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 communication is in response to application 18/146,181 request for continued examination submitted 11/04/2025. Claims 1, 7, and 13 are amended and hereby entered. Claims 3, 5, 9, 11, 15, and 17 are canceled. Claims 1-2, 4, 6-8, 10, 12-14, 16, 18 are currently pending are examined. No claims are allowed.
Response to Arguments
Applicant's arguments filed 11/04/2025 regarding USC 101 and 103 have been fully considered but they are not persuasive.
Regarding 35 USC 101: The applicant submits the independent claims do not recite a judicial exception based on the newly amended portion of the claim. However, this still falls under the abstract idea of mental processes as the invention is directed to collecting, analyzing, and displaying the results of analysis, see MPEP 2106.04(a)(2)(III)(A). The newly amended claim now recites the use of weighting in order to make recommendations. Although the process may require weighting features to output a better recommendation, this still is directed to an abstract idea that can be performed in the human mind. For example, when making a collaboration recommendation, a person may be more likely to recommend two users who have recently worked together to collaborate again. Out of the information that is used to make a recommendation, the recency in which the users worked together is given weight in the decision making. Therefore, simply adding a weighting feature to data elements still recites an abstract idea. The claim itself is not directed to a data manipulation technique similar to Research Corp. Techs, but rather organizes the data for analysis to make a recommendation (i.e. some features are more important when making a recommendation, so they are weighted as such).
The applicant submits that the independent claims are directed to an improvement to technology that integrates the judicial exception into practical application. Specifically, the applicant states that the claims include features that improve the functioning of an engagement recommendation system. However, this engagement recommendation, (i.e. mental process), is part of the abstract idea, not an additional element that can integrate the judicial exception, see MPEP 2106.04(a)(2)(III). There is no improvement to technology as the claims are directed to “improving” an abstract idea. As previously discussed, weighting is still part of the abstract idea of making an engagement recommendation. Therefore, it is not an additional element that can integrate the abstract idea into a practical application. There is no improvement to technology because the additional elements, (general purpose computing components) are simply used to perform the abstract idea, see MPEP 2106.05(f). Therefore, the examiner respectfully disagrees and the rejection is maintained.
Regarding 35 USC 103: The applicant submits that Dicker does not teach newly amended features in claims 1, 7, and 13. These limitations are recited in the previously presented dependent claim 5. The applicant submits the claim elements describing the determination of weights are not listed in an alternative using a “or” conjunction, but rather recites “and” to include all elements in the list. However, the determination of the weights is not a positively recited step. The list simply describes intended results of what the determination of weights looks like, not a determining step of how the weights are calculated. Therefore, elements in the list describing intended results of the claim are not given patentable weight, and the previously referenced prior art still meets the claim, see MPEP 2111.04. Therefore, the rejection is maintained.
Although currently there is no positive recitation of a determining step, it appears the applicant’s intent may have been to include a positively recited determination step that includes the elements in a non-alternative structure. However, even if the elements are amended to be positively recited, these elements can still be found in the existing prior art. Out of courtesy to the applicant and to promote compact prosecution, the examiner provides examples of this below:
Quantity of edges is shown in Dicker; see at least: (Column 9, Lines 30-39) “For instance, site 106 may determine the most important users to user 102 (e.g., the five users in the network of user 102 having the highest symmetrical and/or directional edge strengths) and may apprise user 102 of recent activity of these five most important users. That is, site 106 may personalize a news feed associated with user 102 based on strengths of edges between user 102 and members of the user's network.”
Period of time is shown in Dicker; see at least: (Column 8, Lines 24-27) “Additionally, these calculated edge strengths may decay with time in order to ensure that previously strong but now discontinued or less strong relationships do not continue to demonstrate misleading high edge strengths”, (Column 8, Lines 14-17) “For instance, a strength of an edge connecting user 102 and a user for whom user 102 recently purchased a $600 gift for may be relatively high”.
