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 § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-8, 10-16, and 18-20 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without a practical application or significantly more. More specifically the independent claims 1, 12, and 20, are rejected under 35 U.S.C. 101 the claims recite "determining sub-scores for each of a plurality of characteristics of the network entity, wherein to determine the sub-scores, determine a sub-score associated with the sentiment analysis; and determine, based on the sub-scores for each of the plurality of characteristics of the network entity, a level of trust for the network entity”. The limitations of "determining", as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting "processing circuitry and network entity," nothing in the claims precludes the step from practically being performed in the mind. A person can think (e.g. analyze) and determine a sentiment, and then determine a trust score. If a claim limitation, under its broadest reasonable
interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the "Mental Processes" grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites two additional element - using "processing circuitry and network entity" to perform, based on information collected about a network entity, a sentiment analysis involving user comments associated with the network entity; and perform an action based on the level of trust for the network entity, wherein to perform the action…to communicated with a device to modify operations. Collecting information is a data gather step, and performing a sentiment analysis on the collected information is pre-solution activity. The modifying step. modifying based on the sub-scores operations within the network is post- solution activity. The processing circuitry and network entity is no more than mere instructions to apply the exception using generic computer components. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements do amounts to no more than mere instructions to apply the exception using a generic computer component. The claims as whole, "performing determining, and modifying" are not sufficient to amount to significantly more than the judicial exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination
under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 5-8, 10-12, and 16-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 5-8, 10-12, and 16-20 of U.S. Patent No. 12,170,670 to O’Neil. Although the claims at issue are not identical, they are not patentably distinct from each other because application claims 1, 4, 6, 9, 12, 14, 15, and 16 are anticipated by patent claims 1, 5-8, 10-12, and 16-20.
Claim Rejections - 35 USC § 103
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 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 1-5, 7-8, and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over Salajegheh (2021/0409405) in view of Vasseur et al. (2022/0345394) and further in view of Walton (2016/0292288).
As per claim 1, a computing system comprising processing circuitry and a storage device, wherein the processing circuity has access to the storage device and is configured to:
perform, based on information collected about a network entity in a computer network, a sentiment analysis involving user comments associated with the network entity (Salajegheh:
para. 0162, sentiment analysis features observed locally by the authentication device, data received from other devices (i.e. user comments) associated with the network entity);
determine scores for each of a plurality of characteristics of the network entity, wherein to determine the scores, the processing circuitry is further configured to determine a score associated with the sentiment analysis (Salajegheh: para. 0162, determine trust scores for characteristics (i.e. network data, signal strength, payment history);
determine, based on the scores for each of the plurality of characteristics of the network entity, a level of trust for the network entity (Salajegheh: para. 0162, 0184, determine the level of trust based on trust scores).
Salajegheh does not explicitly disclose perform an action based on the level of trust for the network entity, wherein to perform the action, the processing circuitry is further configured to communicate with a device on the computer network to modify operations within the computer network.
However, analogous art of Vasseur discloses perform an action based on the level of trust for the network entity, wherein to perform the action, the processing circuitry is further configured to communicate with a device on the computer network to modify operations within the computer network (Salajegheh: modifying, based on the trust score for the network entity, routing changes (i.e. modifying) operations with the computer network).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Salajegheh with the system/method of Vasseur to include perform an action based on the level of trust for the network entity, wherein to perform the action, the processing circuitry is further configured to
communicate with a device on the computer network to modify operations within the computer network.
One would have been motivated to use the technique that monitors the performance of routing changes so as to quantify a degree of a trust with the system. Doing so allows a network administrator to decide when the system can be trusted to take automatic control over routing decisions and under which circumstances (Vasseur: para. 0119).
Salajegheh and Vasseur do not disclose a sub-score.
Walton discloses a sub-score (Walton: para. 0118-0119).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Salajegheh and Vasseur with the system/method of Walton, the motivation is that sub-score provides granular insights into specific strengths and weaknesses within a larger assessment, allowing for targeted remediation (Walton: para. 0118-0119).
As per claim 2, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Salajegheh further discloses wherein to determine the level of trust, the processing circuitry is further configured to: assign, based on the determined level of trust, one of a finite number of trust categories to the network entity (Salajegheh: para. 0162, categories (i.e. network data, payment history).
As per claim 3, Salajegheh, Vasseur, and Walton disclose the computing system of claim 2. Salajegheh further discloses wherein the processing circuitry is further configured to: output a user interface expressing the level of trust using the assigned one of the finite number of trust categories; and enable, based on the level of trust, the network entity to perform an operation on the computer network (Salajegheh: para. 0162, categories (i.e. network data, payment history)).
As per claim 4, Salajegheh, Vasseur, and Walton discloses the computing system of claim 1. Salajegheh further discloses wherein the processing circuitry is further configured to: determine an amount of trust that another network entity has for the network entity (Salajegheh: para. 0162, determine an amount of trust that another peer device has for the device).
As per claim 5, Salajegheh, Vasseur, and Walton discloses the computing system of claim 4. wherein to determine the level of trust, the processing circuitry is further configured to: determine the level of trust further based on the amount of trust that the other network entity has for the network entity (Salajegheh: para. 0162, 0184, determine trust score).
