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 .
Status of Claims
The office action is in response to the amendment filed by the applicant on July 3, 2025 in further continued examination to the Examiner’s Final Office Action on the merits filed February 13, 2025.
Claims 1, 4-5, 8, 11-12, 15, 17-18 and 22-24 are pending and have been examined.
Claims 2-3, 6-7, 9-10, 13-14,16-17, 19-21 have been cancelled.
This action is made NON-FINAL.
Foreign Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. 202241040188, filed on July 13, 2022.
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments
The Examiner respectfully acknowledges the cancellation of claim 21. Since claim 21 was cancelled, the objection is Moot and are Withdrawn.
35 U.S.C. § 112(a) and (b)
The Examiner respectfully acknowledges the cancellation of claims 3, 10, 17, and 21. Since the claims from which the 35 U.S.C. § 112(a) and 35 U.S.C. § 112(b) rejections were asserted have been cancelled, therejections are Moot and are withdrawn.
35 U.S.C. § 101
Applicant's arguments filed October 31, 2025 have been fully considered but they are not persuasive.
With regards to the arguments on pages 8-9, the applicants’ assertion that the enterprise device management system and data analysis technologies are technologically improved are not persuasive. Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically identifying additional elements from the claims or specification. Further, the arguments fail to address how recited or disclosed additional elements amount to significantly more than these abstract ideas, i.e. generating the data structure and enrolling clients. Since the additional elements addressed in the arguments are not supported in the claims or the specification, the assertions misrepresent the comprehensive analysis by failing to address recited or disclosed additional elements or particularly pointing out how the recited or disclosed additional elements are significantly more than the abstract ideas.
With regards to the arguments on pages 9-10, the Applicant’s assertion that generating a graph data structure… assigning weights… is not a mathematical relationship or formula because it is a specific computer-implemented data model, is not persuasive. First, the Examiner did not identify that the claims recite the abstract idea of mathematical concepts in the sub-category of mathematical formulas. Instead, the abstract ideas were identified in the sub-categories of mathematical relationships and mathematical calculations. Generating a graph data structure describes a functional result, implemented on general purpose computing structures. The claims perform generic business functions that attempt to cover any solution to the problem with no restriction on how the result of generating the graph data structure or calculating the weights are accomplished, and no description of the mechanism for accomplishing the result, not a concrete data model. Assigning a calculated weight based on frequency and age of communications draws focus to the nature of the data being manipulated, the communications, versus the technique of processing the data. Therefore, these limitations are mathematical relationships and calculations in at least the abstract idea category of mathematical concepts. This technique of manipulating relationship data through the implementation of the recited abstract ideas, i.e. according to at least the mathematical relationships and calculations on and generally linked to general-purpose computing structures, are not indicative of a practical application and the computing structures are not enough to amount to significantly more.
With regards to the arguments on page 10, the Applicant’s assertions that using calculated weights to create and maintain a graph focuses on an improvement to the graph, such that the weight calculations are no longer abstract ideas, is not persuasive. The assertions fail to present the analyses to support the conclusions. McRO utilizes mathematical calculations to produce accurate and realistic lip synchronization and facial expressions in animated characters that previously could only be produced by human animators by hand, such that the invention produced a new computerized method of computer animation. The instant application diverges from McRO because, while the mathematical calculations in this invention form the additional element, i.e. the graph, this particular graph data structure is a utilized as characterized database to hold data for storage, querying and organization purposes, which does not represent a new method of formulating databases or graphs. The specification does not reveal advances to the generation and updating graphs or of databases, i.e. general-purpose computing structures disclosed and recited at a high level of generality. Both the claim and the specification recite or disclose general-purpose computing structures performing generic business functions, i.e. math calculations to form and update a graph, that attempt to cover any solution to the problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. Therefore, after analyzing the claims according to the arguments and previous Examiner position, and reexamining the amended claims, the analysis of McRO does not apply to the mathematical calculations, which are upheld as directed to an abstract idea without significantly more.
With regards to the arguments on page 10, the Applicant’s assertions that the mathematical operations are integrated into a technical process that (1) effectuate a transformation of unstructured communications data into the weighted graph model, and (2) effectuate a technical improvement to how computing systems model, analyze, and interpret communications data due to producing a graph data model, are not persuasive. The broadest reasonable interpretation of a weighted graph model is the assembled graph including weighted lines representing the data manipulated from collected relationship and communications data, and nodes representing the users that executed the communications. The additional elements are those comprised within the preambles, as well as the graph data structure, nodes, and edges. With regards to a transformation, according to MPEP 2016.05(c), “for data, "manipulation of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’" has not been deemed a transformation.” A transformation requires a particular identifiable physical object or substance to change to a different object, substance, state, or thing that has different uses. Mathematically manipulating data held in one characterized database, a user device, that is used to form part of another database, the lines between user nodes, is not a change of a physical object to a different object, state, thing, or substance that has different uses. Therefore, there is no transformation effected when analyzed according to the Applicant’s arguments, examined according to the Examiner’s previous position, and reexamined according to 35 U.S.C. § 101 in the amendments.
Further, the mathematical operations produce the particular graph data structure, a database. The specification does not disclose advances to mathematical operations or the production of graphs or databases. The database is applied as a tool to store and organize data used to rank or select data in subsequent but separate steps. Therefore, the claims recite the use of calculated weights to form and store data in a graph, i.e. a characterized database. The database is used as a tool to analyze, model, and interpret data, i.e. used as a tool to allow performance of future data manipulations, which is not an improvement to the functioning of a computing system or any other technology or technical field. The database is included in the full scope of general-purpose computing structures that are identified fully in the 35 U.S.C. § 101 below as additional elements. These additional elements, when viewed individually or as an ordered pair, are not enough to amount to significantly more than the abstract idea of mathematically manipulating data, when analyzed according to the Applicant’s arguments, examined according to the Examiner’s previous position, and reexamined according to 35 U.S.C. § 101 in the amendments.
