DETAILED ACTION
Claims 1-12 are pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/2/2026 is being considered by the examiner.
Response to Arguments
Applicant's arguments filed 4/2/2026 have been fully considered but they are not persuasive.
A. Applicant argues the prior art does not teach determining whether the received data regarding the communication between the first node and the second node exceeds a predefined threshold metric; and if the received data regarding the communication between the first node and the second node exceeds the predefined threshold metric, storing an indicating of success.
However, the examiner respectfully disagrees. Prior art Adamski teaches “FIG. 8C shows the same video chat user interface after even more puzzle pieces have been removed. In this implementation, the system removes a puzzle piece when the verbal word count from the conversation meets a threshold number of words. For example, the system may monitor and count the number of words collectively spoken by Mark and Mary, and once this number of words satisfies a certain threshold (e.g., fifty words), the system may remove a puzzle piece from each of Mark and Mary's faces…,” ( Col. 27, Lines 34-49). Thus, the verbal word count exceeding a threshold number of words, (determining whether received data regarding the communication between two nodes meets and exceeds a threshold), then puzzle pieces are removed, (storing an indicator of success, meaning the clearer the video chat between users indicates success) Furthermore, Figures 9E and 9F show how word count between users exceeding thresholds, more content and user profiles is revealed or unlocked. The revealing and unlocking of content/profile is the storing of success, otherwise the user would not be able to access this content. Therefore, applicant’s arguments are not persuasive.
B. Applicant argues there is no motivation to combine Nimri and Adamski.
However, the examiner respectfully disagrees. In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, Nimri is focused on scheduling conferences based upon various criteria, and Adamski improves upon the system of Nimri, by scheduling more personable conferences/meetings between users. Therefore, applicant’s arguments are not persuasive.
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.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Nimri (US 2010/0289867 A1) in view of Adamski (US 10,887,270 B1).
With regards to Claim 1, Nimri teaches a method comprising: by a computer with a processor and memory (i.e., Paragraph 61, processor, memory; Figure 2a), receiving data regarding a first node (i.e., In conferencing system 400, conference controller 402 uses information from participant detection system 404, scheduling application 405 and database 406 to automatically initiate a conference at endpoint 401 upon the arrival of a scheduled participant at endpoint 401…, Paragraph 54; Figure 3; arrival of endpoint 401 is receiving data regarding a first node); matching the first node data with a second node based on the received first node data by comparison to previously stored other nodes in a database (i.e., . When conference controller determines that participant A is located at endpoint 401 at or near the time scheduled for the conference, conference controller initiates a connection between endpoint 401 and endpoint 407 associated with participant B. Conference controller can obtain connection parameters for endpoint 407 from scheduling application 405 and/or from database 406 and instruct endpoint 401 to initiate a connection with endpoint 407. If endpoint 407 is within the same premises or enterprise, then endpoint 407 may also be associated with a participant detection system 408, Paragraph 54; matching 401 with 407; Figures 3-4; Paragraph 5; Claim 5); scheduling a communication between the first node an a matched second node from the database using data of the first node and stored data of the second node (i.e., Beginning at block 310 a participant's location can be determined utilizing any of the methods disclosed herein. Next at block 320 a meeting schedule may be retrieved from a scheduling server. The participants scheduled for a meeting at a particular location may be matched at block 330, Paragraph 50; . Conference controller 402 is also communicatively connected to database 406 that can include information on the employees of the organization including information such as names, employee's ID number, list of security permissions, email address, telephone numbers, IP address, buddy list, etc. Database 406 also includes participant identification parameters used in combination with participant detection system 404, as explained in more detail below. Database 406 may be integral with conference controller 402, with scheduling application 405, or may be comprised in one or more separate computing devices, Paragraph 53); initiating the scheduled communication between the first node and the second node using the first node communications data and stored communications data of the second node (i.e., FIG. 3 illustrates relevant processes 300 for automatically initiating a conference based on the proximity of a scheduled participant…, Paragraph 50; Conference controller can obtain connection parameters for endpoint 407 from scheduling application 405 and/or from database 406 and instruct endpoint 401 to initiate a connection with endpoint 407…, Paragraph 54; Paragraph 53); receiving data regarding the communication between the first node and the second node (i.e., monitored input data comprises audio data and processing the input data to determine a match comprises using voice recognition software, Claim 6, Claim 10; Paragraph 57; monitoring voice data).
