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 .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3, 5-11, 13-17, and 19-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chakra et al. (US 2019/0036835 A1, hereinafter Chakra).
Regarding claim 1, Chakra teaches a method comprising:
receiving information indicating an intensity associated with a user input, wherein the user input is associated with a function of an application being used by a user, [Par.[0082] describes collecting user input (repeatedly clicking the mouse, pressing enter etc.) to determine user’s sentiment; user’s sentiment is with respect to workload x (~function of an application) as in Figure 5 or 9 and Par.[0065] describes examples];
determining, based on the intensity, whether to adjust network resources to implement the function, [Figure 5 shows service level for workload x determined based on user’s sentiment as further explained in Par.[0084] and elsewhere]; and
adjusting one or more network configuration parameters to implement the function, [Figure 5, 506 adjust resources for workload x based on service level which is in turn based on user’s sentiment; see Figure 9, 906, 908, and 910].
Regarding claim 11, Chakra teaches a method comprising:
receiving biometric information of a user of an application, [Figure 6, 604, Par.[0075] describes user sentiment analysis using biometrics to systematically identify, extract, quantify, and study affective states and subjective information; Par.[0082] describes collecting user input (repeatedly clicking the mouse, pressing enter etc.) to determine user’s sentiment; user’s sentiment is with respect to workload x (~function of an application) as in Figure 5 or 9 and Par.[0065] describes examples];
determining, based on the biometric information, that an excitement level of the user warrants an adjustment to network resources for the application, [Figure 5 shows service level for workload x determined based on user’s sentiment as further explained in Par.[0084] and elsewhere]; and
adjusting, based on the determining, the network resources, [Figure 5, 506 adjust resources for workload x based on service level which is in turn based on user’s sentiment; see Figure 9, 906, 908, and 910 and elsewhere in the written description].
Regarding claim 16, Chakra teaches a method comprising:
receiving biometric information of a user at a plurality of times while the user is using an application, [Figure 6, 604, Par.[0075] describes user sentiment analysis using biometrics to systematically identify, extract, quantify, and study affective states and subjective information; the collection, feedback, and adjustment for workload x happens repeatedly as shown in Figure 5, repeat 503, 504, and 506 (~plurality of times while users is using an application); Par.[0082] describes collecting user input (repeatedly clicking the mouse, pressing enter etc.) to determine user’s sentiment; user’s sentiment is with respect to workload x (~function of an application) as in Figure 5 or 9 and Par.[0065] describes examples];
determining, based on the biometric information, changes in an excitement level of the user while the user is using the application, [Figure 5 shows service level for workload x determined based on user’s sentiment as further explained in Par.[0084] and elsewhere]; and
dynamically adjusting network resources, during the user’s use of the application, based on the changes in the excitement level of the user, [Figure 5, 506 adjust resources for workload x based on service level which is in turn based on user’s sentiment; the collection, feedback, and adjustment for workload x happens repeatedly as shown in Figure 5, repeat 503, 504, and 506 (~during the user’s use of the application); see Figure 9, 906, 908, and 910 and elsewhere in the written description].
Regarding claim 3, Chakra teaches the method of claim 1, and wherein the information indicates a rate of the user input and wherein the determining is further based on the rate, [Par.[0082] describes repeatedly clicking the mouse or pressing enter to detect sentiment].
Regarding claim 5, Chakra teaches the method of claim 1, wherein adjusting the one or more network configuration parameters comprises setting, based on the intensity, a data priority associated with the application, [see Figures 7 and 8 and associated description].
Regarding claim 6, Chakra teaches the method of claim 1, further comprising receiving second information indicating a second intensity associated with a second user input, wherein the second user input is associated with the function of the application being used by the user; and wherein the determining is further based on the second intensity, [see claim 1 citations; process steps in Chakra apply to all users].
Regarding claim 7, Chakra teaches the method of claim 1, further comprising: storing data comprising an intensity level table for the application, wherein the determining is further based on the intensity level table, [see Figures 7 or 8 and associated description].
Regarding claim 8, Chakra teaches the method of claim 1, further comprising: receiving biometric information of the user, wherein the determining is further based on the biometric information, [Figure 6, 604, Par.[0075] describes user sentiment analysis using biometrics to systematically identify, extract, quantify, and study affective states and subjective information].
Regarding claim 9, Chakra teaches the method of claim 1, determining, based on an increase in the intensity, that additional network resources are needed to implement the function, [Figures 5, 7, 8, and 9 among others and associated description shows adjusting (increasing) service levels and resources based on sentiment value].
Regarding claim 10, Chakra teaches the method of claim 1, further comprising: determining, based on a decrease in the intensity, that fewer network resources are needed to implement the function, [Figures 5, 7, 8, and 9 among others and associated description shows adjusting (decreasing) service levels and resources based on sentiment value].
Regarding claim 13, Chakra teaches the method of claim 11, wherein the biometric information indicates a heart rate; and wherein the determining is further based on the heart rate, [Par.[0074] describes a client module accessing devices to retrieve user heart rate].
