• Time in Patent Office: 3,752 Days
• Field of Search: 707/1, 707/3, 707/100, 715/200, 715/255, 715/273, 715/500, 715/526, 715/530, 715/765, 706/45, 706/62
• US Class Current: 706/47
• CPC Class Codes: G06F 16/244 Grouping and aggregation
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A process, system and computer software are rovided to facilitate at least one recommendation to one or more users (420) and/or one or more applications (430) using multidimensional data (410). In particular, the multidimensional data (410) which define a multidimensional space (400) is accessed. The multidimensional space (400) can have more than two dimensions, each capable of providing variable information. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query (440). This can be performed by generating the recommendation-specific query (440) to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Claims

1. A process executed by a processor for providing at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, comprising the steps of:

a) accessing the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) retrieving information from the multidimensional space; and

c) generating the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, each of which is configured to include a plurality of further attributes, and

wherein at least one of;

each of the dimensions is capable of having a type that is different from a type of another one of the dimensions, or

at least one of the dimensions includes profiles.

2. The process according to claim 1, wherein the multidimensional suggestions are based on multiple factors associated with the at least one of the users and the applications.

3. The process according to claim 1, wherein the retrieved information includes ratings.

4. The process according to claim 3, wherein the ratings include manually-entered ratings previously generated by the at least one of the users and the applications.

5. The process according to claim 4,

wherein the manually-entered ratings are provided for at least one of goods, services and information, and

wherein the at least one recommendation provides further data which relates to the at least one of the goods, the services and the particular information.

6. The process according to claim 4, wherein the manually-entered ratings are provided by the one or more users.

7. The process according to claim 3, further comprising the step of:

d) prior to step (b), filling at least one portion of the multidimensional space with the ratings.

8. The process according to claim 7, wherein the ratings include manually-entered ratings previously generated by the at least one of the users and the applications, and further comprising the steps of:

e) after step (d), determining if the multidimensional space is not substantially or fully filled with the manually-entered ratings, and based on such determination, automatically generating estimated ratings based on the manually-entered ratings; and

f) after step (e), filling at least one unfilled portion of the multidimensional space with the automatically-generated ratings.

9. The process according to claim 8, wherein the automatically-generated ratings relate to the at least one of the goods, the services and the particular information.

10. The process according to claim 3, wherein the ratings include automatically-generated ratings produced based on previously-stored ratings.

11. The process according to claim 3, wherein the multidimensional space represents a set of all possible ratings for the at least one of the goods, the services and the particular information.

12. The process according to claim 1, wherein at least one of the dimensions includes a hierarchy.

20. The process according to claim 1, wherein the at least one recommendation is provided to the at least one of the users and applications.

21. The process according to claim 20, wherein at least one of the dimensions has a hierarchy of elements, wherein the retrieved information includes ratings.

22. The process according to claim 21, wherein at least one of the dimensions includes profiles, and further comprising the step of:

h) determining if the multidimensional space is at least partially not filled with the ratings, and based on such determination, calculating aggregate ratings based on the hierarchy of the profiles.

23. The process according to claim 1, wherein the at least one recommendation is provided for a particular category of at least one of goods, services and certain information.

24. The process according to claim 1, further comprising the step of:

i) prior to step (c), dynamically-selecting a recommendation technique from a set of techniques to generate the at least one recommendation, wherein one or more of the techniques are available for an algorithmic selection from a list of the techniques.

25. The process according to claim 1, wherein the recommendation request-type query is translated into a Structured Query Language query.

26. The process according to claim 1, wherein the multidimensional space includes a multidimensional ratings cube which stores the information to be retrieved therein.

55. The process according to claim 1, wherein the at least one recommendation is generated by issuing a recommendation request-type query, and wherein the recommendation request-type query includes a number of the dimensions which are user-selectable.

59. The process according to claim 1, wherein the dimensions of the at least one multidimensional suggestion are different from the further attributes and from the attributes of the dimensions of the multidimensional space.

