Data semanticizer

• US 20060136194A1
• Filed: 12/20/2004
• Published: 06/22/2006
• Est. Priority Date: 12/20/2004
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Song, Zhexuan, Masuoka, Ryusuke, Hashmi, Nada, Armstrong, Patrick Joseph, Lee, Sung Youn
• Granted Patent: US 8,065,336 B2
• Time in Patent Office: Days
• US Class Current: 704/4
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A computer-implemented method of defining a set of annotation elements to map a concept to electronic data as input data; generating a mapping rule, according to the set of annotation elements defined and a sample of the input data; mapping the concept to the input data by applying the mapping rule to the input data; and generating a semantic instance of the input data based upon the mapping of the concept to the input data. The set of annotation elements to map the concept to the input data are a selected ontology corresponding to the input data, a selected ontology concept from the selected ontology, a mapping of a word or word phrase in the sample input data to the selected ontology concept from the selected ontology, and a pattern of the mapped word or word phrase relative to a structure of the sample input data.

Claims

1. A computer-implemented method, comprising:

defining a set of annotation elements to map a concept to electronic data as input data;

generating a mapping rule, according to the set of annotation elements defined and a sample of the input data;

mapping the concept to the input data by applying the mapping rule to the input data; and

generating a semantic instance of the input data based upon the mapping of the concept to the input data.

2. The method of claim 1, wherein the set of annotation elements to map the concept to the input data comprises a selected ontology corresponding to the input data, a selected ontology concept from the selected ontology as the concept to map, a mapping of a word or word phrase in the sample input data to the selected ontology concept from the selected ontology, and a pattern of the mapped word or word phrase relative to a structure of the sample input data.

3. The method of claim 1, wherein the generating of the mapping rule comprises:

suggesting a sample mapping of the concept to a word or word phrase in a sample input data, as the mapping rule of the input data; and

applying the mapping rule in the mapping to map the concept to the input data.

4. The method of claim 1, further comprising:

providing a service that provides the semantic instance, as an abstraction of the input data, usable within a task computing environment.

5. The method of claim 2, further comprising:

displaying the input data,

wherein the set of elements defined to map the concept to the input data further comprises perceptibly distinguishing selected ontology concepts of the selected ontology mapped to the sample of the input data displayed, and the perceptibly distinguishing comprises visually distinguishing same ontology concepts on a display screen via coloring, fonts, font sizing, underlining, bolding, italicizing, numbering, displaying icons, or any combination thereof.

6. The method of claim 2, further comprising:

displaying in a first graphical user interface window the sample of the input data, and

displaying in a second graphical user interface window the selected ontology,

wherein the mapping of a word or word phrase in the sample input data to the selected ontology concept is performed according to a click-and-drag action between the first and second graphical user interfaces.

8. The method of claim 1, wherein the input data is structured, semi-structured, unstructured, or any combination thereof.

9. The method of claim 2, wherein location information, a regular expression, or any combination thereof determine the pattern of the mapped word or word phrase relative to the structure of the sample input data.

10. The method of claim 9, wherein templates of the location information and the regular expression depending on the input data are used to determine the pattern of the mapped word or word phrase relative to the structure of the sample input data.

11. The method of claim 1, wherein a plurality of mapping rules are generated and the method further comprises:

assigning a priority to each mapping rule; and

applying the mapping rules to the input data according to the assigned mapping rule priority.

12. The method of claim 1, wherein a plurality of mapping rules are generated and the method further comprises:

assigning an order to each mapping rule; and

applying the mapping rules to the input data according to the order of the mapping rules.

13. The method of claim 2, wherein templates are used to determine the pattern of the mapped word or word phrase relative to the structure of the sample input data.

22. The method of claim 1, wherein the input data is any combination of a single input file or multiple input files, and the generating of the semantic instance comprises generating a single output file containing multiple semantic instances, or generating multiple output files with each output file containing one or more semantic instances from the input data.

23. The method of claim 22, wherein the output files are according to the Resource Description Framework (RDF)/Web Ontology Language (OWL) and/or Relational Database (RDB) format.

24. The method of claim 1, further comprising:

selecting the sample of the input data by a user;

mapping, by the user, the concept to the sample of the input data selected by the user,

generating the mapping rule based upon the mapping by the user of the concept to the sample of the input data;

mapping the concept to the input data based upon the generating of the mapping rule for the sample of the input data; and

generating a semantic instance for the input data according to the mapping of the concept to the input data, thereby providing a user controlled data semanticization service for entire input data.

25. The method of claim 24, wherein a plurality of concepts are mapped to the input data and a plurality of user controlled semantic instances are generated, and the method further comprises generating a list of the generated user controlled semantic instances based upon the input data.

26. The method of claim 24,

wherein the mapping by the user comprises mapping a plurality of concepts from a plurality of ontologies to a plurality of samples of a plurality of the input data, and

wherein the generating of the semantic instance comprises generating a plurality of semantic instances mapping the plurality of concepts from the plurality of ontologies to the plurality of the input data.

7. The method of 3, wherein the suggesting of the sample mapping of the selected ontology concept from the selected ontology to the to the word or word phrase in the sample input data comprises same perceptibly distinguishing the word or word phrase in the sample input data as the selected ontology concept.

