METHOD AND APPARATUS FOR DYNAMIC GROUPING OF UNSTRUCTURED CONTENT

• US 20110307477A1
• Filed: 06/19/2011
• Published: 12/15/2011
• Est. Priority Date: 10/30/2006
• Status: Abandoned Application

• Current Assignee: Semantifi Incorporated
• Original Assignee: Semantifi Incorporated
• Inventors: Dasari, Viswanath, Pragada, Sreenivasa Rao, Patil, Abhijit Ashok, Gopala Gottumukkala, Raju Venkatta Rama Raju, Aritakula, Kaliki Murthy
• Application Number:
  US13/163,710
• Publication Number:
  US 20110307477A1
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A computer automated method and apparatus for aggregating unstructured content. The method includes the steps of defining a structured data set based upon unstructured content, storing the structured data set into the computer database system, inputting a set of user-defined instructions into a computer database system, inputting a user query including data attributes into the computer database system, mining the structured data set for data relevant to the user query, creating a results data set comprising the data relevant to the user query, and aggregating data in the results data set using domain metrics selected based on any of predefined and configurable rules and past user usage.

Claims

1. A computer automated method of aggregating unstructured content, the method comprising the steps of:

defining a structured data set based upon unstructured content;

storing the structured data set into the computer database system;

inputting a set of user-defined instructions into a computer database system;

inputting a user query including data attributes into the computer database system;

mining the structured data set for data relevant to the user query;

creating a results data set comprising the data relevant to the user query; and

aggregating data in the results data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises;

tagging all data attributes in the results data set based on database metadata and inputs from a user, wherein the data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting the user query, the database metadata for the data attributes in the user query, and attributes specifications; and

reducing the number of the tagged data attributes in the data set by logically eliminating data attributes;

wherein for each of the data attributes in the user query, the tagging process comprises tagging the data attribute as a grouping attribute when the data attribute is to be treated as a grouping attribute based on inputs to any of the computer database system and the database metadata; and

wherein when the data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, the tagging process comprises tagging the data attribute as a grouping attribute.

2. The method of claim 1, further comprising the step of forming one or more groups of unstructured content, each group being associated with a grouping attribute.

3. The method of claim 1, wherein the set of user-defined instructions comprises:

a structured query language (SQL) data format for processing the set of user-defined instructions;

database metadata associated with the data attributes of the computer database system; and

user input instructions identifying instructions of how an attribute is to be grouped.

4. The method of claim 1, further comprising the step of representing the domain metrics as any of database columns and column attributes.

5. The method of claim 1, further comprising the step of categorizing each said data relevant to said user query in said data set into non-overlapping data regions.

6. The method of claim 1, further comprising the step of calculating a number of unique values in said data set associated with a given attribute.

7. The method of claim 6, further comprising the step of determining whether a total number of combinations of said tagged data attributes is greater than a maximum number of combinations of said data attributes.

8. The method of claim 7, further comprising the step of determining whether tagged data attributes exist that are not relevant to said user query.

9. The method of claim 8, further comprising the step of removing the irrelevant tagged data attributes from said data set.

10. The method of claim 9, further comprising the step of removing said tagged data attributes comprising the highest number of said unique values in said data set.

11. The method of claim 1, wherein for each of said data attributes in said user query, said tagging process comprises tagging the data attribute as an ID when said attribute is to be treated as an ID based on inputs to any of said computer database system and said database metadata.

12. The method of claim 1, wherein for each of said data attributes in said user query, said tagging process comprises applying default statistics when user specified statistics are unavailable and tagging the data attribute as a measure when said data attribute is to be treated as a measure based on inputs to any of said computer database system and said database metadata.

13. The method of claim 1, further comprising the step of applying user defined ranges as grouping ranges and tagging said data attribute as a grouping attribute when said user defined ranges are available for said data attribute.

14. The method of claim 13, further comprising the step of determining appropriate grouping ranges based on a distribution of said data attribute.

15. The method of claim 1, wherein for each of said data attributes in said user query, said tagging process comprises checking the data attribute for grouping candidacy and for any available user defined ranges when no information is input as to how said data attribute is to be treated.

16. The method of claim 15, further comprising the step of tagging said data attribute as a grouping attribute when the checking process results in the identification of any of said grouping candidacy and said any available user defined ranges.

17. The method of claim 16, further comprising the step of tagging said data attribute as a measure with default statistics when the checking process results in no identification of any of said grouping candidacy and said any available user defined ranges.

18. A program storage device readable by computer, tangibly embodying a program of instructions executable by said computer to perform an automated method of aggregating and presenting unstructured content, said method comprising the steps of:

defining a structured data set based upon unstructured content;

storing the structured data set into the computer database system;

inputting a set of user-defined instructions into a computer database system;

inputting a user query including data attributes into the computer database system;

mining the structured data set for data relevant to the user query;

creating a results data set comprising the data relevant to the user query; and

aggregating data in the results data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises;

tagging all data attributes in the results data set based on database metadata and inputs from a user, wherein the data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting the user query, the database metadata for the data attributes in the user query, and attributes specifications; and

reducing the number of the tagged data attributes in the data set by logically eliminating data attributes;

wherein for each of the data attributes in the user query, the tagging process comprises tagging the data attribute as a grouping attribute when the data attribute is to be treated as a grouping attribute based on inputs to any of the computer database system and the database metadata; and

wherein when the data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, the tagging process comprises tagging the data attribute as a grouping attribute.

19. A system of aggregating and presenting unstructured content, said system comprising:

a user interface configured to have a set of user-defined instructions including data attributes and a user query input therein;

a structured data set based upon unstructured content;

a computer database system for storing the structured data set, and for mining the structured data set for data relevant to said user query; and

a logic component configured to aggregate data in said structured data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein said logic component is configured to aggregate said data comprises;

a first processing unit configured to tag all data attributes in said structured data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein said first processing unit is configured to receive said user query, said database metadata for said data attributes in said user query, and attributes specifications being input therein; and

a second processing unit adapted to reduce the number of the tagged data attributes in said data set by logically eliminating data attributes;

wherein for each of said data attributes in said user query, said first processing unit is configured to tag the data attribute as an ID when said attribute is to be treated as an ID based on inputs to any of said computer database system and said database metadata, wherein for each of said data attributes in said user query, said first processing unit is configured to apply default statistics when user specified statistics are unavailable and tag the data attribute as a measure when said data attribute is to be treated as a measure based on inputs to any of said computer database system and said database metadata, wherein for each of said data attributes in said user query, said first processing unit is configured to tag the data attribute as a grouping attribute when said data attribute is to be treated as a grouping attribute based on inputs to any of said computer database system and said database metadata, wherein when said data attribute comprises a grouping attribute and has a number of unique values less than the maximum number of unique values allowed to select a database attribute as a grouping attribute, said first processing unit being configured to tag said data attribute as a grouping attribute, wherein said first processing unit is configured to apply user defined ranges as grouping ranges and tag said data attribute as a grouping attribute when said user defined ranges are available for said data attribute, and wherein said first processing unit is configured to determine appropriate grouping ranges based on a distribution of said data attribute.

20. The system of claim 19, wherein said set of user-defined instructions comprise:

a structured query language (SQL) data format for processing said set of user-defined instructions;

database metadata associated with said data attributes of said computer database system; and

user input instructions identifying instructions of how an attribute is to be grouped, wherein said domain metrics are represented as any of database columns and column attributes,

wherein said logic component is configured to categorize each said data relevant to said user query in said data set into non-overlapping data regions, and

wherein said logic component is configured to calculate a number of unique values in said data set associated with a given attribute.