With regards to the arguments on page 10, that the graph data structure improves how the system manages and queries data, which is a specific data structure that improves computing operations, similar to Enfish, is not persuasive. In Enfish, the courts determined that the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims, according to the specification. In the instant invention, the graph data structure is recited in the claims and disclosed in the specification as a general-purpose database structure. The specification does not reveal advances to databases or graphs, disclosing general-purpose computing structures performing generic business functions that attempt to cover any solution to the problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. Therefore, when analyzed according to the Applicant’s arguments, examined according to the Examiner’s previous position, and reexamined according to 35 U.S.C. § 101 in the amendments, there is no correlation between the instant invention and Enfish, and therefore there is no improvement to the functioning of a computing structure, of databases, or of data manipulations utilizing databases as a tool.
With regards to the arguments on page 10, the Applicant’s assertions that enrolling clients into a directory is a technical operation and not a human or commercial activity because it involves enrolling the devices and not the human, addressing a technological problem in enterprise device management security and access privileges, are not persuasive. The specification does not reveal that the core of the invention discloses advances to networking, device provisioning, security, access rights, or enterprise device management. The claim recites enroll client devices, where the claim language is directed to the significance of the user to the device. Enrolling a user device into a corporate directory allows a business to manage the data held on the user device, including relationship data, comprised within communications between users. This limitation, when analyzed according to the Applicant’s arguments, examined according to the Examiner’s previous position, and reexamined according to 35 U.S.C. § 101 in the amendments continue to exhibit individual and interconnected business relationships and human behaviors, in the referenced sub-categories of "Certain Methods of Organizing Human Activity.”
With regards to the arguments on page 11, the Applicant’s assertions that the instant invention is similar to DDR Holdings because the claimed enrollment process addresses a technological problem in secure device management and provisioning, similar to DDR Holdings, are not persuasive. DDR Holdings resulted in the claim limitation for generating a composite web page that keeps a user on a host site while showing third-party merchant content, was not an abstract idea because it addressed a business challenge particular to the internet—retaining website visitors who would otherwise leave when clicking a third-party ad. The courts determined that this solution to the challenge was necessarily rooted in computer technology to solve the web-specific problem. The instant invention diverges from DDR Holdings because the specification does not reveal advances to secure device management, provisioning of software, or data access over a network. The enrollment process, according to the specification ¶’s [0018-0020] is a manner of installing software on the user’s device to add the user to a database network. After the user grants permission, the software permits the system or an administrator to access the user’s data via the software on their device, allowing their database to be accessible such that the user’s communications data may be manipulated according to subsequent limitations. The claims recite general-purpose computing structures, performing generic business functions and software instructions that attempt to cover any solution to the problem of secure device management, management software provisioning, and managing permissions and privileges that grant data access, with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. Therefore, the enrolling limitation, when analyzed according to the Applicant’s arguments, examined according to the Examiner’s previous position, and reexamined according to 35 U.S.C. § 101 in the amendments, continues to recite the presented abstract ideas.
With regards to Step 2A, Prong 2, the Applicant’s assertions on pages 11-12, that the additional elements are used by algorithmic steps to produce the ranked contact list, which is a technological application and an improvement to computer functionality, are not persuasive. The argument with regards to the algorithmic steps is predicated on the assertion that the instant application uses algorithmic steps. However, the claims do not recite and the specification does not disclose algorithmic steps or an algorithm at all. Therefore, computing structures that implement instructions for a database to store data, i.e. weighted edges, is not a practical application, where the specification does not reveal advances to data storage or databases.
With regards to the arguments on page 11, the Applicant’s assertions that the use of a management component installed on a client device with elevated privileges to collect data is a technical operation that effects a transformation, are not persuasive. The management component is software installed on a user’s device, a general-purpose computing structure performing generic business functions invoked by the management component. The generic business functions of the management component attempt to cover any solution to the problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. Further, the Applicant does not disclose any arguments to support a transformation, i.e. it is unclear what specific identifiable physical object is undergoing a transformation, or what beginning physical state or ending physical state are recited or disclosed to support effectuating any physical transformation.
With regards to the arguments on page 11, the Applicant’s assertions that the graph data structure itself is a practical application of mathematical relationships, are unpersuasive. Using a graph database to allow data to be searched and dynamically assigned and updated, where the same data is generated into an alternate database, a ranked list that is sorted and filtered in an alternative characteristic manner, that enables further data manipulation, sorting, and filtering, is not a practical application of mathematical relationships. The additional elements, i.e. the general-purpose computing structures including either database structures characterized as a graph or a list, are recited at a high level of generality, and the claims attempts to cover any solution to the problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. These claimed steps are commonplace business methods being applied on general purpose computing structures, general methods of manipulating communications via generic computing structures, and recite gathering and analyzing information, all three disclosed in MPEP 2016.05(a) as examples that the courts have indicated may not be sufficient to show an improvement to technology.
With regards to the arguments on pages 11-12, the Applicant’s assertions that the transformation of unstructured communications data into the weighted graph model, is a technical solution that improves the functionality of a computer, are unpersuasive. The argument was asked and answered in ¶ 14 above and the conclusion, that manipulating data into characterized data does not effectuate a physical object to transform into a different physical object or state, remains the consistent. Further, ¶ 21 above addresses how a graph data structure does not improve computer functionality as argued. This data transformation of data to data stored in a graph database, does not constitute a practical application as observed above in ¶ 21.
On page 12, the Applicant’s arguments with respect to 35 U.S.C. § 101 Step 2B, asserting that the combination of elements is an inventive concept, are not persuasive. The Examiner asserts the presented arguments and conclusion in ¶ 20 above, regarding the management component allowing for secure access to the data that is manipulated to generate the graph. The additional elements the computing structures that the software management components are installed on, do not integrate the abstract ideas into a practical application and are not enough to amount to significantly more than the abstract ideas.
With regards to the arguments on page 12, the Applicant’s assertions that the specific arrangement of components provide a non-conventional architecture that improves computer functionality significantly more than the abstract idea are not persuasive. The assertion is not rooted in a rejection analysis presented by the Examiner, where the claims do not recite any extra solution activity that would merit the analysis according to well-understood, routine, and conventional analysis. The specification does not reveal that the core of the invention is focused on an improvement to the computing structures. The computing structures are disclosed in the specification as any non-specific general purpose computing structures, generally linked as tools to perform the identified abstract ideas comprised within the instructions recited in the claims. The computing structures are not applied in some other meaningful way beyond being generally linked or used to implement abstract ideas. The computing structures are not indicative of a practical application of, and do not amount to significantly more, than any abstract ideas.
