Method and system to analyze rules based on aspect-value coverage

Abstract

There is provided methods and systems to provide aspect-value coverage. First, the system receives a first plurality of data items from a database utilized by an information storage and retrieval platform. Next, the system applies a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain. Next, the system counts the second plurality of data items respectively to determine a total quantity of data items. Next, the system applies a second plurality of rules to the second plurality of data items to identify a third plurality of data items that contain matching information identified by the respective rule. Next, the system associates the third plurality of data items with a first aspect-value pair based on the respective rule. Next, the system counts the third plurality of data items respectively to determine a first quantity of data items. Next, the system determines a percentage of coverage for the first aspect-value pair, the percentage coverage based on the first quantity of data items and the total quantity of data items. Finally, the system provides the percentage coverage for the first aspect-value pair as an interface element within an interface.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

An embodiment is illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which:

FIG. 1 is a network diagram depicting a system, according to one example embodiment, having a client-server architecture;

FIG. 2 is a block diagram illustrating modules and engines, according to an embodiment;

FIG. 3 is a block diagram illustrating authoring modules, according to an embodiment;

FIG. 4 is a block diagram illustrating an information storage and retrieval platform, according to an embodiment;

FIG. 5 is a diagram illustrating an example domain structure, according to one embodiment;

FIG. 6 is a table illustrating sell-side data and buy-side data, according to one embodiment;

FIG. 7 is a diagram illustrating a canonical matching concept, according to an embodiment;

FIG. 8A is a block diagram illustrating databases, according to an embodiment;

FIG. 8B is a block diagram illustrating additional databases, according to an embodiment;

FIG. 9A is a block diagram illustrating classification information, according to an embodiment;

FIG. 9B is a block diagram illustrating production classification information, according to an embodiment;

FIG. 9C is a block diagram illustrating preview classification information, according to an embodiment;

FIG. 10 is a diagram illustrating rules, according to an embodiment;

FIG. 11 is a block diagram illustrating data item information, according to an embodiment;

FIG. 12 is a block diagram illustrating a search index engine, according to an embodiment;

FIG. 13A is a block diagram illustrating a data item search information, according to an embodiment;

FIG. 13B is a block diagram illustrating a sample data item search information, according to an embodiment;

FIG. 14 is a block diagram illustrating query information, according to an embodiment;

FIG. 15 is a block diagram illustrating data item criteria, according to an embodiment;

FIG. 16 is a block diagram illustrating preview publish information, according to an embodiment;

FIG. 17 is a block diagram illustrating most popular query information, according to an embodiment;

FIG. 18 is a block diagram illustrating histogram information, according to an embodiment;

FIG. 19 is a flow chart illustrating a method to generate rules to identify data items, according to an embodiment;

FIG. 20 is a flowchart illustrating a method, according to an embodiment, to represent percentage of coverage for a subset of most popular queries;

FIG. 21 is a flowchart illustrating a method, according to an embodiment, to apply aspect rules to most popular queries;

FIG. 22 is a flowchart illustrating a method, according to an embodiment, to determine percentage coverage for most popular queries;

FIG. 23 is a flowchart illustrating a method, according to an embodiment, to represent percentage coverage associated with a domain;

FIG. 24 is a flowchart illustrating a method, according to an embodiment, to apply domain rules to data items;

FIG. 25 is a flowchart illustrating a method, according to an embodiment, to determine domains;

FIG. 26 is a flowchart illustrating a method, according to an embodiment, to represent percentage coverage for aspects;

FIG. 27 is a flowchart illustrating a method, according to an embodiment, to apply aspect rules to data items;

FIG. 28 is a flowchart illustrating a method, according to an embodiment, to determine percentage coverage for aspects;

FIG. 29 is a flowchart illustrating a method, according to an embodiment, to represent percentage coverage for aspect-value pairs;

FIG. 30 is a flowchart illustrating a method, according to an embodiment to determine percentage coverage for aspect-value pairs;

FIGS. 31-38 are diagrams illustrating user interfaces, according to an embodiment;

FIG. 39 is a block diagram illustrating marketplace applications, according to an embodiment;

FIG. 40 is a block diagram illustrating marketplace information, according to an embodiment; and

FIG. 41 is a block diagram of a machine, according to an example embodiment, including instructions to perform any one or more of the methodologies described herein.

Claims

1. A system including: a data item retrieval module to receive a first plurality of data items from a database utilized by an information storage and retrieval platform;a classification service engine to apply a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, the second plurality of data items respectively counted to determine a total quantity of data items, the classification service engine to apply a second plurality of rules to the second plurality of data items to identify a third plurality of data items that contain matching information identified by the respective rule, the third plurality of data items associated with a first aspect-value pair based on the respective rule, the third plurality of data items respectively counted to determine a first quantity of data items; andan aspect-value coverage module to determine a percentage of coverage for the first aspect-value pair, the percentage coverage based on the first quantity of data items and the total quantity of data items, the percentage coverage for the first aspect-value pair to be provided as an interface elements within an interface.

