METHOD AND SYSTEM FOR TAG SUGGESTION IN A TAG-ASSOCIATED DATA-OBJECT STORAGE SYSTEM

• US 20120109982A1
• Filed: 11/01/2011
• Published: 05/03/2012
• Est. Priority Date: 07/28/2009
• Status: Active Grant

• Current Assignee: Jiaxin Wang, Linh Dinh Tran, Prasantha Jayakody
• Original Assignee: Jiaxin Wang, Linh Dinh Tran, Prasantha Jayakody
• Inventors: Jayakody, Prasantha, Tran, Linh Dinh, Wang, Jiaxin
• Granted Patent: US 9,443,038 B2
• Time in Patent Office: Days
• US Class Current: 707/752
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

Embodiments of the present invention are directed to facilitating tag assignment to data objects as data objects are added to a tag-associated data-object storage system by users of the tag-associated data-object storage system and to facilitate subsequent display, access, and further characterization of data objects that already reside in the a tag-associated data-object storage system. Methods and systems of the present invention provide for automated tag suggestion to users in order to both increase usability of the interface provided to the tag-associated data-object storage systems as well as decrease the likelihood of unnecessary and unproductive tag proliferation within the tag-associated data-object storage system.

Claims

1. A tag-suggestion system included as a component of a tag-associated data-object storage system that is implemented as one or more software programs, hardware circuits, or a combination of software programs and hardware circuits within one or more computer systems that include, or that access, one or more data-storage devices, the tag-suggestion system comprising:

a set of defined tags stored in the tag-associated data-object storage system;

tag-associated data objects stored in tag-associated data-object storage system;

a comparator that compares a data object to other data objects stored in the tag-associated data-object storage system in order to determine those data objects stored in the tag-associated data-object storage system which are most similar to the data object for which tags are to be associated, storing results of comparisons in the one or more data-storage devices; and

a tag selector that selects tags associated with a number of data objects stored in tag-associated data-object storage system most similar to the data object for which tags are to be associated.

2. The tag-suggestion system of claim 1 wherein the comparator carries out a dot product operation on a characteristic vector that characterizes data contents of the data object for which tags are to be associated and a cumulative characteristic vector that characterizes cumulative data contents of the data objects associated with a particular tag, the dot product operation returning a numerically valued similarity metric.

3. The tag-suggestion system of claim 2 wherein the tag selector selects, as candidate tags, a number of tags associated with those data objects stored in the tag-associated data-object storage system most similar to the data object for which tags are to be associated.

4. The tag-suggestion system of claim 3 wherein the tag selector selects the candidate tags by:

for each of, or each of a subset of the set of defined tags stored in the tag-associated data-object storage system,

computing a similarity metric, by the comparator, by comparing the data object for which tags are to be associated to those data objects associated with a currently considered tag, and

storing the computed similarity metric together with the currently considered tag in an electronic storage medium; and

selecting, as a candidate tags, those tags associated with similarity metrics that indicate a greatest similarity between the data object for which tags are to be associated and data objects compared to the data object for which tags are to be associated to generate the similarity metrics.

5. The tag-suggestion system of claim 4 wherein selecting, as a candidate tags, those tags associated with similarity metrics that indicate a greatest similarity between the data object for which tags are to be associated and data objects compared to the data object for which tags are to be associated to generate the similarity metrics further includes:

sorting the computed similarity metrics into a sorted list of similarity metrics;

determining an average similarity-metric-value drop for successive similarity metrics in the sorted list of similarity metrics;

determining whether a first similarity-metric drop computed from the first and second similarity metrics is greater than, equal to, or less than the average similarity-metric-value drop; and

applying a first candidate-tag selection method when the first similarity-metric drop is greater than the average similarity-metric-value drop, a second candidate-tag-selection method when the first similarity-metric drop is equal to the average similarity-metric-value drop, or a third candidate-tag-selection method when the first similarity-metric drop is less than the average similarity-metric-value drop

6. The tag-suggestion system of claim 5 wherein the first, second, and third candidate-tag-selection methods analyze a function of similarity metrics with respect to tags to determine when a turning point occurs in the function, and selects those tags associated with similarity metrics with values above the similarity metric of the turning point.

7. The tag-suggestion system of claim 1 wherein the tag-suggestion system outputs tag suggestions through a user interface.

8. The tag-suggestion system of claim 7 wherein the tag-suggestion system further provides suggestions of groups in which the data object may be included.