For the reasons above, the 35 U.S.C. § 101 rejection is being maintained. Please find the updated 35 U.S.C. § 101 rejection below, revised to reflect the amendments.
35 U.S.C. § 103
Applicant’s arguments, see Remarks pages 10, filed 7/3/25, with respect to the 35 U.S.C. § 103, prior art rejections of claims 1, 4-5, 8, 11-12, 15, 18, and 22-24 have been fully considered and are not persuasive.
On Remarks page 12-14, the Applicant’s assertions regarding the prior art, that the amended features not formerly examined as part of claims 1, 8, and 15, are not taught or disclosed in the cited references, are not persuasive.
With regards to the arguments on pages 13-14, the Applicant’s assertion that the reference citations of Garton fail to assert the full scope of the claims, and further, that the citations of Olmstead and Pflughoeft, as a combined set of disclosures fail to teach or disclose all of the features of the amended claims, are not persuasive.
With regards to the arguments on page 13-14, the Applicant’s assertions that Garton only discloses the possibility of gathering data regarding the timing and direction of messaging, which is not equivalent to generating a graph data structure or any other part of the graph data structure data manipulations from the amended claim recitations, are not persuasive. The Applicant’s argument discloses only a partial section of the full scope of Garton citations presented by the Examiner in the previous Office Action. The partial list of citations, argued as not disclosing the graphing limitations, are presented by the Examiner for a different claim limitation directed to receiving data, but due to the amendments, may be included at least in part in the generating a graph limitation. This omission by the Applicant, of the particular sections of the prior art that are drawn to the specific limitations the Examiner purportedly missed, makes this argument unpersuasive because the argument is not germane to the full scope of prior art application as presented by the Examiner for the full scope of the generating a graph functions. The Examiner has updated the rejection to reflect the amendments, which incorporates previously presented, appropriate citations for all limitations of the generating a graph data structure function, including updated citations for the amendments. Further, since the assertion was a mischaracterization of the application of the prior art, the assertion that Garton in view of Olmstead and further in view of Pflughoeft fail to contain any of the limitations for generating a graph data structure, is also unpersuasive, because it is a mischaracterization of the full scope of the rejection, where Garton teaches the full scope of the generating a graph data structure claim limitations as recited in the amended claims, and Garton taught all of the previously presented limitations drawn to generating a graph data structure section of the claims.
Accordingly based on the above and the detailed analysis below, the 35 U.S.C. § 103 rejection is Maintained. The Examiner notes that an updated 35 U.S.C. § 103 rejection is below and reflects Applicant’s amendments.
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, 8-12, and 15-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract ideas without significantly more.
Regarding Claims 1, 8, and 15: Claims 1, 8, and 15 recite the following functions: generate a graph data structure based on user relationship data, compute weights as a combined frequency of communications and age of communications, assign weights to edges based on the relationship computations between users, i.e. nodes, who held relationships, generate a ranked list based on relationship data, order list based on weights, determine highest ranking users to select based on rank; which are an abstract idea in the category of “mathematical concepts,” more specifically, “mathematical relationships” and “mathematical calculations” because the claim mathematically/statistically generates a mathematical function that is driven by the assignment of combined computed weights between users based on said relationship data. (MPEP 2106.04(a)(2)(I)).
The following recitations: enroll users, install software, receive communications data, plus the above recitations under the mathematical concepts abstract idea, which are abstract ideas in the categories of: “certain methods of organizing human activity,” more specifically “commercial interactions (business relations between businesses),” and “managing personal behavior or relationships or interactions between people, (including social activities like user communications and relationships). These actions are indicative of profiling enterprise business users according to their communications and behavioral and business decisions to drive decisions of identifying enterprise connections, i.e. identifying the closest commercial interactions and business relationship behaviors of enterprise stakeholders with outside stakeholders (MPEP 2105.04(a)(2)(II)).
The claims recite the following elements, the graph data structure, weighting, nodes, edges, and ranked list. These elements cannot be both additional elements and part of the abstract ideas. Therefore, the graph data structure and ranked list are mathematical models that are abstract ideas, utilizing the same data represented by the nodes and edges.
Further, since these models are abstract ideas, the mathematical models must be implemented in a manner beyond generally being performed on or linked to computing structures. Since the model performs the mathematical manipulations, the model is a specific data processing technique, performed by the management service. The specification discloses that he management service is software implemented on a computer, therefore, the abstract idea of mathematical manipulations performed by the specific data processing technique using a computer
The additional limitations recited in the claim comprise: enrolling client devices, installing management components with granted access based on the elevated privileges of a device administrator, receiving data, reporting data, receiving requests specifying data, generating data, representing data, identifying user nodes, identifying node connections, generating graphs, identifying data, representing and generating ranked lists, where the specification does not reveal that the core of the invention is directed to advances in general graph nor edge-node graph technology, generating graphs, or theoretical and practical frameworks of graph structures, representations of users as nodes, the structure of weighted edge-node graphs; enrolling devices in networks or directories, installing software components on user devices, edge node graphs representing communications between entities; sending, receiving, obtaining, requesting, analyzing, specifying, generating, representing, or identifying data, or related techniques, data structures, or improvements to the graphing of or characterization of data. Additionally, claims 1, 8, and 15 recite a management service, a management component installed on the client device, a network connection, elevated privilege of a device administrator, or granting access to user devices or the data they contain. These are additional elements that are general purpose computing limitations, where the specification does not disclose advances to networking technologies, to management oversight capabilities, or to security protocols for devices in general or for the devices or architecture that access an enterprise network or directory, or general-purpose infrastructure and software systems of an Enterprise business, much less to any network or directory. Lastly, the specification does not make advances in the techniques of graph data structures, algorithms, machine language models, or to statistical or mathematical sciences. In fact, the claims only recite the steps to achieve the outcomes. Instructions to generally link a judicial exception to a particular field of use is not a practical application (MPEP 2106.05(a) and (h)).
