COMPOSING TEXT AND STRUCTURED DATABASES

• US 20130275441A1
• Filed: 07/30/2012
• Published: 10/17/2013
• Est. Priority Date: 04/13/2012
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Agrawal, Rakesh, Kannan, Anitha, Shafer, John C., Fuxman, Ariel
• Granted Patent: US 8,996,539 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing

Abstract

A framework is provided for composing texts about objects with structured information about these objects, and thus disclosed are methodologies for linking information from at least two data sources—one comprising a plurality of documents comprising text pertaining to at least one object, and one comprising a plurality of structured records comprising at least one characteristic of the at least one object, each characteristic comprising one property name and an associated property value corresponding to the property name for the at least one object—by determining one or more instance-based traits for each object in both data sources and associating at least one record with at least one document that refers to each object, each trait comprising one or more characteristics that identifiably distinguish each object from all other objects.

Claims

1. A system for linking information from at least two data sources, the system comprising:

a first data source comprising a plurality of documents comprising text pertaining to at least one object;

a second data source comprising a plurality of structured records comprising at least one characteristic of the at least one object, each characteristic comprising one property name and an associated property value corresponding to the property name for the at least one object; and

a processor for determining one or more instance-based traits for each object and for associating at least one record in the second data source with the at least one document from the first data source that refers to each object, each trait comprising one or more characteristics that identifiably distinguish each object from all other objects in the plurality of documents.

2. The system of claim 1, wherein at least one object has at least one trait that identifiably distinguishes the at least one object from among all other objects.

3. The system of claim 1, further comprising a mapping function, performed by the processor, to associate traits in the structured records and the plurality of documents.

4. The system of claim 3, further comprising a scoring function, performed by the processor, to score at least one text document'"'"'s relevancy to at least one record that shares at least one trait.

5. The system of claim 4, wherein the scoring performed by the processor utilizes at least one additional characteristic present in the plurality of documents and in the structured records but not included in the traits.

6. The system of claim 1, wherein the processor further computes an N-gram computation derived from a corpus in order to identify at least one invalid trait, and wherein the processor further prunes at least one instance-based trait based on the N-gram computation.

7. The system of claim 6, wherein the processor further determines at least one instance-based trait for the at least one object that would enable at least one record in the second data source to be associated with the at least one document from the first data source that refers to the at least one object.

8. The system of claim 1, wherein the system determines that an association of a first trait to a first record is correct if a first text from a first document pertains to either the first record or to an accessory of the product represented by the first record.

9. The system of claim 1, wherein the second data source comprises a plurality of web-based pages.

10. The system of claim 9, wherein a set of objects from the second data source pertain to products.

11. A method for linking information from at least two data sources, the method comprising:

describing a plurality of objects using a set of characteristics wherein each object comprising the plurality of objects is identifiably distinguishable by one or more characteristics from among the plurality of characteristics; and

using at least one additional characteristic that does not comprise the set of characteristic to score a relevancy of a document to a record from a first data source that shares at least one of the characteristics of another document from a second data source, wherein the additional characteristic is from the document.

12. The method of claim 11, wherein a trait from among a plurality of traits and comprising a characteristic from the set of characteristics further comprises at least one anchor property, and wherein the at least one anchor property is determined by an anchor score corresponding relative distinctiveness of a value for at least one corresponding property name in the trait.

13. The method of claim 11, wherein at least one trait from among a plurality of traits is filtered out using an N-Gram analysis, wherein each trait comprises a characteristic from the set of characteristics.

14. The method of claim 11, further comprising precluding at least one characteristic that is ambiguous in view of the first data source.

15. The method of claim 11, further comprising composing information pertaining to a set of objects common to the two data sources based on set the characteristics.

16. A computer-readable medium comprising computer-readable instructions for linking information from at least two data sources, the computer-readable instructions comprising instructions that cause a processor to:

map a plurality of documents in a first data source to a plurality of traits in a second data source; and

score the relevancy of a document from among the plurality of documents to at least one record from the second data source.

17. The computer-readable medium of claim 16, further comprising instructions for identifying the plurality of traits from among the traits present in both the first data source and the second data source.

18. The computer-readable medium of claim 16, further comprising instructions for composing the first data source and the second data source based on the mapping and scoring.

19. The computer-readable medium of claim 16, further comprising instructions wherein each trait from among the plurality of traits comprises at least one anchor property.

20. The computer-readable medium of claim 19, further comprising instructions wherein the at least one anchor property is determined by an anchor score corresponding to a relative distinctiveness of a value for at least one corresponding property name in the trait.