9. The tag-suggestion system of claim 2 wherein, prior to carrying out the dot product operation on a characteristic vector that characterizes data contents of the data object for which tags are to be associated and a cumulative characteristic vector that characterizes cumulative data contents of the data objects associated with a particular tag, the comparator multiplies one or more elements of the characteristic vector by weights, in order to adjust the relative significance of the characteristic-vector elements.

10. The tag-suggestion system of claim 9 wherein the comparator multiplies one or more elements of the characteristic vector by weights that are computed based on a type of the data object.

11. The tag-suggestion system of claim 2 wherein the tag-suggestion system selects tags based on one or more similarity thresholds.

12. The tag-suggestion system of claim 10 wherein the tag-suggestion system changes the one or more thresholds to optimize a number of tag suggestions provided for the data object.

13. The tag-suggestion system of claim 1 wherein a user may modify or specify one or more parameters that control how the comparator compares a data object to other data objects stored in the tag-associated data-object storage system in order to determine those data objects stored in the tag-associated data-object storage system which are most similar to the data object for which tags are to be associated.

14. The tag-suggestion system of claim 1 wherein a user may modify or specify one or more parameters that control how the tag selector selects tags associated with a number of data objects stored in tag-associated data-object storage system most similar to the data object for which tags are to be associated.

15. A method, carried out in a tag-associated data-object storage system that is implemented as one or more software programs, hardware circuits, or a combination of software programs and hardware circuits within one or more computer systems that include, or access, one or more data-storage devices, the method comprising:

comparing, by a comparator, a data object to other data objects stored in the tag-associated data-object storage system in order to determine those data objects stored in the tag-associated data-object storage system which are most similar to the data object for which tags are to be associated, storing results of comparisons in the one or more data-storage devices;

selecting, by a tag selector, tags associated with a number of data objects stored in tag-associated data-object storage system most similar to the data object for which tags are to be associated.

16. The method of claim 15 wherein the comparator carries out a dot product operation on a characteristic vector that characterizes data contents of the data object for which tags are to be associated and a cumulative characteristic vector that characterizes cumulative data contents of the data objects associated with a particular tag, the dot product operation returning a numerically valued similarity metric.

17. The method of claim 16 wherein the tag selector selects, as candidate tags, a number of tags associated with those data objects stored in the tag-associated data-object storage system most similar to the data object for which tags are to be associated.

18. The method of claim 17 wherein the tag selector selects the candidate tags by:

for each of, or each of a subset of, the set of defined tags stored in the tag-associated data-object storage system,

computing a similarity metric, by the comparator, by comparing the data object for which tags are to be associated to those data objects associated with a currently considered tag, and

storing the computed similarity metric together with the currently considered tag in an electronic storage medium; and

selecting, as a candidate tags, those tags associated with similarity metrics that indicate a greatest similarity between the data object for which tags are to be associated and data objects compared to the data object for which tags are to be associated to generate the similarity metrics.

19. The method of claim 18 wherein selecting, as a candidate tags, those tags associated with similarity metrics that indicate a greatest similarity between the data object for which tags are to be associated and data objects compared to the data object for which tags are to be associated to generate the similarity metrics further includes:

sorting the computed similarity metrics into a sorted list of similarity metrics;

determining an average similarity-metric-value drop for successive similarity metrics in the sorted list of similarity metrics;

determining whether a first similarity-metric drop computed from the first and second similarity metrics is greater than, equal to, or less than the average similarity-metric-value drop; and

applying a first candidate-tag selection method when the first similarity-metric drop is greater than the average similarity-metric-value drop, a second candidate-tag-selection method when the first similarity-metric drop is equal to the average similarity-metric-value drop, or a third candidate-tag-selection method when the first similarity-metric drop is less than the average similarity-metric-value drop

20. The method of claim 19 wherein the first, second, and third candidate-tag-selection methods analyze a function of similarity metrics with respect to tags to determine when a turning point occurs in the function, and selects those tags associated with similarity metrics with values above the similarity metric of the turning point.

21. The method of claim 15 further including outputting tag suggestions through a user interface.

22. The method of claim 21 further including providing suggestions of groups in which the data object may be included.

23. The method of claim 15 wherein a user may modify or specify one or more parameters that control how the comparator compares a data object to other data objects stored in the tag-associated data-object storage system in order to determine those data objects stored in the tag-associated data-object storage system which are most similar to the data object for which tags are to be associated.

24. The method of claim 15 wherein a user may modify or specify one or more parameters that control how the tag selector selects tags associated with a number of data objects stored in tag-associated data-object storage system most similar to the data object for which tags are to be associated.