The additional elements for Claim 1 are a non-transitory computer-readable medium, processors; claim 8 recites a system, a computing device; for claims 1 and 8 and 15, client devices and a network, where all of these elements are general purpose computing structures. The three claims also recite a management component and management service, which are software, i.e. instructions implemented by the computing structures. The claims also recite nodes and edges, which represent data gathered and/or programmatically computed and assigned, such that the edges and nodes are non-functional descriptive information, i.e. data characterizations. Lastly, the claims recite the enterprise directory, graph data structure, and the ranked list of users, i.e. characterized databases. The graph data structure and ranked list of users are abstract ideas, i.e. dynamic data models that cannot be additional elements. However, at a particular time of an inquiry, the graph and list are queried at a particular moment in time, a graph or list that represent the temporal slices of the data functionally determined by the abstract idea recited as the mathematical model. Characterized databases are general-purpose computing structures like any other characterized database. All of the additional elements are described at a high level of generality in the specification. Instructions (including the management component and management service) to apply abstract ideas for manipulating data, using general-purpose computing structures, are not a practical application of a judicial exception (MPEP 2106.05(f)). Further, these additional elements are generally linked to the use of the abstract ideas, i.e. the technological field is the manipulation of data, utilizing instructions and instruction-based software, implemented on general purpose computing structures, such that the abstract ideas are not improving the generally linked computing structures and are, in fact, nothing more than a drafting effort meant to monopolize the judicial exceptions.
The claims as a whole, while looking at additional elements individually and in combination, do not integrate the judicial exceptions into a practical application (MPEP 2106.04).
Step 2B: The analysis above is commensurate with the analysis for Step 2B, such that the same additional elements taken individually and in combination do not result in the claims, as a whole, amounting to significantly more than the judicial exceptions (MPEP 2106).
Independent Claims
Claims 4-5 11-12, and 18 further define additional data that the communications data may be comprised of. These claims do not perform any steps that recite abstract ideas. The additional elements match those of the independent claims, and additionally for claims 5 and 11, the additional elements are a messaging service and a conferencing service, which are software instructions applied on the general-purpose computing structures recited in the claims and They each recite non-functional descriptive information that cannot be relied on to integrate the claims into a practical application. Since there are no additional abstract ideas, the additional elements, i.e. the general-purpose computing structures, are not indicative of integration of a absent abstract idea into a practical application, nor can they amount to significantly more than the nonexistent abstract ideas.
Regarding Claims 22-24: The claims recite generating a ranked list by selecting only users located in a specified proximity of the client from which the request was made, which is an abstract idea that amends the abstract idea of the independent claims, and falls under the abstract idea categories explained for claims 1, 8, and 15 for the same reasons. These categories include “mathematical concepts,” more specifically, “mathematical relationships” and “mathematical calculations,” incorporating the analysis to generate the weighting based on user relationships (MPEP 2106.04(a)(2)(I)). These categories also include “certain methods of organizing human activity,” more specifically “commercial interactions (business relations),” and “managing personal behavior or relationships or interactions between people, (including social activities), (MPEP 2105.04(a)(2)(II)) for the same reasons disclosed in the independent claims.
The data recited in the claims are data characterizations, thus they are non-functional descriptive information, are not abstract ideas and carry no patentable weight, therefore, they cannot be depended upon to integrate the judicial exceptions into a practical application.
The additional limitations recited in the claim comprise: weighting edges and weighting based on age and frequency of communications between users, and receive location data, where the specification does not reveal that the core of the invention is directed to advances in general graph nor edge-node graph technology, generating graphs, or theoretical and practical frameworks of graph structures; representations of users; the structure of weighted edge-node graphs; edge node graphs representing communications between entities; sentiment analysis theoretical frameworks, algorithms or machine learning techniques; sending, receiving, obtaining, requesting, analyzing, specifying, generating, representing, or identifying data, or related techniques, data structures, or improvements to the graphing of or characterization of data. The specification does not make advances in the techniques of graph data structures, algorithms, machine language models, or statistical or mathematical sciences. In fact, the claims only recite the steps to achieve the outcomes. Instructions to generally link a judicial exception to a particular field of use is not a practical application (MPEP 2106.05(a) and (h)).
The claims recite a partial list of the same additional elements as the independent claims, i.e. general-purpose computer structures disclosed in the specification at a high level of generality. These claims are Instructions to apply abstract ideas on a general-purpose computing structure, which is not a practical application (MPEP 2106.05(f)).
The claims as a whole, while looking at additional elements individually and in combination, do not integrate the judicial exceptions into a practical application (MPEP 2106.04).
Step 2B: The analysis above is commensurate with the analysis for Step 2B, such that the same additional elements taken individually and in combination do not result in the claims, as a whole, amounting to significantly more than the judicial exceptions (MPEP 2106).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4-5, 8, 11-12, 15, 18 and 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Garton, “Studying Online Social Networks,” Journal of Computer-Mediated Communication, vol. 3., Issue 1, 1 June 1997, hereafter “Garton” in view of Olmstead, US20190057310A1, and in further view of Pflughoeft, US20130339400A1.
Regarding claims 1, 8, and 15: Garton discloses:
a plurality of client devices corresponding to a plurality of users in a directory for management by a management service, the directory comprising an enterprise user directory, a management component on the client device, the management component access to contacts data on the client device and communications data associated with the contacts data; [pg 2] (involving the computing devices of user’s for computer mediated communications (CMC) between people on computer supported social networks (CMMS), [pg 5] ““groupware” to describe the software, hardware, and peopleware combination that supports computer-mediated communication,” [pg 28] “Software logging may make it technically feasible for scholars to collect data about all those with whom a person is in contact online. … a whole network study,… a roster of all the people in a specific group … automate the collection of who-to-whom online contact data within a group.” (automated collection of network user’s data from each user’s device corresponding to a network directory of members in the same organization or in similar groups, i.e. internal or internal and external stakeholders), [pg 34] “Electronic monitoring can routinely collect information … All commands entered into a system are available for monitoring, making it possible to gather information on the form of media used, the frequency of use, the timing and direction of messaging, the subject of the message, and even the content of the message itself,” [pg 41] “use within an organizational context” (Enterprise), [pg 32] “Software applications … are useful to organize ethnographic data and to investigate patterns among persons, activities and attitudes towards new media. This process provides a way for integrating the analysis of social networks of persons and offices with cognitive networks of meaning.”
receive, from the plurality of client devices over a network connection, the communications data associated with the contacts data reported by the management component on each of the plurality of client devices; [pg 34] “Electronic monitoring can routinely collect information on whole networks or selected subsamples. … All commands entered into a system are available for monitoring, making it possible to gather information on the form of media used, the frequency of use, the timing and direction of messaging, the subject of the message, and even the content of the message itself,” [pg 28] “Software logging may make it technically feasible for scholars to collect data about all those with whom a person is in contact online. … automate the collection of who-to-whom online contact data within a group.” (automated collection of network user’s data from each user’s device).
