Business intelligence data models with concept identification using language-specific clues

• US 10,157,175 B2
• Filed: 03/15/2013
• Issued: 12/18/2018
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Grosset, Robin N., Rais-Ghasem, Mohsen, Watts, Graham A., Wei, Qing
• Primary Examiner(s): OBISESAN, AUGUSTINE KUNLE
• Application Number:
  US13/844,587
• Publication Number:
  US 20140278364A1
• Time in Patent Office: 2,104 Days
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 40/258 Heading extraction; Automatic titling; Numbering
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Claims

1. A computer system comprising:

one or more processors, one or more computer-readable memories, and one or more computer-readable, tangible storage devices;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare a data item heading from a data source with concept keywords in a concept library, wherein the data item heading is associated with a set of data items in the data source, and the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts, wherein the concept library is tailored to a particular business ontology of a particular business;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify the data item heading as being associated with the particular concept;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to validate the one or more matches between the data item heading and the one or more concept keywords associated with the particular concept;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to apply a concept tag in association with the data item heading, wherein the concept tag indicates the particular concept with which the data item heading is identified as being associated; and

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to output for display the concept tag in association with the data item heading to a business intelligence user interface web application, wherein the business intelligent web application uses the concept tag to determine a data analytics interface output mode for creation of a data visualization of one or more variables in relation to entries corresponding to the particular concept,

wherein validating the one or more matches between the data item heading and the one or more concept keywords associated with the particular concept comprises assigning priority to the particular concept based on a number of matches between the one or more concept keywords associated with the particular concept in the particular business ontology and the data item heading, and

wherein assigning priority to the particular concept based on the number of matches between the one or more concept keywords associated with the particular concept in the particular business ontology and the data item heading comprises identifying whether the one or more concept keywords associated with the particular concept provides a highest number of matches with the data item heading of any concept in the concept library.

2. The computer system of claim 1, further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify one or more tokens based on the data item heading; and

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare the one or more tokens based on the data item heading with the one or more concept keywords in the concept library.

3. The computer system of claim 1, further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify one or more alternate strings based on a word stem of the data item heading;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare the one or more alternate strings based on the word stem of the data item heading with the one or more concept keywords in the concept library;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify one or more near matches of the data item heading;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare the one or more near matches of the data item heading with the one or more concept keywords in the concept library;

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify one or more alternate language clues associated with the data item heading, wherein the one or more alternate language clues comprise content in one or more alternate languages besides a primary language of the data item heading; and

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare the one or more alternate language clues associated with the data item heading with the one or more concept keywords in the concept library.

4. The computer system of claim 3, further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein identifying the one or more tokens based on the data item heading comprises applying a trie-based tokenizer to the data item heading.

5. The computer system of claim 1, wherein the data item heading is a first data item heading, and wherein the additional evidence from the data source comprises one or more of:

values of data associated with the first data item heading, patterns of data associated with the first data item heading, and additional data item headings comparable to the first data item heading.

6. The computer system of claim 1, wherein the concept library comprises concept clues in a first language and in a second language, the computer system further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to use lexical clues specific to the first language for a data set with content in the alternate language, and to use lexical clues specific to the second language for a data set with content in the second language.

7. The computer system of claim 1, further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify a primary language of the data item heading, wherein the one or more of the concept keywords in the at least one language comprise one or more concept keywords in the primary language; and

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to compare the data item heading with the one or more concept keywords in the primary language.

8. The computer system of claim 1, further comprising:

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify a data analytics interface output mode that corresponds to the particular concept; and

program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to output, in a business intelligence interface, the data analytics interface output mode identified as corresponding to the particular concept.

9. The computer system of claim 8, wherein the particular concept comprises time, and the data analytics interface output mode identified as corresponding to the particular concept comprises a data visualization of one or more variables in relation to time.

10. The computer system of claim 8, wherein the particular concept comprises names, and the data analytics interface output mode identified as corresponding to the particular concept comprises a data visualization of one or more variables in relation to entries corresponding to the names.

11. The computer system of claim 1, wherein the data item heading comprises one or more of a column heading, a row heading, a sheet name, and a graph caption from the data source.

12. A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by a computing device to:

compare a data item heading from a data source with concept keywords in a concept library, wherein the data item heading is associated with a set of data items in the data source, and the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts, wherein the concept library is tailored to a particular business ontology of a particular business;

identify one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library;

identify the data item heading as being associated with the particular concept;

validate the one or more matches between the data item heading and the one or more concept keywords associated with the particular concept;

apply a concept tag in association with the data item heading, wherein the concept tag indicates the particular concept with which the data item heading is identified as being associated; and

output for display the concept tag in association with the data item heading to a business intelligence web application, wherein the business intelligent web application uses the concept tag to determine a data analytics interface output mode for creation of a data visualization of one or more variables in relation to entries corresponding to the particular concept,

wherein validating the one or more matches between the data item heading and the one or more concept keywords associated with the particular concept comprises assigning priority to the particular concept based on a number of matches between the one or more concept keywords associated with the particular concept in the particular business ontology and the data item heading, and

wherein assigning priority to the particular concept based on the number of matches between the one or more concept keywords associated with the particular concept in the particular business ontology and the data item heading comprises identifying whether the one or more concept keywords associated with the particular concept provides a highest number of matches with the data item heading of any concept in the concept library.

13. The computer program product of claim 12, further comprising program code executable by a computing device to:

identify one or more tokens based on the data item heading; and

compare the one or more tokens based on the data item heading with the one or more concept keywords in the concept library.

14. The computer program product of claim 12, further comprising program code executable by a computing device to:

identify one or more alternate strings based on a word stem of the data item heading;

compare the one or more alternate strings based on the word stem of the data item heading with the one or more concept keywords in the concept library;

identify one or more near matches of the data item heading;

compare the one or more near matches of the data item heading with the one or more concept keywords in the concept library;

identify one or more alternate language clues associated with the data item heading, wherein the one or more alternate language clues comprise content in one or more alternate languages besides a primary language of the data item heading; and

compare the one or more alternate language clues associated with the data item heading with the one or more concept keywords in the concept library.

15. The computer program product of claim 14, wherein identifying the one or more tokens based on the data item heading comprises applying a tie-based tokenizer to the data item heading.

16. The computer program product of claim 12, wherein the data item heading is a first data item heading, and wherein the additional evidence from the data source comprises one or more of:

values of data associated with the first data item heading, patterns of data associated with the first data item heading, and additional data item headings comparable to the first data item heading.

17. The computer program product of claim 12, wherein the concept library comprises concept clues in a first language and in a second language, further comprising program code executable by a computing device to:

use lexical clues specific to the first language for a data set with content in the alternate language, and use lexical clues specific to the second language for a data set with content in the second language.

18. The computer program product of claim 12, further comprising program code executable by a computing device to:

identify a primary language of the data item heading, wherein the one or more of the concept keywords in the at least one language comprise one or more concept keywords in the primary language; and

compare the data item heading with the one or more concept keywords in the primary language.