Whether one or more users of the individual users voluntarily joined the respective communication channel is shown in Dicker; see at least: (Column 6, Lines 7-15) “For instance, the identity of the users interacting with one another may be logged and stored in database 134. Other information may include a frequency of play with the users, identities of users that engage in chats with one another (e.g., via a voice or text chat), identities of users who send and/or receive invitations to play or interact over the network, identities of users who send and/or receive invitations to join a network of friends, or the like”, (Claim 18) “attending an event with the second user, or joining a group that includes the second user.”
The prior art shown above is based on the applicant’s arguments, and it is intended to be purely exemplary based on the broad concepts discussed. The examples are simply provided as a courtesy to the applicant. They not an official rejection based on 35 USC 103. Any future claim amendments made by the applicant will be examined independently to these examples and could necessitate similar or different prior art in accordance to 35 USC 103.
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.
Claim 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more.
The claimed invention is directed to an abstract idea in that the instant application is directed to a mental process (See MPEP 2106.04(a)(2)(III)). The independent claims (1, 7, and 13) recite a method and systems to evaluate data associated with various entities and make recommendations based on the processed data. These claim elements are being interpreted as concepts performed in the human mind (including observation, evaluation, judgement, and opinion). Using social graph data to make recommendations can equivalently be achieved by human observation and evaluation of communications and entity information. For example, analyzing data and other information related to users can be done by a human to make recommendations and suggestions. The claims recite an abstract idea consistent with the “mental process” grouping set forth in the MPEP 2106.04(a)(2)(III).
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites an “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea. The instant application is directed towards a method and systems to implement the identified abstract idea of receiving information, processing information, and displaying the result of the analysis (i.e. processing graphical data structure information to recommend collaboration connections and the like) in a general-purpose computing environment. The independent claims recite the additional elements “a processor” and “a non-transitory computer-readable medium”. These claim elements are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using general-purpose computing components. The machines merely act as a modality to implement the abstract idea and are not indicative of integration into a practical application (i.e., the additional elements are simply used as a tool to perform the abstract idea), see MPEP 2106.05(f).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in Step 2A Prong Two analysis, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies here in 2B and does not provide an inventive concept.
In regards to the dependent claims
Claims 2, 4, 6, 8, 10, 12, 14, 16, and 18 do not introduce any new additional abstract ideas or new additional elements and do not impact analysis under 35 USC 101.
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, 7, 13), (2, 8, 14), (4, 10, 16), and (6, 12, 18) are rejected under 35 U.S.C. 103 as being unpatentable over McGarr (US 20220351142 A1) in view of Dicker (US 8606721 B1) in further view of Cho (US 20170255708 A1).
Regarding Claim 1, 7 and 13 (substantially similar in scope and language), McGarr teaches:
A method, an apparatus, and non-transitory computer-readable medium [see at least McGarr: (Figure 1), (Para 33-35)] comprising retrieving, from a first data source associated with a group-based communication platform associated with an entity, connection information of a plurality of users of the group-based communication platform, [(Para 5), (Para 14) “The communication platform can be a group-based communication platform”, (Para 15) “The organizational data can include data associated with the organization, such as… user data… team data”, (Para 0051) “ the organizational data can include the organizational graph, such as in pre-determined structure of working relationships”] the connection information corresponding to inclusion of individual users of the plurality of users in one or more communication channels of the group-based communication platform; [(Para 15) “The organizational data can include data associated with the organization, such as.. user data… associated workspaces and/or channels”] retrieving, from a second data source associated with the entity, membership information of the plurality of users, the membership information corresponding to inclusion of the individual users of the plurality of users [(Para 6) “an example user interface for identifying members of an organization based on one or more attributes of the members, as described herein.”] in one or more groups of a plurality of groups associated with the entity; [(Para 14) “The communication platform can determine that one or more of the users of the first group often collaborate with a user associated with a second group of the organization (e.g., a second team),”] generating a graphical data structure comprising: generating one or more user nodes corresponding to identifiers for the plurality of users, [(Para 0018) “In various examples, the communication