Receive a request specifying an external user that is external to the directory; [pg 4]: “Indirect ties link in compound relations (e.g., friend of a friend) that fit network members into larger social systems. The social network approach facilitates the study of how information flows through direct and indirect network ties, how people acquire resources, and how coalitions and cleavages operate,” and [pg 8]: “The content of a relation refers to the resource that is exchanged. In a CMC context, pairs exchange different kinds of information, such as communications,” where [pg 34]: “All commands entered into a system are available for monitoring, making it possible to gather information on … the frequency of use, the timing and direction of messaging,” and [pg 37] “Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments,” (Garton discloses a user outside of the enterprise network)
generate a graph data structure based on the communications data, the graph data structure comprising a plurality of nodes connected by edges, wherein a first node connected of the plurality of nodes represents a first user of the plurality of users in the directory and a second node connected to the first node by and edge represents the user that has communicated with the first user, wherein generating the graph data structure includes programmatically computing and assigning a weight to the edge between the first node and the second node based on both (i) a frequency of communication between the first user and the user and (ii) an average age of the communications between the first user and the external user such that a higher weighting is assigned to the edge for more recent communications while a lower weighting is assigned for less recent communications; [Figure 7] (nodes representing at least a user and other users in an office network and users in another group, external to the first group); [pg 41]: “Analyses of interaction frequency identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or frequency of exchange among specific ties,” [pg 42] “The following sociograms were generated by Krackplot [i.e. programmatically computed] and depict the organizational communication structure …. In these visual representations, people are displayed as points and arranged in relation to the relative frequency of their interaction. People who communicated more with each other are placed closer together. The connecting lines indicate communication direction and frequency level,” and “The Headquarters Office Coordinator remained a central communication star despite changes in staff and job descriptions. Furthermore, the Satellite Office Coordinator remained a relative isolate, connected to the others primarily through a link with the Vice President,” [pg 16]: “Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different groups. These roles and positions emerge through analysis of the network data rather than through prior categorization,” [pg 7]: “Analysts ask about exchanges that create and sustain work and social relationships… such as influence or social support,” [pg 8] “communication may be initiated more frequently by one actor than the other,” and [pg 9]:“Relations also differ in strength…with respect to communication, pairs may communicate throughout the work day, once a day, weekly or yearly,” (i.e. age of communications is calculated and tracked), [pg 37] “Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments,” (Garton discloses a structure of users communication with at least a user outside of the enterprise network), [pg 40] “In these visual representations people are displayed as points and arranged in relation to the relative frequency of their interaction. People who communicated more with each other are placed closer together. The connecting lines indicate communication direction and frequency level;” (depicting lines, aka edges, and points, aka nodes, with weights “assigned” according to direction and frequency), [pg 34]: “All commands entered into a system are available for monitoring, making it possible to gather information on … the frequency of use, the timing and direction of messaging,” (timing of messaging representing the age of communication), [pg 14] “They built a picture of the typical person as having about a dozen active ties outside of their household and workplace, including “at least 4 ties with socially close intimates, enough to fill the dinner table and at least 3 ties with persons routinely contacted three times a week or more,” (the picture existing as a graph dependent on communication frequency and age), [pg 30] “refer to a specific relational content such as “socialize with” or “give advice to” within a given time frame,” [pg 31] “that took place over a broad time frame… If the time frame is too long, or the amount of information too detailed, reliability and accuracy are jeopardized,” (age of communication), [pg 37] “Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments,” (Garton discloses a user outside of the enterprise network and a graph structure of social networking, i.e. determined from metrics like frequency, direction, and age of communication, where the structure of a graph database holding the values is clearly depicted) (Examiner notes the plain meaning of weight vs level in terms of an edge vs a line: Where a line is considered, a line is defined by only 5 parameters, 2 points and the line that connects them, where the last parameters are the distance between the points and the line thickness. Where it could be denoted by number or actual thickness in a visual depiction, (if color is not considered), the line is synonymous with an edge between two points and the level is synonymous with the weight, or thickness of the line. Level does not depict distance, where level in terms of distance here would only be viable if this were a 2-dimensional (x, y) plot graph with x and y coordinates, this is not that kind of graph. Therefore, there is no other educated solution that could become apparent.)
Examiner notes: While the graph data structure in the prior art Garton page 42 and figure 7 discloses a graph specific to multiple users inside of a single business network, since the users are in two separate office spaces, it would be obvious to a person having ordinary skill in the art to substitute one user in the separate office as a user outside of business network, wherein Garton clearly discloses the analysis of communications between users that are covered by at least both ideologies comprising users that can be in the same network or in separate networks where one user is in a specified internal network and the second user is outside of said network.