Regarding claim 14, Chakra teaches the method of claim 11, wherein the biometric information indicates a change in the excitement level of the user, and wherein the adjusting is based on the change in the excitement level, [Figure 6, 604, Par.[0075] describes user sentiment analysis using biometrics to systematically identify, extract, quantify, and study affective states and subjective information and Figures 5, 7, 8, and 9].
Regarding claim 15, Chakra teaches the method of claim 11, wherein the adjusting is further based on information indicating different network resource levels for different excitement levels, [Figures 5, 7, 8, and 9 among others].
Regarding claim 17, Chakra teaches the method of claim 16, further comprising: increasing the network resources based on determining that the excitement level has satisfied a threshold; and reducing the network resources based on determining that the excitement level has no longer satisfied the threshold, [Figure 5 shows sentiment compared to different thresholds, 0, positive or negative values and levels and resources].
Regarding claim 19, Chakra teaches the method of claim 16, further comprising: determining based on an increase in the intensity that additional network resources are needed for the application, [see Figures 5, 7, 8, and 9 among others].
Regarding claim 20, Chakra teaches the method of claim 16, further comprising: determining based on a decrease in the intensity that fewer network resources are needed for the application, [see Figures 5, 7, 8, and 9 among others].
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Chakra in view of Manolescu et al. (US 2010/0223581 A1, hereinafter Manolescu).
Regarding claim 2, Chakra teaches the method of claim 1, and teaches wherein the determining is further based on (biometric) information (as noted above) and does not explicitly teach wherein the information indicates a pressure with which the user input was entered by the user;
Manolescu in an analogous art teaches wherein the information indicates a pressure with which the user input was entered by the user, [claim term pressure is interpreted as ‘touch pressure’ though it can be interpreted as blood pressure; Par. [0034] describes touch pressure to describe participant context pertinent to electronic messaging];
it would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to receive information related to user state of mind for context. The motivation/suggestion would have been to compile data and transform into a visualization of user disposition or context and output to a user device as a multi-dimensional graphical rendering. By rendering contextual data graphically, the rich and diverse information available from usage histories, current user context and user dispositions can be output and consumed rapidly and efficiently, resulting in productive electronic interaction, [Manolescu: Abstract; Chakra: Par.[0075].
Regarding claim 12, Chakra teaches the method of claim 11, and teaches wherein the determining is further based on (biometric) information (as noted above) and does not explicitly teach wherein the biometric information indicates motion of an eye of the user;
Manolescu in an analogous art teaches wherein the biometric information indicates motion of an eye of the user, [Par. [0048] describes eye movement to describe participant context pertinent to electronic messaging];
it would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to receive information related to user state of mind for context. The motivation/suggestion would have been to compile data and transform into a visualization of user disposition or context and output to a user device as a multi-dimensional graphical rendering. By rendering contextual data graphically, the rich and diverse information available from usage histories, current user context and user dispositions can be output and consumed rapidly and efficiently, resulting in productive electronic interaction, [Manolescu: Abstract; Chakra: Par.[0075].
Regarding claim 18, Chakra teaches the method of claim 16, and teaches increasing bandwidth for a video (game) based on determining (increased) user inputs, [Figures 5, 7, 8, and 9 among others and associated description shows adjusting (increasing) service levels and resources based on sentiment; Par.[0025] describe adjusting resources refers to network bandwidth as a resource; Par.[0065] workload refers to accessing video]; Chakra does not explicitly teach user inputs from a user are made with physical pressure;
Manolescu in an analogous art, teaches user inputs from a user are made with physical pressure, [claim term physical pressure is interpreted as ‘touch pressure’; Par. [0034] describes touch pressure to describe participant context pertinent to electronic messaging];
it would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to receive information related to user state of mind for context. The motivation/suggestion would have been to compile data and transform into a visualization of user disposition or context and output to a user device as a multi-dimensional graphical rendering. By rendering contextual data graphically, the rich and diverse information available from usage histories, current user context and user dispositions can be output and consumed rapidly and efficiently, resulting in productive electronic interaction, [Manolescu: Abstract; Chakra: Par.[0075].
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Chakra in view of DeLuca et al. (US 2015/0295867 A1, hereinafter DeLuca).
Regarding claim 4, Chakra teaches the method of claim 1, wherein the determining is further based on the information (collected from the device about pictures/video) [Par.[0080]-[0081] and does not explicitly teach wherein the information indicates an orientation of a device held by the user;
DeLuca in an analogous art teaches wherein the information indicates an orientation of a device held by the user, [Abstract and elsewhere is described associating a sentiment with detecting the orientation of the device];
it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to determine a orientation of the device. The motivation/suggestion would have been to determine a sentiment associated with the picture based on the orientation of the device and the motion by the user, [DeLuca: Abstract; Chakra: Par.[0080]].
Conclusion
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/PADMA MUNDUR/Primary Examiner, Art Unit 2441