13. A process executed by a processor for providing at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, comprising the steps of:

a) accessing the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) retrieving information from the multidimensional space; and

c) generating the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, and

wherein the at least three dimensions of the at least one multidimensional suggestion are related to at least three of the following;

(i) at least one dimension of at least one of users, people, entities or customers,

(ii) at least one dimension of at least one of a place or a location,

(iii) at least one dimension of at least one of a time, a date, a day, a month, a year or a season, or

(iv) at least one dimension of at least one of items, products or services.

14. The process according to claim 13, wherein the profiles have static characteristics.

15. The process according to claim 14, wherein the static profiles include factual information consisting of at least one of fields, variables and records relating to the respective dimension.

16. The process according to claim 15, further comprising the step of:

g) recording each of the static profiles in a data storage arrangement as one record per each dimension.

17. The process according to claim 13, wherein the profiles have dynamic characteristics.

18. The process according to claim 17, wherein the dynamic profiles include at least one set of rules.

19. The process according to claim 17, wherein the dynamic profiles include at least one set of sequences.

56. The process according to claim 13, wherein the at least one recommendation is generated by issuing a recommendation request-type query, and wherein the recommendation request-type query includes a number of the dimensions which are user-selectable.

60. The process according to claim 13, wherein the dimensions of the at least one multidimensional suggestion are different from further attributes thereof and from the attributes of the dimensions of the multidimensional space.

27. A system comprising a processor which, when executed on a processing device, provides at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the system comprising:

a processing subsystem which, when executed on the processing device, configures the processing device to perform the following;

a) access the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes,

b) retrieve information from the multidimensional space, and

c) generate the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, each of which is configured to include a plurality of further attributes, and

wherein at least one of;

each of the dimensions is capable of having a type that is different from a type of another one of the dimensions, or

at least one of the dimensions includes profiles.

28. The system according to claim 27, wherein the multidimensional suggestions are based on multiple factors associated with the at least one of the users and the applications.

29. The system according to claim 27, wherein the retrieved information includes ratings.

30. The system according to claim 29, wherein the ratings include manually-entered ratings previously generated by the at least one of the users and the applications.

31. The system according to claim 30,

wherein the manually-entered ratings are provided for at least one of goods, services and information, and

wherein the at least one recommendation provides further data which relates to the at least one of the goods, the services and the particular information.

32. The system according to claim 30, wherein the manually-entered ratings are provided by the one or more users.

33. The system according to claim 29, wherein the processing subsystem which, when executed on the processing device, configures the processing device to further perform the following:

d) prior to retrieving the information, fill at least one portion of the multidimensional space with the ratings.

34. The system according to claim 33, wherein the ratings include manually-entered ratings previously generated by the at least one of the users and the applications, and wherein the processing subsystem which, when executed on the processing device, configures the processing device to further perform the following:

e) after the at least one portion is filled, determining if the multidimensional space is not substantially or fully filled with the manually-entered ratings, and based on such determination, automatically generate estimated ratings based on the manually-entered ratings, and

f) after the ratings are automatically generated, fill at least one unfilled portion of the multidimensional space with the automatically-generated ratings.

35. The system according to claim 34, wherein the automatically-generated ratings relate to the at least one of the goods, the services and the particular information.

36. The system according to claim 29, wherein the ratings include automatically-generated ratings produced based on previously-stored ratings.

37. The system according to claim 29, wherein the multidimensional space represents a set of all possible ratings for the at least one of the goods, the services and the particular information.

38. The system according to claim 27, wherein at least one of the dimensions includes a hierarchy.

46. The system according to claim 27, wherein the at least one recommendation is provided to the at least one of the users and applications.

47. The system according to claim 46, wherein at least one of the dimensions has a hierarchy of elements, wherein the retrieved information includes ratings.

48. The system according to claim 47, wherein at least one of the dimensions includes profiles, and wherein the processing subsystem which, when executed on the processing device, configures the processing device to further perform the following:

h) determining if the multidimensional space is at least partially not filled with the ratings, and based on such determination, calculate aggregate ratings based on the hierarchy of the profiles.

49. The system according to claim 27, wherein the at least one recommendation is provided for a particular category of at least one of goods, services and certain information.

50. The system according to claim 27, wherein the processing subsystem which, when executed on the processing device, configures the processing device to further perform the following:

i) prior to generating the at least one recommendation, dynamically-select a recommendation technique from a set of techniques to generate the at least one recommendation, wherein one or more of the techniques are available for an algorithmic selection from a list of the techniques.

