Granted Patent B2

US 12,488,028 · App. 18/117,281 · Granted Dec 2, 2025

Inventors: Aaron K. Baughman (Cary, NC); Shikhar Kwatra (San Jose, CA); Iranna Dharmaraya Ankad (Bengaluru, IN); Utpal Mangla (Toronto, CA)

Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION

G06F16/3322G06F9/543G06F16/3323G06F40/216G06F40/274G06F16/3329G06F16/3349G06F40/279G06F40/289G06F40/295

Abstract

Claims (49)

1 . A computer-implemented method comprising:

implementing a predictive search functionality in a computing device using a short-term data storage and transfer feature (system clipboard) of the computing device, wherein the implementing avoids an explicit paste operation from the system clipboard, the implementing comprising—

computing, using a probability distribution and a search result history, a probability of selecting a specified number of relevant samples and a specified number of irrelevant samples from a set of contents, each content in the set of contents comprising a content stored in the system clipboard of the computing device;

weighting, using the probability distribution, each content in the set of contents, the weighting resulting in a weighted set of contents;

executing code configured for generating, responsive to an indication of an intent to perform a search, without requiring (i) the explicit paste operation and (ii) a user entry of at least a part of a search term, and by using the weighted set of contents from the system clipboard, a set of predicted search terms;

presenting, for selection responsive to an indication of intent to perform a search, the set of predicted search terms; and

executing code of the predictive search functionality wherein a code of a search function is executed using a selected search term from the set of predicted search terms to produce a search result.

2 . The computer-implemented method of claim 1 , further comprising:

extracting, from a first content in the set of contents, a first numerical representation of a first set of features, the first content comprising a most recent addition to the set of contents.

3 . The computer-implemented method of claim 2 , further comprising:

removing, from the set of contents prior to weighting the set of contents, a second content, the second content having a second numerical representation, the second numerical representation having a similarity below a threshold similarity to the first numerical representation.

4 . The computer-implemented method of claim 1 , wherein the set of contents comprises a third content, the third content copied to a second system clipboard of a second device.

5 . The computer-implemented method of claim 4 , wherein the specified number of irrelevant samples is determined according to a proportion of user time spent on a set of devices including the first device and the second device.

6 . The computer-implemented method of claim 1 , further comprising:

updating, based on a selection of a search within the set of predicted search terms, the search result history.

7 . A computer program product comprising one or more computer readable storage medium, and program instructions collectively stored on the one or more computer readable storage medium, the program instructions executable by a processor to cause the processor to perform operations comprising:

implementing a predictive search functionality in a computing device using a short-term data storage and transfer feature (system clipboard) of the computing device, wherein the implementing avoids an explicit paste operation from the system clipboard, the implementing comprising—

computing, using a probability distribution and a search result history, a probability of selecting a specified number of relevant samples and a specified number of irrelevant samples from a set of contents, each content in the set of contents comprising a content stored in the system clipboard of the computing device;

weighting, using the probability distribution, each content in the set of contents, the weighting resulting in a weighted set of contents;

executing code configured for generating, responsive to an indication of an intent to perform a search, without requiring (i) the explicit paste operation and (ii) a user entry of at least a part of a search term, and by using the weighted set of contents from the system clipboard, a set of predicted search terms;

presenting, for selection responsive to an indication of intent to perform a search, the set of predicted search terms; and

executing code of the predictive search functionality wherein a code of a search function is executed using a selected search term from the set of predicted search terms to produce a search result.

8 . The computer program product of claim 7 , wherein the stored program instructions are stored in a computer readable storage device in a data processing system, and wherein the stored program instructions are transferred over a network from a remote data processing system.

9 . The computer program product of claim 7 , wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising:

program instructions to meter use of the program instructions associated with the request; and

program instructions to generate an invoice based on the metered use.

10 . The computer program product of claim 7 , further comprising:

extracting, from a first content in the set of contents, a first numerical representation of a first set of features, the first content comprising a most recent addition to the set of contents.

11 . The computer program product of claim 10 , further comprising:

removing, from the set of contents prior to weighting the set of contents, a second content, the second content having a second numerical representation, the second numerical representation having a similarity below a threshold similarity to the first numerical representation.

12 . The computer program product of claim 7 , wherein the set of contents comprises a third content, the third content copied to a second system clipboard of a second device.

13 . The computer program product of claim 12 , wherein the specified number of irrelevant samples is determined according to a proportion of user time spent on a set of devices including the first device and the second device.

14 . The computer program product of claim 7 , further comprising:

updating, based on a selection of a search within the set of predicted searches, the search result history.

15 . A computer system comprising a processor and one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by the processor to cause the processor to perform operations comprising:

implementing a predictive search functionality in a computing device using a short-term data storage and transfer feature (system clipboard) of the computing device, wherein the implementing avoids an explicit paste operation from the system clipboard, the implementing comprising—

computing, using a probability distribution and a search result history, a probability of selecting a specified number of relevant samples and a specified number of irrelevant samples from a set of contents, each content in the set of contents comprising a content stored in the system clipboard of the computing device;

weighting, using the probability distribution, each content in the set of contents, the weighting resulting in a weighted set of contents;

executing code configured for generating, responsive to an indication of an intent to perform a search, without requiring (i) the explicit paste operation and (ii) a user entry of at least a part of a search term, and by using the weighted set of contents from the system clipboard, a set of predicted search terms;

presenting, for selection responsive to an indication of intent to perform a search, the set of predicted search terms; and

executing code of the predictive search functionality wherein a code of a search function is executed using a selected search term from the set of predicted search terms to produce a search result.

16 . The computer system of claim 15 , further comprising:

extracting, from a first content in the set of contents, a first numerical representation of a first set of features, the first content comprising a most recent addition to the set of contents.

17 . The computer system of claim 16 , further comprising:

removing, from the set of contents prior to weighting the set of contents, a second content, the second content having a second numerical representation, the second numerical representation having a similarity below a threshold similarity to the first numerical representation.

18 . The computer system of claim 15 , wherein the set of contents comprises a third content, the third content copied to a second system clipboard of a second device.

19 . The computer system of claim 18 , wherein the specified number of irrelevant samples is determined according to a proportion of user time spent on a set of devices including the first device and the second device.

20 . The computer system of claim 15 , further comprising:

updating, based on a selection of a search within the set of predicted searches, the search result history.

Assignments (1)

Continuity (1)

References Cited (31)