Prosecution Insights
Last updated: April 19, 2026
Application No. 17/158,641

SYSTEMS AND METHODS FOR INTELLIGENT SEGMENTATION AND RENDERING OF COMPUTER ENVIRONMENT DATA

Non-Final OA §103
Filed
Jan 26, 2021
Examiner
CURRAN, J MITCHELL
Art Unit
2169
Tech Center
2100 — Computer Architecture & Software
Assignee
Acentium Inc.
OA Round
7 (Non-Final)
61%
Grant Probability
Moderate
7-8
OA Rounds
3y 6m
To Grant
96%
With Interview

Examiner Intelligence

Grants 61% of resolved cases
61%
Career Allow Rate
65 granted / 106 resolved
+6.3% vs TC avg
Strong +35% interview lift
Without
With
+34.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
18 currently pending
Career history
124
Total Applications
across all art units

Statute-Specific Performance

§101
13.9%
-26.1% vs TC avg
§103
57.6%
+17.6% vs TC avg
§102
15.4%
-24.6% vs TC avg
§112
5.6%
-34.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 106 resolved cases

Office Action

§103
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 . Detailed Action This Office Action is a Final Rejection in response arguments and amendments filed on 03/19/2025 for application 17/158,641. Claims 1, 10 and 19 are currently amended. Claims 1-20 are pending and are examined below. Response to Arguments Applicant's arguments filed 03/19/2025 have been fully considered but they are not persuasive. Applicant argues that wherein the multi-dimensional model comprises nodes representing assets in the slice and links between nodes represent the inter-dependencies between corresponding assets, wherein a shape, size and color of each node represents a feature of the corresponding asset and a length, thickness and color of the links represent a feature of the inter-dependencies, wherein the size of the each node represents at least one of the security state or the risk score of the corresponding assets; is not taught by cited reference art Chiba. Applicant contends that Chiba discloses converting a graph type between formats, “such that it maintains the characteristics of the original format.” Because “Chiba is not determining using a shape, size, and color of each node to represent a feature of the corresponding asset and a length, thickness and color of the links represent a feature of the inter-dependencies between corresponding assets,” it’s not teaching the cited claim language. However, the key portion of the cited section (Par. [0067]) of Chiba that indicates it isn’t simply, “converting a graph type between formats” is the first phrase, “As items that can be set in detail at the time of PDF conversion.” The conversion to PDF is not simply maintaining the characteristics of the original format as applicant argues, it decides how the PDF is generated at runtime. To further support this position, the paragraph immediately preceding (Par. [0066]) the cited section lays out Fig. 7 steps that attest to this run-time decision. Step 84 in particular checks to see if there is a user conversion form or not. If not, it uses a standard conversion form (S86). If there is, it uses that conversion format in order to generate the PDF conversion (S85). As explained in the cited section (Par. [0067]), this includes line color (i.e. link color), line thickness, line kind, character font, character color, background color, dot size (i.e. node size), dot color, expansion and contraction (i.e. shapes and lengths), and security features. A user conversion form is capable of specifying “nodes” and “inter-dependencies between corresponding assets, wherein a shape, size and color of each node represents a feature of the corresponding asset, and a length, thickness and color of the links represent a feature of the inter-dependencies, wherein the size of the each node represents at least one of the security state or the risk score of the corresponding assets” as required by claim 1 language. Therefore, argument is unpersuasive. Applicant further argues that Chiba doesn’t teach using the size of the node to represent the security state or risk score of the corresponding assets. However, as explained above, the user conversion form is fully capable of relating the size of a node and its security features. Therefore, the argument is unpersuasive. Claim Objections Examiner agrees that amendments to claims 1, 10 and 19 are sufficient to overcome previous claim objections for claims 1-20. Therefore, all claim objections are withdrawn. 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 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. Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lukas et al. (US Pub. 2014/0136682) in view of Cella et al. (US Pub. 2021/0182996) and Chiba et al. (US Pub. 2005/0256874). Regarding claim 1, Lukas teaches A system comprising: one or more processors and a memory configured to cause the system to: receive data of a computer environment including a plurality of assets; (Fig. 1 #128; Par. [0026] database performance monitor receives data about virtual and hardware networks) filter, using the data and one or more first criteria, the plurality of assets to identify a subset of filtered assets, the one or more first criteria including at least one of an exposure to a specific vulnerability or a cybersecurity attack; (Fig. 1 #128; Par. [0026, 44] database performance monitor receives data about virtual (i.e. first filter criteria) and hardware networks, which can include information about database performance issues due to security issues (i.e. criteria including exposure to a cybersecurity attack)) Lukas does not explicitly teach cluster the subset of filtered assets into a plurality of different slices using the state of each of asset of the subset of filtered assets and one or more values of slicing criteria for clustering the subset of filtered assets into the plurality of different slices, the slicing criteria defined based on user profiles for various users of the computer environment, each slice of the plurality of different slices including assets of the subset of filtered assets of interest to one or more users having a role associated with a corresponding user profile of the user profiles and identified based on corresponding state of each asset and corresponding one or more values of the slicing criteria; generate a visual representation of a slice of the plurality of different slices, the visual representation depicting a multi- dimensional model of the slice to represent inter-dependencies between assets in the slice and a size of each filtered asset in the slice with respect to the one or more first criteria, wherein the multi-dimensional model comprises nodes representing assets in the slice and links between nodes represent the inter-dependencies between corresponding assets, wherein a shape, size and color of each node represents a feature of the corresponding asset and a length, thickness and color of the links represent a feature of the inter-dependencies, wherein the size of the each node represents at least one of the security state or the risk score of the corresponding assets; and assign the visual representation depicting the multi-dimensional model of the slice to a user account or a computing device for rendering based on the role of a user profile associated with the user account or computing device. However, from the same field Cella teaches cluster the subset of filtered assets into a plurality of different slices using the state of each of asset of the subset of filtered assets and one or more values of slicing criteria for clustering the subset of filtered assets into the plurality of different slices, the slicing criteria defined based on user profiles for various users of the computer environment, each slice of the plurality of different slices including assets of the subset of filtered assets of interest to one or more users having