2. The system of claim 1, wherein the information storage and retrieval platform includes a network based marketplace, wherein the first plurality data items are offered by a seller on the network-based marketplace.

3. The system of claim 1, wherein the matching information includes any one selected from a group consisting of matching information including a first category, a first keyword, and a first item-specific.

4. The system of claim 3, wherein the second plurality of data items includes a first data item that contains the first keyword in a title.

5. The system of claim 1, wherein the classification service engine is to identify a fourth plurality of data items that contain matching information, the fourth plurality of data items associated with a second aspect-value pair that includes the first aspect, the fourth plurality of data items respectively counted to determine a second quantity of data items, wherein the aspect-value coverage module is to determine a percentage of coverage for the second aspect-value pair, the percentage coverage based on the second quantity of data items and the total quantity of data items.

6. The system of claim 1, further including a processing module to publish the second plurality of rules to a network-based marketplace that is utilized by a buyer and a seller to transact a data item.

7. The system of claim 1, wherein the first plurality of data items includes any one selected from a group consisting of current data items, a seasonal data items, and historical data items.

8. The system of claim 1, wherein the first plurality of rules includes a first rule that includes a condition clause and a predicate clause.

9. The system of claim 9, wherein the predicate clause assigns the first domain to a data item based on the condition clause.

10. The system of claim 10, wherein the first domain includes a product type domain.

11. The system of claim 9, wherein the condition clause determines whether a data item contains a first category.

12. A method including: receiving a first plurality of data items from a database utilized by an information storage and retrieval platform;applying a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, the second plurality of data items respectively counted to determine a total quantity of data items;applying a second plurality of rules to the second plurality of data items to identify a third plurality of data items that contain matching information identified by the respective rule, the third plurality of data items associated with a first aspect-value pair based on the respective rule, the third plurality of data items respectively counted to determine a first quantity of data items; anddetermining a percentage of coverage for the first aspect-value pair, the percentage coverage based on the first quantity of data items and the total quantity of data items, the percentage coverage for the first aspect-value pair to be provided as an interface elements within an interface.

13. The method of claim 12, wherein the information storage and retrieval platform includes a network based marketplace, wherein the first plurality data items are offered by a seller on the network-based marketplace.

14. The method of claim 12, wherein the matching information includes any one selected from a group consisting of f matching information including a first category, a first keyword, and a first item-specific.

15. The method of claim 14, wherein the second plurality of data items includes a first data item that contains the first keyword in a title.

16. The method of claim 12, wherein the applying the second plurality of rules includes identification of a fourth plurality of data items that contain matching information, the fourth plurality of data items associated with a second aspect-value pair that includes the first aspect, the fourth plurality of data items respectively counted to determine a second quantity of data items; determining a percentage of coverage for the second aspect-value pair, the percentage coverage based on the second quantity of data items and the total quantity of data items.

17. The method of claim 12, further including publishing the second plurality of rules to a network-based marketplace that is utilized by a buyer and a seller to transact a data item.

18. The method of claim 12, wherein the first plurality of data items includes any one selected from a group consisting of current data items, a seasonal data items, and historical data items.

19. The method of claim 12, wherein the first plurality of rules includes a first rule that includes a condition clause and a predicate clause.

20. The method of claim 19, wherein the predicate clause assigns the first domain to a data item based on the condition clause.

21. The method of claim 20, wherein the first domain includes a product type domain.

22. The method of claim 19, wherein the condition clause determines whether a data item contains a first category.

23. A system including: a first means for receiving a first plurality of data items from a database utilized by an information storage and retrieval platform;a second means for applying a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, the second plurality of data items respectively counted to determine a total quantity of data items, the a second means for applying a second plurality of rules to the second plurality of data items to identify a third plurality of data items that contain matching information identified by the respective rule, the third plurality of data items associated with a first aspect-value pair based on the respective rule, the third plurality of data items respectively counted to determine a first quantity of data items; anda third means for determining a percentage of coverage for the first aspect-value pair, the percentage coverage based on the first quantity of data items and the total quantity of data items, the percentage coverage for the first aspect-value pair to be provided as an interface elements within an interface.

24. A tangible machine readable medium storing a set of instructions that, when executed by a machine, cause the machine to: receive a first plurality of data items from a database utilized by an information storage and retrieval platform;apply a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, the second plurality of data items respectively counted to determine a total quantity of data items;apply a second plurality of rules to the second plurality of data items to identify a third plurality of data items that contain matching information identified by the respective rule, the third plurality of data items associated with a first aspect-value pair based on the respective rule, the third plurality of data items respectively counted to determine a first quantity of data items; anddetermine a percentage of coverage for the first aspect-value pair, the percentage coverage based on the first quantity of data items and the total quantity of data items, the percentage coverage for the first aspect-value pair to be provided as an interface elements within an interface.