Cluster organization of electronically-stored items

• US 7,698,335 B1
• Filed: 06/27/2005
• Issued: 04/13/2010
• Est. Priority Date: 06/27/2005
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Vronay, David
• Primary Examiner(s): Fleurantin; Jean B
• Assistant Examiner(s): Kerzhner; Aleksandr
• Application Number:
  US11/167,515
• Time in Patent Office: 1,751 Days
• Field of Search: 707 3- 6
• US Class Current: 707/737
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures

Abstract

Clusters are described which may be utilized to organize electronically-stored items. A variety of techniques may be employed using the clusters to organize the items. For instance, the clusters may be automatically generated and then modified by a user to classify the items as desired such that a modification made to a single item is propagated to other similar items. Therefore, the single item and the other similar items may be clustered automatically through interaction with the single item.

Claims

1. A method comprising:

storing, by an online-service device configured to provide cluster functionality of electronically-stored items, a plurality of electronically-stored items from each of a plurality of clients, wherein the online service application is located at a server;

automatically clustering, by the online-service device, for each client, a plurality of electronically-stored items into corresponding item clusters based on relative similarity of each said item, one to another, without user input;

generating, by the online-service device, for each client, a client profile for organization of representations of the clustered items;

storing, by the online-service device, the client profile at the server;

communicating, by the online-service device, the client profile to a first client for output via a user interface of the first client;

receiving, by the online-service device, via the user interface, a user-submitted request submitted by the first client, the request indicating;

a first item that is in a first item cluster; and

a second item cluster to which the first item is to be assigned;

in response to the user-submitted request;

moving the first item from the first item cluster to the second item cluster;

without further input from the user;

identifying, by the online-service device, one or more other items to be reassigned to a different cluster, based on similarity between the first item and the other items; and

reassigning, by the online-service device, the one or more other items to the different cluster.

2. A method as described in claim 1, wherein the clustering is performed automatically and without user intervention.

3. A method as described in claim 1, wherein the one or more items are clustered based on relative similarity of each of the items, one to another, based on use of keywords extracted from the items.

4. A method as described in claim 1, wherein:

one or more said item clusters are formed based on keywords; and

the identifying, by the online-service device, one or more other items to be reassigned to a different cluster, based on similarity between the first item and the other items comprises;

identifying, by the online-service device, a first keyword associated with the first item;

identifying, by the online-service device, a second keyword that is similar to the first keyword; and

identifying, by the online-service device, the one or more other items based on the second keyword being associated with each of the one or more other items.

5. A method as described in claim 1, wherein one or more said item clusters are formed based on keywords and wherein the reassigning the one or more other items to the different cluster comprises:

creating, by the online-service device, a third cluster, separate from the first and second clusters, wherein the third cluster is based, at least in part, on the second keyword; and

assigning, by the online-service device, the one or more other items to the third cluster.

6. A method as described in claim 1, wherein clustering the plurality of electronically-stored items into corresponding item clusters comprises:

analyzing, by the online-service device, a plurality of items to define a plurality of cluster profiles;

analyzing, by the online-service device, the plurality of electronically-stored items to determine, for each of the electronically-stored items, a particular one of the cluster profiles; and

clustering, by the online-service device, the plurality of electronically-stored items based on the cluster profiles.

7. A method as described in claim 6, wherein the plurality of items that are analyzed to define the plurality of cluster profiles comprises at least one of the plurality of electronically-stored items.

8. A method as described in claim 6, wherein the plurality of items that are analyzed to define the plurality of cluster profiles does not include any of the plurality of electronically-stored items.

9. A method as described in claim 1, wherein reassigning the one or more other items to the different cluster comprises performing a reclustering operation selected from a group of reclustering operations comprising:

removing an item from the first cluster;

adding an item to the first cluster;

removing an item from the second cluster; and

adding an item to the second cluster.

10. A method as described in claim 1, wherein the item clusters comprises:

a public cluster, the items of which are shared with other users; and

a private cluster, the items of which cannot be searched, accessed, or shared by other users.

11. A method as described in claim 1, wherein:

the relative similarity is expressed as a numerical value;

a threshold value indicates a minimum amount of similarity that is to be demonstrated by items in a particular item cluster.