a role associated with a corresponding user profile of the user profiles and identified based on corresponding state of each asset and corresponding one or more values of the slicing criteria; (Fig. 12; Par. [0370-73] the storage layer (#624) stores data including data clusters based on (i.e. second criteria) the particular expertise (i.e. user profile) and asset tags (#1178) associated with the user, as well as over various state information handled by a set of state and event managers (#1450)) generate a visual representation of a slice of the plurality of different slices, the visual representation depicting a multi- dimensional model of the slice to represent inter-dependencies between assets in the slice and a size of each filtered asset in the slice with respect to the one or more first criteria; (Par. [0343, 374] visual monitoring systems (#1930) allows for the visualization of a number of items, including factors or parameters of entities (i.e. multiple dimensions containing interdependencies; #652)) and assign the visual representation depicting the multi-dimensional model of the slice to a user account or a computing device for rendering based on the role of a user profile associated with the user account or computing device. (Par. [0370, 374-5] an identity management system can assign an identifier to a user and can use asset tags associated with the data for access control and visualization) It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the asset visualization system of Cella into the database performance monitoring of Lukas. The motivation for this combination would have been to improve intelligence of a distributed asset system as explained in Cella (Par. [0337]). The combination of Lukas and Cella do not explicitly teach wherein the multi-dimensional model comprises nodes representing assets in the slice and links between nodes represent the inter-dependencies between corresponding assets, wherein a shape, size and color of each node represents a feature of the corresponding asset and a length, thickness and color of the links represent a feature of the inter-dependencies, wherein the size of the each node represents at least one of the security state or the risk score of the corresponding assets; However, from the same field, Chiba teaches wherein the multi-dimensional model comprises nodes representing assets in the slice and links between nodes represent the inter-dependencies between corresponding assets, wherein a shape, size and color of each node represents a feature of the corresponding asset and a length, thickness and color of the links represent a feature of the inter-dependencies, wherein the size of each node represents at least one of the security state or the risk score of the corresponding assets; (Par. [0067] when creating a graph for user visualization, the line color (i.e. link color), line thickness, line kind, character font, character color, background color, dot size (i.e. node size), dot color, expansion and contraction (i.e. shapes and lengths), and security features among other criteria are taken into consideration) It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the document perusal systems of Chiba into the database performance monitoring of Lukas. The motivation for this combination would have been to make it possible for the file user to peruse the converted document file as explained in Chiba (Par. [0012]). Regarding claim 2, Lukas, Cella and Chiba teach claim 1 as shown above, and Lukas further teaches The system of claim 1, wherein the one or more first criteria include at least one of: an asset type; a solution stack; or a geolocation. (Fig. 1 #128; Par. [0026] database performance monitor receives data about virtual (i.e. first filter criteria containing an asset type) and hardware networks) Regarding claim 3, Lukas, Cella and Chiba teach claim 1 as shown above, and Cella further teaches The system of claim 1, wherein the state of each asset of the set of filtered assets includes at least one of: a rank of the asset; a stress level of the asset; a compliance state of the asset; configuration settings of the asset; dependencies of the asset; or communications of the asset with a predefined time interval. (Par. [0547] partial dependence plot is included in visualization) Regarding claim 4, Lukas, Cella and Chiba teach claim 1 as shown above, and Lukas further teaches The system of claim 1, wherein the one or more slicing criteria include at least one of: an asset category; an asset functionality; an asset type; a solution stack; a geolocation; or one or more user profiles. (Fig. 1 #128; Par. [0026] database performance monitor receives data about virtual and hardware (i.e. second filter criteria containing an asset type) networks) Regarding claim 5, Lukas, Cella and Chiba teach claim 1 as shown above, and Cella further teaches The system of claim 1, wherein the one or more processors and the memory are configured, in generating the visual representation of the slice, to cause the system to generate a three-dimensional (3D) model of the slice. (Par. [0630] 3D rendering of assets in an environment is generated) Regarding claim 6, Lukas, Cella and Chiba teach claim 5 as shown above, and Cella further teaches The system of claim 5, wherein the one or more processors and the memory are configured to cause the system to augment the 3D model with metadata of assets of the slice of the plurality of different slices. (Par. [0629-30] 3D rendering of assets in an environment is generated with properties (i.e. metadata) presented for user adjustment) Regarding claim 7, Lukas, Cella and Chiba teach claim 1 as shown above, and Cella further teaches The system of claim 1, wherein the visual representation of the slice is an interactive visual representation. (Par. [0629-30] 3D rendering of assets in an environment is generated with properties presented for user adjustment (i.e. interactive)) Regarding claim 8, Lukas, Cella and Chiba teach claim 1 as shown above, and Lukas further teaches The system of claim 1, wherein the one or more processors and the memory are configured to cause the system to transmit the visual representation to the computing device associated with the user profile. (Fig. 8-14; Par. [0047] a visual list is presented indicating virtual and hardware network statuses) Regarding claim 9, Lukas, Cella and Chiba teach claim 1 as shown above, and Cella further teaches The system of claim 1, wherein the user profile includes a team profile. (Par. [1107] user investigating performance of various groups can include optional data filters including ones for a product team or marketing team among others) Regarding claim 10, please see the rejection for claim 1. Regarding claim 11, please see the rejection for claim 2. Regarding claim 12, please see the rejection for claim 3. Regarding claim 13, please see the rejection for claim 4. Regarding claim 14, please see the rejection for claim 5. Regarding claim 15, please see the rejection for claim 6. Regarding claim 16, please see the rejection for claim 7. Regarding claim 17, please see the rejection for claim 8. Regarding claim 18, please see the rejection for claim 9. Regarding claim 19, please see the rejection for claim 1. Regarding claim 20, please see the rejection for claim 4. Conclusion THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to J MITCHELL CURRAN whose telephone number is (469)295-9081. The examiner can normally be reached M-F 8:00am - 5:00pm. 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, Apu Mofiz can be reached on (571) 272-4080. 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. /J MITCHELL CURRAN/Examiner, Art Unit 2157 /APU M MOFIZ/Supervisory Patent Examiner, Art Unit 2161
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Prosecution Timeline