51. The system according to claim 27, wherein the recommendation request-type query is translated into a Structured Query Language query.

52. The system according to claim 27, wherein the multidimensional space includes a multidimensional ratings cube which stores the information to be retrieved therein.

57. The system according to claim 27, wherein the at least one recommendation is generated by issuing a recommendation request-type query, and wherein the recommendation request-type query includes a number of the dimensions which are user-selectable.

61. The system according to claim 27, wherein the dimensions of the at least one multidimensional suggestion are different from the further attributes and from the attributes of the dimensions of the multidimensional space.

63. The system according to claim 27, wherein the at least three dimensions of the at least one multidimensional suggestion are related to at least three of the following:

(i) at least one dimension of at least one of users, people, entities or customers,

(ii) at least one dimension of at least one of a place or a location,

(iii) at least one dimension of at least one of a time, a date, a day, a month, a year or a season, or

(iv) at least one dimension of at least one of items, products or services.

64. The system according to claim 27, wherein the at least one multidimensional suggestion includes:

(i) a suggestion to at least one of a user, a person, an entity or a customer,

(ii) a suggestion for at least one of an item, a product, or a service, and

(iii) a suggestion at least one of a particular time, a date, a day, a month, a year or a season.

65. The system according to claim 27, wherein the at least one multidimensional suggestion includes:

(i) a suggestion to at least one of a user, a person, an entity or a customer,

(ii) a suggestion for at least one of an item, a product, or a service, and

(iii) a suggestion for at least one of a particular place or a location.

66. The system according to claim 27, wherein the at least one multidimensional suggestion includes at least four dimensions.

67. The system according to claim 65, wherein the at least four dimensions relate to:

(i) at least one of users, people, entities or customers,

(ii) at least one of a place or a location;

(iii) at least one of a time, a date, a day, a month, a year or a season, and

(iv) at least one of items, products or services.

39. A system comprising a processor which, when executed on a processing device, provides at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the system comprising:

a processing subsystem which, when executed on the processing device, configures the processing device to perform the following;

a) access the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information,

b) retrieve information from the multidimensional space and including a plurality of attributes, and

c) generate the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, and

wherein the at least three dimensions of the at least one multidimensional suggestion are related to at least three of the following;

(i) at least one dimension of at least one of users, people, entities or customers,

(ii) at least one dimension of at least one of a place or a location,

(iii) at least one dimension of at least one of a time, a date, a day, a month, a year or a season, or

(iv) at least one dimension of at least one of items, products or services.

40. The system according to claim 39, wherein the profiles have static characteristics.

41. The system according to claim 40, wherein the static profiles include factual information consisting of at least one of fields, variables and records relating to the respective dimension.

42. The system according to claim 41, wherein the processing subsystem which, when executed on the processing device, configures the processing device to further perform the following:

g) record each of the static profiles in a data storage arrangement as one record per each dimension.

43. The system according to claim 39, wherein the profiles have dynamic characteristics.

44. The system according to claim 43, wherein the dynamic profiles include at least one set of rules.

45. The system according to claim 43, wherein the dynamic profiles include at least one set of sequences.

58. The system according to claim 39, wherein the at least one recommendation is generated by issuing a recommendation request-type query, and wherein the recommendation request-type query includes a number of the dimensions which are user-selectable.

62. The system according to claim 39, wherein the dimensions of the at least one multidimensional suggestion are different from further attributes thereof and from the attributes of the dimensions of the multidimensional space.

53. A computer storage medium comprising computer software executable on a processing device to provide at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the computer software comprising:

a) a first module which, when executed by the processing device, accesses the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions configured to provide variable information and configured to include a plurality of attributes;

b) a second module which, when executed by the processing device, retrieves information from the multidimensional space; and

c) a third module which, when executed by the processing arrangement, generates the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, each of which is configured to include a plurality of further attributes, and

wherein at least one of;

each of the dimensions is capable of having a type that is different from a type of another one of the dimensions, or

at least one of the dimensions includes profiles.