Generate, based on the graph data structure, wherein the users includes the first user and other users represented by other nodes that are connected to the external user by other edges, each of which is weighted based on both a frequency of communication between the corresponding other user and the external user and an average age of the communications between the corresponding other user and the external user, and wherein the ranked list is ordered based on weights of the edges connecting the nodes of the users in the ranked list and the second node; [[Figure 7] (nodes representing at least a user and other users); [pg 41]: “Analyses of interaction frequency identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or frequency of exchange among specific ties,” [pg 42] “The following sociograms were generated by Krackplot and depict the organizational communication structure …. In these visual representations, people are displayed as points and arranged in relation to the relative frequency of their interaction. People who communicated more with each other are placed closer together. The connecting lines indicate communication direction and frequency level,” and “The Headquarters Office Coordinator remained a central communication star despite changes in staff and job descriptions. Furthermore, the Satellite Office Coordinator remained a relative isolate, connected to the others primarily through a link with the Vice President,” [pg 16]: “Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different groups. These roles and positions emerge through analysis of the network data rather than through prior categorization,” [pg 7]: “Analysts ask about exchanges that create and sustain work and social relationships… such as influence or social support,” (where) [pg 8] “communication may be initiated more frequently by one actor than the other,” and [pg 9]:“Relations also differ in strength…with respect to communication, pairs may communicate throughout the work day, once a day, weekly or yearly, [pg 37] “Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments,” (Garton discloses a user outside of the enterprise network), [pg 40] “In these visual representations people are displayed as points and arranged in relation to the relative frequency of their interaction. People who communicated more with each other are placed closer together. The connecting lines indicate communication direction and frequency level;” [pg 34]: “All commands entered into a system are available for monitoring, making it possible to gather information on … the frequency of use, the timing and direction of messaging.” [pg 14] “They built a picture of the typical person as having about a dozen active ties outside of their household and workplace, including “at least 4 ties with socially close intimates, enough to fill the dinner table and at least 3 ties with persons routinely contacted three times a week or more,” [pg 30] “refer to a specific relational content such as “socialize with” or “give advice to” within a given time frame,” [pg 31] “that took place over a broad time frame… If the time frame is too long, or the amount of information too detailed, reliability and accuracy are jeopardized,” [pg 37] “Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments,” (Garton discloses a user outside of the enterprise network) (Examiner notes the plain meaning of weight vs level in terms of an edge vs a line: Where a line is considered, a line is defined by only 5 parameters, 2 points and the line that connects them, where the last parameters are the distance between the points and the line thickness. Where it could be denoted by number or actual thickness in a visual depiction, (if color is not considered), the line is synonymous with an edge between two points and the level is synonymous with the weight, or thickness of the line. Level does not depict distance, where level in terms of distance here would only be viable if this were a 2-dimensional (x, y) plot graph with x and y coordinates, this is not that kind of graph. Therefore, there is no other educated solution that could become apparent.)
Examiner notes: While the graph data structure in the prior art Garton page 42 and figure 7 discloses a graph specific to multiple users inside of a single business network, since the users are in two separate office spaces, it would be obvious to a person having ordinary skill in the art to substitute other users in one office as other users and one user in the separate office as a user outside of business network, wherein Garton clearly discloses the analysis of communications between users that are covered by at least both ideologies comprising users that can be in the same network or in separate networks where one user is in a specified internal network and the second user is outside of said network.
Identify a closest contact of the external user from the directory by selecting a highest-ranking user in the ranked list of users; and: [pg 8] “Relations (sometimes called strands) are characterized by content, direction and strength,” [pg 9] “Such aspects of relationships measure different types of relational strength,” [pg 10] “A tie connects a pair of actors by one or more relations. Pairs may maintain a tie based on one relation only, e.g., as members of the same organization, or they may maintain a multiplex tie, based on many relations, such as sharing information, giving financial support, and attending conferences together. {i.e., user’s outside of an enterprise directory} Thus ties also vary in content, direction, and strength. Ties are often referred to as weak or strong, although the definition of what is weak or strong may vary in particular contexts [Marsden & Campbell, 1984]. Ties that are weak are generally infrequently maintained, non-intimate connections, for example, between co-workers who share no joint tasks or friendship relations. Strong ties include combinations of intimacy, self-disclosure, provision of reciprocal services, frequent contact, and kinship, as between close friends or colleagues,” where [pg 11] “Thus, an electronic tie combined with an organizational tie is sufficient to allow the flow of information between people …. Connectivity among previously unacquainted people is a well-established finding in the CMC research literature. Examples of this form of connectivity are documented in studies of large international organizations as well as in dispersed occupational communities …,” [pg 16]: “Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different groups. These roles and positions emerge through analysis of the network data rather than through prior categorization,” [pg 41]: “Analyses of interaction frequency identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or frequency of exchange among specific ties. … Communication positions such as “isolate,” “bridge” or “star” emerge from an analysis of matrix data. Visual representations of relational matrices are generated by establishing coordinates through multidimensional scaling and importing these into a drawing program such as Krackplot,” [pg 42] “The Headquarters Office Coordinator remained a central communication star despite changes in staff and job descriptions. Furthermore, the Satellite Office Coordinator remained a relative isolate, connected to the others primarily through a link with the Vice President. People who communicated more with each other are placed closer together,”
Generate a response to the request, wherein the response to the request specifies the closest contact. [pg 16]: “Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different groups. These roles and positions emerge through analysis of the network data rather than through prior categorization,” [pg 41]: “Analyses of interaction frequency identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or frequency of exchange among specific ties.”