platform can generate an interaction graph representative of communications and data flow between users of an organization.”] generating one or more group nodes corresponding to the one or more groups associated with the entity, [(Para 0018) “ In some examples, the interaction graph can represent the communications across an entire organization and/or between two or more organizations.”] generating one or more connection edges corresponding to the connection information, [(Para 0048) “In various examples, the interaction graph can represent real-time collaborations and/or working relationships between users of the organization”] generating one or more membership edges corresponding to the membership information, or any combination thereof; [(Para 0019) “team and/or workspace membership of each of the user(s)”, (Para 0096) “In such an example, the data can provide the user 200 with up to date information associated with connections of the user”]
and generating, based at least in part on the connection information, the membership information, and the graphical data structure, an engagement recommendation for users of the plurality of users included in a first group of the one or more groups to engage with users of the plurality of users included in a second group of the one or more groups. [(Fig 9), (Para 0012) “process for recommending an action to perform to increase collaboration between groups of users,”]
While McGarr teaches generating a graphical data structure with various data and relationships, it does not explicitly teach the use of nodes and edges in the graphical data structure related to the various data and relationships, weighting edges, or grouping of edges.
However, Dicker teaches:
nodes and edges related to various types of data and relationships [see at least Dicker: (Col 2, Lines 16-19) “As discussed above, the nodes of social graphs may represent people, organizations, or other sorts of entities. The edges between the nodes, meanwhile, may represent interdependency or a relationship between the nodes”]
wherein the one or more communication connections between the individual users indicated in the connection information are weighted based at least in part on one or more weights associated with the one or more communication channels, [(Column 7, Lines 19-22) “To determine these affinities, module 136 may weight each type of activity stored within database 134. These weighted activities may then be summed to determine one or more affinities”, (Column 8, Lines 6-9) “With use of these determined affinities, edge strength calculator 138 functions to calculate and assign an edge strength to each edge connecting the node associated with the first user with each node associated with the other three users.”]
the one or more weights determined based at least in part on a respective quantity of edges corresponding to the connection information that pass through a respective communication channel passthrough node, a period of time since a last interaction event occurred in the respective communication channel associated with the respective communication channel passthrough node, and whether one or more users of the individual users voluntarily joined the respective communication channel. [(Column 7, Lines 38-43) “Other group heuristics may also be leveraged in weighting users' memberships in groups. For instance, being a member of a smaller group may be weighted more heavily than being a member of a larger group. These weights may also vary based on other heuristics, such as a type of group or a level of activity of the group.” (Column 8, Lines 14-17) “For instance, a strength of an edge connecting user 102 and a user for whom user 102 recently purchased a $600 gift for may be relatively high.”]
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date to combine the method of generating a graphical data structure with various data and relationships taught by McGarr, with the use of nodes, edges and weighting taught by Dicker. It is well within the capabilities of one of ordinary skill in the art to represent the data and relationships taught by McGarr with a social graph that includes nodes, edges and weighting taught by Dicker, yielding the predictable result of a social graph representing the elements taught by McGarr. One of ordinary skill would have recognized the benefits of weighting to better recommend collaborations between users based on specific features.
While McGarr in view of Dicker teach generating graphical data structure with various data/relationships, and the use of nodes, edges, and weighting, it does not explicitly teach the grouping of edges. However, Cho teaches:
and generating one or more communication channel passthrough nodes that organize the one or more connection edges into groups based at least in part on one or more associations between the one or more communication channels and the connection information [(Para 0041) “Compaction of the edges in compact representation 310 may be achieved by sorting the edges by a first attribute, further sorting the edges by a second attribute within each grouping of the edges by the first attribute, and specifying a set of values for one or more additional attributes of the edges for each grouping of the edges by the first, second, and/or third attributes”]
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of generating a graphical data structure with various data and relationships represented by nodes and edges taught by McGarr in view of Dicker, with the method of grouping edges taught by Cho. It is well within the capabilities of one of ordinary skill to organize the data in a social graph by grouping edges, yielding a predictable result.