However, Nimri does not explicitly disclose determining whether the received data regarding the communication between the first node and the second node exceeds a predefined threshold metric; and if the received data regarding the communication between the first node and the second node exceeds the predefined threshold metric, storing an indicator of success. Adamski does teach determining whether the received data regarding the communication between the first node and the second node exceeds a predefined threshold metric; and if the received data regarding the communication between the first node and the second node exceeds the predefined threshold metric, storing an indicator of success (i.e., FIG. 8C shows the same video chat user interface after even more puzzle pieces have been removed. In this implementation, the system removes a puzzle piece when the verbal word count from the conversation meets a threshold number of words. For example, the system may monitor and count the number of words collectively spoken by Mark and Mary, and once this number of words satisfies a certain threshold (e.g., fifty words), the system may remove a puzzle piece from each of Mark and Mary's faces…, Col. 27, Lines 34-49; Figures 9E-9F; profiles unlocked equivalent to an indicator of success) in order to provide more personable interactions between users (Col. 1, Lines 17-32). Therefore, based on Nimri in view of Adamski, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Adamski with the system of Nimri in order to provide more personable interactions between users.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Rapaport (US 2010/0205541 A1) in view of Adamski (US 10,887,270 B1).
With regards to Claim 12, Rapaport teaches a computer implemented method comprising: by a computer server, receiving data from a first node by a registration webpage API, and updating the digital database (i.e., . In one embodiment, template profiles that fit stereotypical persons within the system's user population are made available, applied to new users who are joining the system and then minor modifications are made to the applied stereotyping template profiles so that they become more representative of the associated individual user to whom they are applied, Paragraph 92; Paragraph 116; ); by the computer server, receiving data from the first node by an onboarding questionnaire and updating the digital database (i.e., Each new user may be initially asked to fill out a very short demographics questionnaire (e.g., just name, age, gender and place of birth or residence) from which a stereotyping model of the user is developed, Paragraph 129); by the computer server, receiving data regarding geography of the first node, and updating the digital database (i.e., Additionally, the local client software 105 may use various context cues, such as by detecting the location of the user via a GPS sensor 111z or other means (e.g., nearby RFID tags, nearby other equipment detected by wireless coupling via BlueTooth.TM. or the like) , Paragraph 80); by the computer server, receiving data regarding online web browsing activity of the first node, and updating the digital database (i.e., . All of this information about user activities associated with the reading of the news article 117a (primary focused-upon content) is relayed into the user's browser history 105c and search history 105e (or into cloud-maintained versions of such histories) and is interpreted by the machine means (e.g., by use of knowledge-base rules) as providing additional clues regarding the user's implied topic or topic domain for the focused on content appearing in screen area 117a, Paragraph 84); by the computer server, recording audio data of a voice of the first node to create audio data of the first node, and updating the digital database (i.e., . The special software may use voice recognition modules to automatically detect the unusual use of objectionable language by the user and/or change in voice tonality, change in stress levels or in other vocal system parameters (e.g., including changed breathing patterns) to classify this behavior, Paragraph 178); by the computer server, applying natural language processing to input from the first node, and updating the digital database (i.e., . The special software may use voice recognition modules to automatically detect the unusual use of objectionable language by the user and/or change in voice tonality, change in stress levels or in other vocal system parameters (e.g., including changed breathing patterns) to classify this behavior, Paragraph 178); by the computer server, storing all of the data regarding the first node in a data storage, and updating the digital database (i.e., The demographic data of the local user 121'' is stored in a database region represented in FIG. 1B by the first horizontal region 171 (which may have plural rows) and the first vertical column 154 labeled "mine" (which in some cases may have plural subcolumns)…, paragraph 98); by a computer server, receiving data from a second node by a registration webpage API, and updating the digital database (i.e., . In one embodiment, template profiles that fit stereotypical persons within the system's user population are made available, applied to new users who are joining the system and then minor modifications are made to the applied stereotyping template profiles so that they become more representative of the associated individual user to whom they are applied, Paragraph 92; Paragraph 116; ); by the computer server, receiving data from the second node by an onboarding questionnaire and updating the digital database (i.e., Each new user may be initially asked to fill out a very short demographics questionnaire (e.g., just name, age, gender and place of birth or residence) from which a stereotyping