12. A system comprising:

a processor;

a memory;

an online-service module maintained by the memory and executed by the processor, the online-service module configured to;

provide cluster functionality of electronically-stored items, a plurality of electronically-stored items from each of a plurality of clients, wherein the online service application is located at a server;

for each client, automatically cluster a plurality of electronically-stored items into corresponding item clusters based on relative similarity of each said item, one to another, without user input;

for each client, generate a client profile for organization of representations of the clustered items;

store the client profile at the server;

communicate the client profile to a first client for output via a user interface of the first client;

a cluster user interface module maintained by the memory and executed by the processor, the cluster user interface module configured to;

present representations of the clusters via a display device; and

receive a user-submitted cluster modification, the user-submitted cluster modification comprising a modification to a first keyword in a keyword profile associated with a particular cluster;

an analysis module configured to;

identify attributes of the user-submitted cluster modification; and

extend the user-submitted cluster modification by performing a non-requested cluster modification, wherein the non-requested cluster modification is determined to have attributes that are similar to the attributes of the user-submitted cluster modification, the non-requested cluster modification comprising a modification to a second keyword in the keyword profile associated with the particular cluster.

13. A method as described in claim 12, wherein:

the modification to the first keyword comprises adding the first keyword to the keyword profile associated with the particular cluster; and

the modification to the second keyword comprises adding the second keyword to the keyword profile based on a similarity between the first and second keywords.

14. A method as described in claim 12, wherein:

the modification to the first keyword comprises removing the first keyword from the keyword profile associated with the particular cluster; and

the modification to the second keyword comprises removing the second keyword from the keyword profile based on a similarity between the first and second keywords.

15. A method as described in claim 14, wherein removing the second keyword from the keyword profile comprises creating a new keyword profile for a new cluster, the new keyword profile comprising the second keyword.

16. One or more computer-readable media comprising computer executable instructions that, when executed, cause a computer to perform a method, the method comprising:

storing, by an online-service device configured to provide grouping functionality of electronically-stored items, a plurality of electronically-stored items from each of a plurality of clients, wherein the online service application is located at a server;

automatically grouping, by the online-service device, for each client a plurality of keywords extracted from the plurality of electronically-stored items based on relative similarity of each said keyword, one to another, calculated from use of the keywords in the items, into a keyword profile, without user input;

generating, by the online-service device, for each client, a client profile for organization of representations of the keywords;

storing, by the online-service device, the client profile at the server;

communicating, by the online-service device, the client profile to a first client for output via a user interface of the first client;

outputting representations of electronically-stored items that reflect the keyword profiling;

outputting a user interface configured to accept modifications to the keyword profiling;

receiving, by the online-service device, via the user interface, a user-submitted indication submitted by the first client, of a first keyword to be removed from a first keyword profile;

in response to the user-submitted indication, removing, by the online-service device, the first keyword from the first keyword profile;

without further user input, dynamically applying, by the online-service device, a modification to the keyword profiling by removing a second keyword from the first keyword profile based on similarities between the first and second keywords, wherein the first and second keywords are not the same keyword; and

outputting, by the online-service device, updated representations of the electronically-stored items that reflect the modification to the keyword profiling.

17. One or more computer-readable media as described in claim 16, the method further comprising:

creating a new keyword profile, different from the first keyword profile, that comprises the first and second keywords.

18. One or more computer-readable media as described in claim 16, the method further comprising:

receiving, via the user interface, a user-submitted indication of a third keyword, that is part of a second keyword profile, to be moved from the second keyword profile to the first keyword profile;

in response to the user-submitted indication;

removing the third keyword from the second keyword profile; and

adding the third keyword to the first keyword profile;

without further user input, dynamically applying a modification to the keyword profiling by;

identifying a fourth keyword that is similar to the third keyword;

removing the fourth keyword from a keyword profile currently including the fourth keyword; and

adding the fourth keyword to the first keyword profile,

wherein;

the first and second keyword profile are not the same keyword profile; and

the third keyword and the fourth keyword are not the same keyword.

19. One or more computer-readable media as described in claim 18, wherein the user-submitted indication of the keywords is performed through use of check boxes included in the user interface that correspond to respective said keywords.