54. A computer storage medium comprising computer software executable on a processing device to provide at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the computer software comprising:

a) a first module which, when executed by the processing device, accesses the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions configured to provide variable information and configured to include a plurality of attributes;

b) a second module which, when executed by the processing device, retrieves information from the multidimensional space; and

c) a third module which, when executed by the processing arrangement, generates the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions, and

wherein the at least three dimensions of the at least one multidimensional suggestion are related to at least three of the following;

(i) at least one dimension of at least one of users, people, entities or customers,

(ii) at least one dimension of at least one of a place or a location,

(iii) at least one dimension of at least one of a time, a date, a day, a month, a year or a season, or

(iv) at least one dimension of at least one of items, products or services.

68. A process executed by a processor for providing at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, comprising the steps of:

a) accessing the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) retrieving information from the multidimensional space; and

c) generating the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion that includes the at least three dimensions, and;

(i) a suggestion to at least one of a user, a person, an entity or a customer,

(ii) a suggestion for at least one of an item, a product, or a service, and

(iii) a suggestion at least one of (x) at least one of a particular time, a date, a day, a month, a year or a season, or (y) for at least one of a particular place or a location.

69. A system comprising a processor which, when executed on a processing device, provides at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the system comprising:

a processing subsystem which, when executed on the processing device, configures the processing device to perform the following;

a) access the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes,

b) retrieve information from the multidimensional space, and

c) generate the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion that includes the at least three dimensions and;

(i) a suggestion to at least one of a user, a person, an entity or a customer,

(ii) a suggestion for at least one of an item, a product, or a service, and

(iii) a suggestion at least one of (x) at least one of a particular time, a date, a day, a month, a year or a season, or (y) for at least one of a particular place or a location.

71. The system according to claim 69, wherein the user-specifiable multidimensional query includes dimensions which are user-specifiable.

72. The system according to claim 69, wherein the user-specifiable multidimensional query includes a number of dimensions which are user-specifiable.

70. A computer storage medium comprising computer software executable on a processing device to provide at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the computer software comprising:

a) a first module which, when executed by the processing device, accesses the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) a second module which, when executed by the processing device, retrieves information from the multidimensional space; and

c) a third module which, when executed by the processing arrangement, generates the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion that includes the at least three dimensions and;

(i) a suggestion to at least one of a user, a person, an entity or a customer,

(ii) a suggestion for at least one of an item, a product, or a service, and

(iii) a suggestion at least one of (x) at least one of a particular time, a date, a day, a month, a year or a season, or (y) for at least one of a particular place or a location.

73. A process executed by a processor for providing at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, comprising the steps of:

a) accessing the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) retrieving information from the multidimensional space; and

c) generating the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three four dimensions that relate to;

(i) at least one of users, people, entities or customers,

(ii) at least one of a place or a location;

(iii) at least one of a time, a date, a day, a month, a year or a season, and

(iv) at least one of items, products or services.

74. A system comprising a processor which, when executed on a processing device, provides at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the system comprising:

a processing subsystem which, when executed on the processing device, configures the processing device to perform the following;

a) access the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes,

b) retrieve information from the multidimensional space, and

c) generate the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three dimensions that relate to;

(i) at least one of users, people, entities or customers,

(ii) at least one of a place or a location;

(iii) at least one of a time, a date, a day, a month, a year or a season, and

(iv) at least one of items, products or services.

75. A computer storage medium comprising computer software executable on a processing device to provide at least one recommendation to at least one of one or more users and one or more applications using multidimensional data, the computer software comprising:

a) a first module which, when executed by the processing device, accesses the multidimensional data which define a multidimensional space, the multidimensional space having at least three dimensions, the multidimensional space being defined by a Cartesian product of the dimensions, each of the dimensions being configured to provide variable information and configured to include a plurality of attributes;

b) a second module which, when executed by the processing device, retrieves information from the multidimensional space; and

c) a third module which, when executed by the processing arrangement, generates the at least one recommendation based on the retrieved information,

wherein the at least one recommendation includes at least one multidimensional suggestion, the at least one multidimensional suggestion including the at least three few dimensions that relate to;

(i) at least one of users, people, entities or customers,

(ii) at least one of a place or a location;

(iii) at least one of a time, a date, a day, a month, a year or a season, and

(iv) at least one of items, products or services.