SEQUENTIAL INFORMATION RETRIEVAL

• US 20110078194A1
• Filed: 07/07/2010
• Published: 03/31/2011
• Est. Priority Date: 09/28/2009
• Status: Abandoned Application

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Goldberg, Josep H., Helfman, Jonathan
• Application Number:
  US12/831,641
• Publication Number:
  US 20110078194A1
• Time in Patent Office: Days
• US Class Current: 707/780
• CPC Class Codes: G06F 16/2474 Sequence data queries, e.g. querying versioned data

Abstract

Embodiments of the invention provide systems and methods for retrieving sequential information from a dataset. More specifically, retrieving sequential information from a dataset including one or more existing sequences can comprise receiving a query sequence representing a sequence against which the one or more existing sequences in the dataset is compared. The query sequence can be added to the dataset and a dotplot of the sequences in the dataset including the query sequence can be created. A determination can be made as to whether any of the one or more existing sequences match the query sequence based on the dotplot. For example, determining whether any of the one or more existing sequences match the query sequence based on the dotplot can comprise performing a line fitting process such as a regression-based line fitting process.

Claims

1. A method of retrieving sequential information from a dataset including one or more existing sequences, the method comprising:

receiving a query sequence representing a sequence against which the one or more existing sequences in the dataset is compared;

adding the query sequence to the dataset;

creating a dotplot of the sequences in the dataset including the query sequence; and

determining whether any of the one or more existing sequences match the query sequence based on the dotplot.

2. The method of claim 1, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises performing a line fitting process on the sequences of the dotplot.

3. The method of claim 2, wherein the line fitting process comprises a regression-based line fitting process.

4. The method of claim 1, wherein the one or more existing sequences comprises a plurality of existing sequences and wherein receiving the query sequence comprises receiving a selection of one of the plurality of existing sequences.

5. The method of claim 1, wherein adding the query sequence to the data set comprises temporarily adding the query sequence to the data set.

6. The method of claim 1, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises finding a closest match for the query sequence.

7. The method of claim 1, wherein the dataset comprises eye tracking data and the one or more existing sequences comprise scanpaths between fixation points.

8. The method of claim 7, wherein collecting the query sequence comprises receiving a trace over a stimulus image via a user interface and converting the trace to the query sequence, wherein the trace comprises a hypothetical eye tracking strategy.

9. A system comprising:

a processor; and

a memory communicatively coupled with and readable by the processor and having stored therein a series of instructions which, when executed by the processor, cause the processor to retrieve sequential information from a dataset including one or more existing sequences by receiving a query sequence representing a sequence against which the one or more existing sequences in the dataset is compared, adding the query sequence to the dataset, creating a dotplot of the sequences in the dataset including the query sequence, and determining whether any of the one or more existing sequences match the query sequence based on the dotplot.

10. The system of claim 9, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises performing a line fitting process on the sequences of the dotplot.

11. The system of claim 10, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises finding a closest match for the query sequence.

12. The system of claim 9, wherein the one or more existing sequences comprises a plurality of existing sequences and wherein receiving the query sequence comprises receiving a selection of one of the plurality of existing sequences.

13. The system of claim 9, wherein the dataset comprises eye tracking data and the one or more existing sequences comprise scanpaths between fixation points.

14. The system of claim 13, wherein collecting the query sequence comprises receiving a trace over a stimulus image via a user interface and converting the trace to the query sequence, wherein the trace comprises a hypothetical eye tracking strategy.

15. A machine-readable medium having stored thereon a series of instructions which, when executed by a processor, cause the processor to retrieve sequential information from a dataset including one or more existing sequences by:

receiving a query sequence representing a sequence against which the one or more existing sequences in the dataset is compared;

adding the query sequence to the dataset;

creating a dotplot of the sequences in the dataset including the query sequence; and

determining whether any of the one or more existing sequences match the query sequence based on the dotplot.

16. The machine-readable medium of claim 15, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises performing a line fitting process on the sequences of the dotplot.

17. The machine-readable medium of claim 16, wherein determining whether any of the one or more existing sequences match the query sequence based on the dotplot comprises finding a closest match for the query sequence.

18. The machine-readable medium of claim 15, wherein the one or more existing sequences comprises a plurality of existing sequences and wherein receiving the query sequence comprises receiving a selection of one of the plurality of existing sequences.

19. The machine-readable medium of claim 15, wherein the dataset comprises eye tracking data and the one or more existing sequences comprise scanpaths between fixation points.

20. The machine-readable medium of claim 19, wherein collecting the query sequence comprises receiving a trace over a stimulus image via a user interface and converting the trace to the query sequence, wherein the trace comprises a hypothetical eye tracking strategy.