DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is responsive to: Application filed 14 Nov. 2024
Claims 2-21 are pending in this case. Claims 2, 13 and 18 are independent claims
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 2-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Krishnamurthy (Pub, No.: US 2016/0117355 A1; Filed: Oct. 22, 2014).
Regarding independent claims 2, 13 and 18, Krishnamurthy disclose a method comprising:
identifying channels usable to communicate with a device associated with a user regarding a
prospective contribution by the user to a digital content item (0031; 0051; 0053; 0057);
determining channel usage data for channels available to the device, wherein the channel usage data comprises, for a respective channel of the channels, data relating to use of the respective channel (0018-0019; 0034; 0057; 0081; 0087);
computing channel affinity scores for the channels based on the channel usage data, wherein a channel affinity score comprises, for the respective channel, a likelihood of the user making a contribution to the digital content item via the respective channel (0018-0019; 0034; 0057; 0081; 0087); and
subsequent to receiving a signal associated with a communication sent via a channel selected
using the channel affinity scores, updating a channel affinity score for the selected channel based on the received signal (0069; 0073-0074).
Regarding dependent claims 3, 14 and 19, Krishnamurthy disclose the method of claims 2, 13 and 18 respectively, further comprising:
outputting, by a generative language model, the digital content item (0030-0034; 0052-0053); and
receiving, via the device, the contribution to the digital content item, wherein the contribution is generated by the user in response to the communication (0030-0034; 0052-0053).
Regarding dependent claims 4, 15 and 20, Krishnamurthy disclose the method of claims 2, 13 and 18 respectively, further comprising:
receiving, via the device, as the signal, the contribution to the digital content item, wherein
the contribution is generated by the user in response to the communication sent through the selected channel (0031; 0033; 0057).
Regarding dependent claim 5, Krishnamurthy disclose the method of claims 2,, further comprising:
receiving, as the signal, the contribution to the digital content item, wherein the contribution is generated by the user (0031; 0033; 0057).
Regarding dependent claim 6, Krishnamurthy disclose the method of claim 2, further comprising:
determining content generation data comprising data about generation, by the user, of content relating to a topic associated with the digital content item (0061; 0064);
based on the content generation data, computing a contributor score for the user, wherein the
contributor score comprises a likelihood of the user contributing content associated with the topic to the digital content item (0061; 0064); and
based on the contributor score, selecting the user from users of a network (0005; 0019; 0069; 0074).
Regarding dependent claim 7, Krishnamurthy disclose the method of claim 2, further comprising:
determining social action data comprising data about digital social actions received via a network in response to distribution of content relating to a topic associated with the digital content item (0051; 0061; 0064);
based on the social action data, computing a contributor score for the user, wherein the contributor score comprises a likelihood of the contribution to the digital content item, by the user, receiving digital social actions (0034; 0051; 0061; 0064; 0068); and
based on the contributor score, selecting the user from users of a network (0005; 0019; 0069; 0074).
Regarding dependent claim 7, Krishnamurthy disclose the method of claim 2, further comprising:
searching entity profile data for a badge (0017; 0032; 0045; 0061-0062); and
in response to determining that entity profile data associated with the user comprises the badge, selecting the user from users of a network (0017; 0032; 0045; 0061-0062).
Regarding dependent claim 9, Krishnamurthy disclose the method of claim 2, further comprising:
generating topic to skill set mappings (0061-0064); and
based on the topic to skill set mappings, selecting the user from users of a network (0061-0064).
Regarding dependent claim 10, Krishnamurthy disclose the method of claim 9, further comprising:
extracting topic data from digital content items output by a generative language model (0061-0064);
extracting skill data from entity profiles (0061-0064); and
generating the topic to skill set mappings based on the topic data and the skill set data (0061-0064).
Regarding dependent claim 11, Krishnamurthy disclose the method of claim 2, further comprising:
distributing the digital content item via a network (0031; 0051; 0053; 0057; 0064-0065);
receiving, via the network, a digital social action associated with the distributed digital content item (0051; 0164);
based on the received digital social action, identifying a second user as a prospective contributor to the digital content item (0048; 0064-0065; 0081; 0083); and
sending, to the second user, a second communication to join a waitlist to contribute to the digital content item (0048; 0064-0065; 0081; 0083).
Regarding dependent claim 12, Krishnamurthy disclose the method of claim 2, further comprising:
receiving interaction data involving the user and the digital content item, wherein the interaction data is generated in response to the communication (0048; 0064-0065; 0081; 0083);
determining attribute data associated with the interaction data, wherein the attribute data
comprises skill data (0032; 0048);
based on the attribute data associated with the interaction data, computing a contributor score
for the user, wherein the contributor score comprises a likelihood of the user making a contribution associated with the skill data to output of a generative language model (0034; 0051; 0061; 0064; 0068); and
based on the contributor score, sending a second communication to the user (0048; 0064-0065; 0081; 0083).
Regarding dependent claim 16, Krishnamurthy disclose the system of claim 13, wherein the instructions further cause the processor to:
distribute the digital content item via a network (0031; 0051; 0053; 0057; 0064-0065);
receive, via the network, a digital social action associated with the distributed digital content
item (0051; 0164);
based on the received digital social action, identify a second user as a prospective contributor
to the digital content item (0048; 0064-0065; 0081; 0083); and
send, to the second user, a second communication to join a waitlist to contribute to the digital
content item (0048; 0064-0065; 0081; 0083).
Regarding dependent claim 17, Krishnamurthy disclose the system of claim 13, wherein the instructions further cause the processor to:
receive interaction data involving the user and the digital content item, wherein the interaction data is generated in response to the communication (0048; 0064-0065; 0081; 0083);
determine attribute data associated with the interaction data, wherein the attribute data comprises skill data (0032; 0048);
based on the attribute data associated with the interaction data, compute a contributor score for the user, wherein the contributor score comprises a likelihood of the user making a contribution associated with the skill data to output of a generative language model (0034; 0051; 0061; 0064; 0068); and
based on the contributor score, send a second communication to the user (0048; 0064-0065; 0081; 0083).
Regarding dependent claim 20, Krishnamurthy disclose the non-transitory machine-readable medium of claim 18, wherein the instructions further cause the processor to:
receive, via the device, as the signal, the contribution to the digital content item, wherein the
contribution is generated by the user in response to the communication sent through the selected channel (0069; 0073; 0079; 0081-0083).
Regarding dependent claim 21, Krishnamurthy disclose the non-transitory machine-readable medium of claim 18, wherein the instructions further cause the processor to:
based on the channel affinity scores, select a channel from the channels (0069; 0073; 0079; 0081-0083).
NOTE
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES J DEBROW whose telephone number is (571)272-5768. The examiner can normally be reached on 09:00 - 06:00.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William Bashore can be reached on 571-272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/James J Debrow/
Primary Patent Examiner
Art Unit 2174
571-272-5768