model of the user is developed, Paragraph 129); by the computer server, receiving data regarding geography of the second node, and updating the digital database (i.e., Additionally, the local client software 105 may use various context cues, such as by detecting the location of the user via a GPS sensor 111z or other means (e.g., nearby RFID tags, nearby other equipment detected by wireless coupling via BlueTooth.TM. or the like) , Paragraph 80); by the computer server, receiving data regarding online web browsing activity of the second node, and updating the digital database (i.e., . All of this information about user activities associated with the reading of the news article 117a (primary focused-upon content) is relayed into the user's browser history 105c and search history 105e (or into cloud-maintained versions of such histories) and is interpreted by the machine means (e.g., by use of knowledge-base rules) as providing additional clues regarding the user's implied topic or topic domain for the focused on content appearing in screen area 117a, Paragraph 84); by the computer server, recording audio data of a voice of the second node to create audio data of the first node, and updating the digital database (i.e., . The special software may use voice recognition modules to automatically detect the unusual use of objectionable language by the user and/or change in voice tonality, change in stress levels or in other vocal system parameters (e.g., including changed breathing patterns) to classify this behavior, Paragraph 178); by the computer server, applying natural language processing to input from the second node, and updating the digital database (i.e., . The special software may use voice recognition modules to automatically detect the unusual use of objectionable language by the user and/or change in voice tonality, change in stress levels or in other vocal system parameters (e.g., including changed breathing patterns) to classify this behavior, Paragraph 178); by the computer server, storing all of the data regarding the second node in a data storage, and updating the digital database (i.e., The demographic data of the local user 121'' is stored in a database region represented in FIG. 1B by the first horizontal region 171 (which may have plural rows) and the first vertical column 154 labeled "mine" (which in some cases may have plural subcolumns)…, paragraph 98); using the data regarding the first node and the data regarding the second node to determine a match (i.e., he uploaded and optionally parsed and merged CFi-provided data items obtained from each of the different users are then automatically compared to that of other users (or against composite data of ongoing chat rooms) in the MM-IGS for purpose of matching with one another (user-to-user match-making or clustering) and/or for purpose of matching with predefined chat rooms (user-to-room match-making), Paragraph 31); if a match is determined, sending a communication to the first node and the second node to initiate communication between the first node and the second node (i.e., If yes, the user(s) having the identified and currently common focus on same or similar content and/or having the same or similar topic of interest currently on their minds, are automatically invited to join in a system-spawned chat room or to exchange information using another real-time and system-supported information exchange mechanism (e.g., a live video web conference or a live voice only conference, etc.), where in one embodiment the invitations are sent to users who also have current personality-based co-compatibility for chatting with each other…, Paragraph 31).
However, Rapaport does not explicitly disclose receiving data regarding the communication; determining whether the received data regarding the communication between the first node and the second node exceeds a predefined threshold metric; and if the received data regarding the communication between the first node and the second node exceeds the predefined threshold metric, storing an indicator of success. Adamski does teach receiving data regarding the communication; determining whether the received data regarding the communication between the first node and the second node exceeds a predefined threshold metric; and if the received data regarding the communication between the first node and the second node exceeds the predefined threshold metric, storing an indicator of success (i.e., FIG. 8C shows the same video chat user interface after even more puzzle pieces have been removed. In this implementation, the system removes a puzzle piece when the verbal word count from the conversation meets a threshold number of words. For example, the system may monitor and count the number of words collectively spoken by Mark and Mary, and once this number of words satisfies a certain threshold (e.g., fifty words), the system may remove a puzzle piece from each of Mark and Mary's faces…, Col. 27, Lines 34-49; Figures 9E-9F; profiles unlocked equivalent to an indicator of success) in order to provide more personable interactions between users (Col. 1, Lines 17-32). Therefore, based on Rapaport in view of Adamski, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Adamski with the system of Rapaport in order to provide more personable interactions between users.
Allowable Subject Matter
Claims 2-11 are allowed.
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 SURAJ M JOSHI whose telephone number is (571)270-7209. The examiner can normally be reached Monday - Friday 8-6 ET.
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, Joon Hwang can be reached at (571)272-4036. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SURAJ M JOSHI/Primary Examiner, Art Unit 2447 June 22, 2026
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