Jan 26, 2021
Application Filed
Oct 17, 2022
Non-Final Rejection — §103
Jan 30, 2023
Response Filed
Feb 25, 2023
Final Rejection — §103
Jun 05, 2023
Response after Non-Final Action
Jun 20, 2023
Response after Non-Final Action
Jun 30, 2023
Request for Continued Examination
Jul 12, 2023
Response after Non-Final Action
Aug 01, 2023
Non-Final Rejection — §103
Dec 18, 2023
Examiner Interview Summary
Dec 18, 2023
Applicant Interview (Telephonic)
Jan 16, 2024
Response Filed
May 04, 2024
Final Rejection — §103
Sep 09, 2024
Request for Continued Examination
Sep 12, 2024
Response after Non-Final Action
Sep 18, 2024
Non-Final Rejection — §103
Mar 19, 2025
Response Filed
Apr 05, 2025
Final Rejection — §103
Oct 10, 2025
Request for Continued Examination
Oct 14, 2025
Response after Non-Final Action
Dec 18, 2025
Non-Final Rejection — §103
Mar 23, 2026
Response Filed
Mar 31, 2026
Applicant Interview (Telephonic)
Apr 01, 2026
Examiner Interview Summary

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

7-8
Expected OA Rounds
61%
Grant Probability
96%
With Interview (+34.8%)
3y 6m
Median Time to Grant
High
PTA Risk
Based on 106 resolved cases by this examiner. Grant probability derived from career allow rate.

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