14. A computer-implemented method comprising:

selecting electronic data, as input data, to semanticize;

selecting an ontology by a user;

selecting an input data from among the input data;

selecting an ontology concept from the selected ontology, by the user;

mapping, by the user, the selected ontology concept to the input data;

generating a data structure capture rule based upon the mapping of the selected ontology concept to the input data;

storing the data structure capture rule;

suggesting to the user a mapping of the selected ontology concept to a sample of the input data, based upon the data structure capture rule;

optimizing the generated data structure capture rule according to the user input by modifying the selected ontology, the input data, the selected ontology concept, the mapping of the selected ontology concept to the input data, or any combination thereof; and

semanticizing the input data by applying the generated optimized data structure capture rule applied to entire input data, if the user accepts a mapping suggestion that maps the selected ontology concept to the sample input data.

15. A computer-implemented method, comprising:

selecting an ontology to apply to input electronic data;

selecting a sample of the data;

capturing a structure of the input electronic data using the sample of the data, based upon the selected ontology of the data; and

generating semantic instances for the input electronic data based upon the captured structure of the data and the selected ontology.

16. The method of claim 15, wherein the capturing the structure of the sample input data comprises:

mapping an ontology concept from the selected ontology to the sample input data;

approximating a structure of the sample input data based upon the mapping of the ontology concept; and

capturing the structure of the input electronic data according to the approximating of the structure of the sample input data.

17. The method of claim 16, wherein the capturing the structure of the sample input data further comprises:

selecting the ontology concept by a user;

suggesting to the user a mapping of the selected ontology concept to the sample input data; and

approximating the structure of the sample input data, if the user accepts the mapping of the selected ontology concept to the sample input data.

18. The method of claim 15, wherein the ontology is selected according to a domain of the input electronic data.

19. A computer-implemented method, comprising:

defining a set of annotation elements to capture a structure of electronic data as input data;

generating a rule, according to the set of annotation elements defined and a sample of the input data, to capture the structure of the input data;

applying the rule to the input data; and

generating a semantic instance of the input data based upon the rule applied to the input data.

20. The method of claim 19, wherein the set of annotation elements to capture the structure of the input data comprises a selected ontology corresponding to the input data, a selected ontology concept from the selected ontology, and a mapping of a phrase and/or a region of a phrase in the sample input data to the selected ontology concept from the selected ontology.

21. The method of claim 20, wherein the generating of the rule to capture the structure of the input data comprises:

suggesting a mapping of the selected ontology concept from the selected ontology to the sample input data, as a data structure rule of the input data; and

selecting the mapping according to the suggesting to select the data structure rule of the input data, to apply the data structure rule in the applying of the rule to the input data.

27. A computing apparatus, comprising:

a programmed computer processor controlling the apparatus according to a process comprising;

defining a set of annotation elements to map a concept to electronic data as input data;

generating a mapping rule, according to the set of annotation elements defined and a sample of the input data;

mapping the concept to the input data by applying the mapping rule to the input data; and

generating a semantic instance of the input data based upon the mapping of the concept to the input data.

28. The apparatus of claim 27, wherein the set of annotation elements to map the concept to the input data comprises a selected ontology corresponding to the input data, a selected ontology concept from the selected ontology, a mapping of a word or word phrase in the sample input data to the selected ontology concept from the selected ontology, and a pattern of the mapped word or word phrase relative to a structure of the sample input data.

29. The apparatus of claim 28, wherein the generating of the mapping rule comprises:

suggesting a sample mapping of the selected ontology concept from the selected ontology to the word or word phrase in the sample input data, as the mapping rule of the input data; and

applying the mapping rule in the mapping to map the concept to the input data.

30. The apparatus of claim 27, wherein the apparatus controlling process by the programmed computer processor further comprises:

providing a service that provides the semantic instance, as an abstraction of the input data, usable within a task computing environment.

31. The apparatus of claim 27, wherein the apparatus controlling process by the programmed computer processor further comprises:

selecting the sample of the input data by a user;

mapping, by the user, the concept to the sample of the input data selected by the user,

generating the mapping rule based upon the mapping by the user of the concept to the sample of the input data;

mapping the concept to the input data based upon the generating of the mapping rule for the sample of the input data; and

generating a semantic instance for the input data according to the mapping of the concept to the input data, thereby providing a user controlled data semanticization service for entire input data.

32. A computing apparatus, comprising:

means for defining a set of annotation elements to map a concept to electronic data as input data;

means for generating a mapping rule, according to the set of annotation elements defined and a sample of the input data;

means for mapping the concept to the input data by applying the mapping rule to the input data; and

means for generating a semantic instance of the input data based upon the mapping of the concept to the input data.

33. A computing apparatus, comprising:

a programmed computer processor controlling the apparatus according to a process comprising;

selecting electronic data, as input data, to semanticize;

selecting an ontology database by a user;

selecting an input data from among the input data;

selecting an ontology concept from the selected ontology, by the user;

mapping, by the user, the selected ontology concept to the input data;

generating a data structure capture rule based upon the mapping of the selected ontology concept to the input data;

suggesting to the user a mapping of the selected ontology concept to a sample of the input data, based upon the data structure capture rule;

optimizing the generated data structure capture rule according to the user input by adjusting the selected ontology, the input data, the selected ontology concept, the mapping of the selected ontology concept to the input data, or any combination thereof; and

semanticizing the input data by applying the generated optimized data structure capture rule applied to entire input data, if the user accepts a mapping suggestion that maps the selected ontology concept to the sample input data.