As per claim 7, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Walton further discloses wherein the processing circuitry is further configured to: determine a prerequisite sub-score for the network entity based on one or more prerequisites for the network entity (Walton: para. 0119-0120).
Same motivation as claim 1 above.
As per claim 8, Salajegheh, Vasseur, and Walton disclose the computing system of claim 7. The combination of Salajegheh and Walton further discloses wherein to determine the level of trust (Salajegheh: para. 0162), the processing circuitry is further configured to: determine the level of trust (Salajegheh: para. 0162) further based on the prerequisite sub-score (Walton: para. 0118-0120).
Same motivation as claim 1 above.
As per claim 10, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Salajegheh further discloses wherein the information collected about the network entity includes at least one of: log information, diagnostic information, trouble-ticketing information, emails, chat messages, collaboration applications, metadata associated with the network entity, information derived from user interface interactions, or text received in response to user interface interactions (Salajegheh: para. 0162, information collected about the network entity (i.e. authentication device/peer device) includes metadata associated with the network entity (i.e.
authentication device/peer device), such as IP address, Wi-fi connection data to name a few, the Examiner asserts that claim recites “at least one of”).
As per claim 11, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Vasseur further discloses wherein to modify operations, the processing circuitry is further configured to change configurations for at least one of: a router, a firewall, an access control system, an asset management system, or an alarm system (Vasseur: para. 0117,
modifying operations includes configuration changes affecting the router, the claim only needs one to be required, “at least one”).
Same motivation as claim 1 above.
As per claim 12, rejected under similar scope as claim 1 above.
As per claims 13-14, rejected under similar scope as claims 2-3 respectively.
As per claim 15-17, rejected under similar scope as claims 4-6 respectively.
As per claims 18-19, rejected under similar scope as claims 7-8 respectively.
As per claim 20, rejected under similar scope as claim 1 above.
Claims 6 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Salajegheh (2021/0409405) in view of Vasseur et al. (2022/0345394) and in view of Walton (2016/0292288), and further in view of Xiu (2020/0302540).
As per claim 6, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Salajegheh further discloses wherein the network entity is a specific network entity from among a plurality of network entities, and wherein to perform the sentiment analysis (Salajegheh: para. 0162).
Salajegheh, Vasseur, and Walton do not disclose the processing circuitry is further configured to: train a machine learning model to predict sentiment from information about network entities included within the plurality of network entities; and apply the machine learning
model to predict the sentiment for the specific network entity from the information collected about the specific network entity.
However, Xiu discloses the processing circuitry is further configured to: train a machine learning model to predict sentiment from information about network entities included within the plurality of network entities; and apply the machine learning model to predict the sentiment for the specific network entity from the information collected about the specific network entity (Xiu: See Fig. 2B, para. 0024, 0027, training the machine learning model #125 to predict sentiment from information and applying machine learning model to predict the sentiment from the information collected).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Salajegheh, Vasseur, and Walton with the system/method of Xiu to include performing the sentiment analysis includes: training a machine learning model to predict sentiment from information; and applying the machine learning model to predict the sentiment from the information collected. One would have been motivated to use a method that utilizes machine learning to process features extracted, an input dataset (e.g. information) obtained from one or more data sources and produces an output; thus the input dataset may be derived from data obtained from the data source (Xiu: para. 0027).
As per claim 9, Salajegheh, Vasseur, and Walton disclose the computing system of claim 1. Salajegheh, Vasseur, and Walton do not disclose wherein to perform the sentiment analysis, the processing circuitry is further configured to: process the information collected about the network entity in a pipeline that translates raw text into clean text suitable for natural language
processing; and apply a machine learning model to the clean text to predict the sentiment associated with the network entity.
However, Xiu analogous art discloses process the information collected about the network entity in a pipeline that translates raw text into clean text suitable for natural language processing (Xiu: para. 0006, See Fig. 2A #202 raw textual data, the information is inputted in a pipeline #210 that translates the raw text into a clean text); and apply a machine learning model to the clean text to predict the sentiment associated with the network entity (Xiu: para. 0005, applying
a machine learning model (i.e. sentiment extraction model) to the clean text to predict the sentiment).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of collecting information of a network entity of Salajegheh, Vasseur, and Walton with the system/method of Xiu to include process the information collected about the network entity in a pipeline that translates raw text into clean text suitable for natural language processing; and apply a machine learning model to the clean text to predict the sentiment associated with the network entity.
One would have been motivated to use a method that utilizes machine learning to process features extracted, an input dataset (e.g. raw textual data) obtained from one or more data sources and produces an output; thus the input dataset may be derived from data obtained from the data source (Xiu: para. 0027).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JENISE E JACKSON whose telephone number is (571)272-3791. The examiner can normally be reached M-F 7:00am-3:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Philip J Chea can be reached at (571) 272-3951. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
2/19/2026
/J.E.J/Examiner, Art Unit 2499 /PHILIP J CHEA/Supervisory Patent Examiner, Art Unit 2499