While Garton does not disclose: generate, based on a graph data structure, a ranked list of users, wherein the ranked list of users includes the first user and the other users based on a frequency of communications between the corresponding other user and the external user, and ab average age of the communications between the corresponding other user and the external user, and wherein the ranked list of users includes the first user and other users, and wherein the ranked list is ordered based on weights of the edges connecting the nodes of the users in the ranked list and the second node; the edge between the first node and second node is further weighted based upon an age of communications between the first user and the user,
Olmstead teaches: [0002] “Identifying experts in an organization … particularly if the organization includes many experts,” (i.e. experts exhibit the highest ranked relationship with a particular connection, with other expert relationship scores) [0010] “generates a relationship graph using at least some of the named entities and computes the relationship path using the relationship graph, wherein the presentation unit generates a visual element corresponding to the relationship path and at least a portion of the relationship graph,” (relationship path is defined by the score) [0055] “The graph can be referred to as a relationship graph, …. The system 100 can use the relationship graph to generate paths between different entities …. For example, a path can connect an entity to another entity and can be used to suggest different ways for the first entity to connect to the other entity. The relationship graph can include notes that correspond to different named entities … along with edges that correspond to scores between the different nodes. The knowledge engine 108 can be continually updated as the system 100 processes new electronic data …to further update scores computed between entities…. The relationship graph can be used to suggest a path between an entity interested in a topic and an expert entity that is expert in the topic,” (i.e., scores are synonymous with ranking where a higher score is ranked higher than a lower score and the highest ranked entity would be the expert entity), [0091] “determine the time each sender/receiver pair have been in contact,” [0092] “The relationship unit 106 can use a Heuristic Function as part of the relationship score measurement. The heuristic function computes the closeness between sender and receiver of each email or other data communication. As an example, for each unique sender/receiver pair, the heuristic scores of all their emails are averaged to produce one final relationship score,” [0099] “can implement the K-shortest Path Algorithm to determine a path between two entities in the relationship graph. The path can be displayed at an interface, … determines the K— ‘friendliest’ pathways between any two contacts in an organization. This algorithm can be used to provide the most efficient pathways in which people could connect,” (friendliest pathways are the highest relationship scores and the most efficient pathways of connection implicitly disclose a hierarchical list/ranking of the users based on the relationship scores, where the friendliest pathways are synonymous with the highest ranked, i.e. closest user, based on the ranking values determined by the weightings of the lines between nodes) [0064] “A relationship unit 528 generates a relationship graph and relationship scores,” [0103] “An interface can display visual elements regarding the path and relationship scores , along with other visual representations of the knowledge base , entities , and topics,” [0113] “relationship between a first entity and a second entity. [0011] “The system 100 includes a relationship unit 106 to process the input data 102 to generate a relationship score and a relationship graph for the entities and topics in the knowledge engine 108. The relationship unit 106 includes a sentiment classifier 118, a formality classifier 120, and a path unit 122. The path unit 122 can generate a relationship graph with nodes that correspond to different entities and topics and edges that correspond to relationship scores between the entities and topics. The path unit 122 can use the relationship graph to define different relationship paths between the nodes (entities and/or topics) to connect different entities and topics.” [70] “The classification rules can involve rules for time stamp processing and duration calculations. The relationship unit 528 generates a relationship graph and computes one or more paths between the first entity and the second entity. The presentation unit generates a visual element corresponding to the one or more paths and at least a portion of the relationship graph. [47] The resulting formality score makes up another variable that influences the heuristic relationship score. The heuristic score can be used to define and weight edges in the relationship graph,” and [54] “The relationship model 106 can choose the coefficients to weigh in the factors such as sentiment, formality and durations based on field studies. As an example, sentiment scores can be given more weight than the formality score of the communication.” (Examiner notes that this patent prior art does not explicitly state an internal user connected to an external user, however, the prior art of Garton explicitly and implicitly discloses users in a similar thought/social network from different business entities and as such, the reason to combine below supports the effective combination of prior art.)
One of ordinary skill in the art would find it obvious to combine the prior art documents before the effective filing date because they share the same field of computer science, sentiment analysis, graphs from sentiment analysis, nodes and lines that are weighted based upon analysis of connectivity over a plurality of communications to yield the predictable results of the combined disclosure and patent claims. The combination of these prior art documents leads to a markedly advantageous system of social media and social media graphs analysis and data generation showing continuity in obviousness.
While Garton does not disclose and Olmstead does not teach: enroll a plurality of client devices corresponding to a plurality of users in a directory for management by a management service, the directory comprising an enterprise user directory, wherein enrolling a client device includes installing a management component on the client device, wherein the management component is installed with an elevated privilege of a device administrator that grants the management component access to contacts data on the client device and communications data associated with the contacts data;
Pflughoeft teaches: [0076] “The administrator may use the user management interface 514 to manage and configure users, “ (configuring users is done with user enrollment), [0067] “The administrator can use the user management system 300 to view or edit user information, and control access and permissions of particular users. User directory 302 displays a list page of all users that have been assigned to the administrator to manage … Through this list page the administrator may access a new user addition 314 program to create a user profile for a new user and input information including name, profile type, role, manager, title, contact information, and other permissions. The administrator may also access existing user information by selecting a particular user's user information page 304 … The user information page 304 also displays the particular users activity log 308…such as … activity history … administrator with privileges,” [0069] “administrator may check statuses such as: login, search, mobile, API, … Reporting mechanisms provided by reporting option 412 include email, chatter, text, or tweet,” [0073] “tracking a particular user,” [0075] “User management interface 514 includes user directory 702, user search field 704, add user module 706, user information fields 708, edit user 710, user information page 712, administrative actions 714, back button 716, user status 718, activity log 720, reset 722, deactivate 724, user access control 726, migrate access 728, increase access 730, granular level access 732, “ [0060] “informs the administrator of any notifications or alerts occurring in the applications installed on the device,” [0062] “App request 210 alerts the administrator upon a request by an organization to grant access to a user to the database or to download an application. Requests can be made by a user, a manager, an organization, or another administrator of the system,” [0006] “Each organization may have one or more administrators with sufficient privileges to manage one or more users”
One of ordinary skill in the art would find it obvious to combine the prior art documents before the effective filing date because they share the same field of computer science, network management, and collection of user data for plurality of communications to yield the predictable results of the combined disclosure and patent claims. The combination of these prior art documents leads to a markedly advantageous system of social media and social media graphs analysis with management oversight, and data generation showing continuity in obviousness.
Regarding Dependent Claims 4, 10, and 18: Garton discloses, and Olmstead and Pflughoeft teach: Garton discloses: wherein, communication data comprises emails exchanged between a respective user and the external user, [pg. 8] “Relations (sometimes called strands) are characterized by content, direction, and strength. The content of a relation refers to the resource that is exchanged. In a CMC context, pairs exchange different kinds of information, such as communication,” [pg 30] “Information about social networks is gathered … through computer monitoring. …an account of their work communication with each person in unscheduled face-to-face meetings, scheduled face-to-face meetings, by telephone, fax, email, paper letters or memos, audioconferencing, and videoconferencing,” [pg 34] “Gathering data electronically replaces issues of accuracy and reliability with issues of data management, interpretation, and privacy. Electronic monitoring can routinely collect information on whole networks or selected subsamples. … All commands entered into a system are available for monitoring, making it possible to gather information on the form of media used, the frequency of use, the timing and direction of messaging, the subject of the message, and even the content of the message itself.”
Regarding Dependent Claims 5 and 12: Garton discloses, and Olmstead and Pflughoeft teach: Garton discloses: wherein, communication data sources comprise previous interaction between a respective user and the external user via a messaging service or conferencing service, [pg 30] “Information about social networks is gathered … through computer monitoring. …an account of their work communication with each person in unscheduled face-to-face meetings, scheduled face-to-face meetings, by telephone, fax, email, paper letters or memos, audioconferencing, and videoconferencing. … Respondents are often asked to recall behavior that took place over a broad time frame in order to capture as much information as possible,” [pg 30] “Electronic text, including CMC, can be analyzed for patterns of relations between words or phrases,” [pg 34] “All commands entered into a system are available for monitoring, making it possible to gather information on the form of media used, the frequency of use, the timing and direction of messaging, the subject of the message, and even the content of the message itself.”