Regarding Claim 2, 8, and 14, McGarr in view of Dicker in further view of Cho teach the limitations set forth above, McGarr further teaches:
based at least in part on one or more communication connections between the individual users, [(Para 0048) “In various examples, the interaction graph can represent real-time collaborations and/or working relationships between users of the organization… [b]ased on first-party information (e.g., messages exchanged between users)”] wherein the engagement recommendation is generated based at least in part on generating the communication connection strength values. [(Para 0014) “interaction between the one or more users of the first group and the user of the second group is above a threshold level of interaction, the communication platform can provide a recommended action for the user to perform with respect to the communication platform”]
While McGarr teaches the use of communication connections between users and engagement recommendations, it does not explicitly teach generating strength values. However, Dicker teaches:
generating communication connection strength values between the individual users indicated in the connection information [(Col 1 Lines 36-37) “example architecture for calculating strengths of edges connecting nodes in a social graph” (Col 1 Lines 59-60) “This disclosure is directed to, among others, calculating edge strengths for edges of a social graph.”]
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date to combine the generation of strength values, taught by Dicker, with the use of the data to make recommendations taught by McGarr. Simply substituting a communications frequency threshold, for a communication connection strength value to determine a recommendation be made, would yield predictable results.
Regarding Claims 4, 10, and 16, McGarr in view of Dicker in further view of Cho teach the limitations set forth above, McGarr further teaches:
based at least in part on the membership information and the communication connection strength values between users of the individual groups; [(Para 0050) “In some examples, the interaction graph can include a representation of a frequency of messages and/or associated weights of messages sent by a particular user. In such examples, the interaction graph can represent a level of effectiveness and/or a professional contribution that the particular user adds to a team and/or an organization.”] wherein the engagement recommendation is generated based at least in part on a first group connection strength value of the group connection strength values that is associated with the first group and the second group. [(Para 0011) “recommending an action to perform with respect to a group of users based on a frequency of messages received by the group of users”, (Para 0014) “interaction between the one or more users of the first group and the user of the second group is above a threshold level of interaction, the communication platform can provide a recommended action for the user to perform with respect to the communication platform”]
While McGarr teaches the use of communication connections between users and engagement recommendations, it does not explicitly teach generating strength values. However, Dicker teaches:
generating group connection strength values between individual groups of the plurality of groups associated with the entity [(Col 1 Lines 36-37) “example architecture for calculating strengths of edges connecting nodes in a social graph” (Col 1 Lines 59-60) “This disclosure is directed to, among others, calculating edge strengths for edges of a social graph.”]
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date to combine the generation of strength values, taught by Dicker, with the use of the data to make recommendations taught by McGarr. Simply substituting a communications frequency threshold, for group connection strength values to determine a recommendation be made, would yield predictable results.
Regarding Claims 6, 12, and 18, McGarr in view of Dicker in further view of Cho teach the limitations set forth above, McGarr further teaches:
wherein the one or more groups associated with the entity correspond to one or more functional roles of the plurality of users within the entity. [(Para 0014) “In some examples, groups of the communication platform can be determined based on organizational graphs, or other organizational data, of organizations” (Para 0015) “organizational data can include data associated with the organization, such as … user data… employment data (e.g., position, title, team association, reporting manager, etc.), etc.), team data (e.g., team members, team identifiers, associated projects, team expertise or focus areas”]
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Examiner Benjamin Truong, whose telephone number is 703-756-5883. The examiner can normally be reached on Monday-Friday from 9 am to 5 pm (EST)
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/B.L.T./
Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626