Regarding claims 22-24: Garton discloses: receive location data from the management component on each of the plurality of client devices; [pg 29] “Since indirect as well as direct relations can become data, the boundary expands exponentially…can provide information about the interconnectivity of the network…how well the network might coordinate its activity, and how much social control it might exert…investigated the number of steps or ties it took for a person sending a note to an unknown person geographic and social location” (implicitly disclosing location data is received by the system to gauge within or without of the same geographic and social location, such that the location data is received), [pg 42-43] “others who were physically proximate,”
wherein generating the ranked list of users in the directory further includes selecting only users in the directory of the client device from which the request specifying the external user was received as determined based on the location data received from each of the plurality of client devices; [pg 17] "explore how a sense of community is maintained through ties, rather than through geographical proximity among Toronto residents. They built a picture of the typical person as having about a dozen active ties outside of their household and workplace, including “at least 4 ties with socially close intimates, enough to fill the dinner table and at least 3 ties with persons routinely contacted three times a week or more,” (such that the scoring uses the proximity as a filter after the score is determined), [pg 29] “Since indirect as well as direct relations can become data, the boundary expands exponentially…can provide information about the interconnectivity of the network…how well the network might coordinate its activity, and how much social control it might exert…investigated the number of steps or ties it took for a person sending a note to an unknown person in… [a] geographic and social location” (implicitly disclosing location data is received by the system to gauge connections within or without of the same geographic and social location, such that the location data is received and used as a filter to eliminate those not in the same location, i.e. not proximate, and show those who are proximate), [pg 42-43] “others who were physically proximate,” [pg 16]: “Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different group. These roles and positions emerge through analysis of the network data” [pg 41] “Analyses of interaction … identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or…of exchange among specific ties.” [pg 8] “Relations (sometimes called strands) are characterized,” [pg 10] “A tie connects a pair of actors by one or more relations. Pairs may maintain a tie based on one relation only, e.g., as members of the same organization, or they may maintain a multiplex tie, based on many relations, such as sharing information, giving financial support, and attending conferences together. {i.e., user’s outside of an enterprise directory that is in the same location or within a predetermined location of the inside user} Thus ties also vary ... Ties are often referred to as weak or strong, although the definition of what is weak or strong may vary in particular contexts [Marsden & Campbell, 1984]. Ties that are weak are generally infrequently maintained, non-intimate connections (not in the same location), for example, between co-workers who share no joint tasks or friendship relations. Strong ties include combinations of intimacy (close proximity including locations in the same predetermined location), self-disclosure, provision of reciprocal services, frequent contact, and kinship, as between close friends or colleagues {where closeness may represent collocation of users using devices},” where [pg 11] “Thus, an electronic tie combined with an organizational tie … Examples of this form of connectivity are documented in studies of large international organizations as well as in dispersed occupational communities,”[pg 34]: “All commands entered into a system are available for monitoring, making it possible to gather information;” (where location data receipt is a reasonable command entered into the system for monitoring);
Where Garton does not disclose, Olmstead teaches: receive location data; generating the ranked list of users in the directory determined based on the location data received: [0078] “determine and measure relationship scores between entities,” [0099] “can implement the K-shortest Path Algorithm to determine a path between two entities in the relationship graph. The path can be displayed at an interface, … determines the K—‘friendliest’ pathways between any two contacts in an organization. This algorithm can be used to provide the most efficient pathways in which people could connect,” (friendliest pathways are the highest relationship scores, where the most efficient pathways of connection implicitly disclose a hierarchical list/ranking of the users based on the relationship scores, where the friendliest pathways are synonymous with the highest ranked, i.e. closest user, based on the ranking values determined by the weightings of the lines between nodes which may further be filtered by location) [0064] “A relationship unit 528 generates a relationship graph and relationship scores,” [0103] “An interface can display visual elements regarding the path and relationship scores , along with other visual representations of the knowledge base , entities , and topics,” (where a ranked list is a visual element that may be displayed to show the closest path based on scores between users), [0113] “relationship between a first entity and a second entity. (Examiner notes that this patent prior art does not explicitly state an internal user connected to an external user, however, the prior art of Garton explicitly and implicitly discloses users in a similar thought/social network from different business entities and as such, the reason to combine below supports the effective combination of prior art.)
One of ordinary skill in the art would find it obvious to combine the prior art documents before the effective filing date because they share the same field of computer science, sentiment analysis, graphs from sentiment analysis, nodes and lines that are weighted based upon analysis of connectivity over a plurality of communications to yield the predictable results of the combined disclosure and patent claims. The combination of these prior art documents leads to a markedly advantageous system of social media and social media graphs analysis and data generation showing continuity in obviousness.
Where Garton does not disclose, and Olmstead does not teach, Pflughoeft teaches: receive location data from the management component on each of the plurality of client devices; [0067] “The administrator may configure the user's access to certain data depending on the user's location as indicated by the user's mobile device or computer by using the granular level access 330 program. Because an action taken can affect user access.”
Users that are located within a specified physical proximity as determined based on the location data received from each of the plurality of client devices. [0067] “The administrator may configure the user's access to certain data depending on the user's location as indicated by the user's mobile device or computer by using the granular level access 330 program. Because an action taken can affect user access,” [0079] “able to configure user access to … certain data depending upon the user's location as indicated by the user's mobile device or computer. If the user is at a work office, he may access more data than if the user is at a customer site. Other activities may also be made available.” (Discloses that proximity to particular locations, which could be reasonably substituted to be locations of other users versus particular sites, allows a user to receive particular information, like a list of users in a particular proximity.)
One of ordinary skill in the art would find it obvious to combine the prior art documents before the effective filing date because they share the same field of computer science, network management, and collection of user data for plurality of communications to yield the predictable results of the combined disclosure and patent claims. The combination of these prior art documents leads to a markedly advantageous system of social media and social media graphs analysis with management oversight, and data generation showing continuity in obviousness.
Conclusion
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ANGELA HATCH
Examiner
Art Unit 3626
/ANGELA HATCH/Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626