Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of Claims
This communication is a First Office Action on the merits in reply to application number 18/736,013 filed on 06/06/2024.
Claims 1-15 are currently pending and have been examined.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119 and/or 35 U.S.C. 120 is acknowledged.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5, 10, and 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claims 5, 10, and 15 each recite the limitation of “various types of computing device,” which renders the claim indefinite because the claim includes elements not actually disclosed (those encompassed by "various types"), thereby rendering the scope of the claim unascertainable. See MPEP § 2173.05(d). Appropriate correction is required.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the subject matter eligibility guidance set forth in MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106.03), it is first noted that the claimed method (claims 1-5) and is therefore directed to a potentially eligible category of subject matter (i.e., a process). Accordingly, claims 1-5 satisfy Step 1 of the eligibility inquiry.
However, the computer program product (claims 6-10) and system (claims 11-15) encompass non-statutory embodiments and therefore fail to meet Step 1 of the eligibility inquiry.
With respect to claim 6-10, the computer program product comprises a tangible computer-readable medium, which under a broadest reasonable interpretation may be understood as encompassing a transitory signal. There is an absence from the Specification of any description of the computer program product or tangible computer-readable medium disavowing from their scope transitory embodiments such as carrier waves/signals such that, in the absence of a clear, deliberate, and precise “special definition” that limits the tangible computer-readable medium to non-transitory embodiments, and therefore the computer program product (and the tangible computer-readable medium) may be reasonably interpreted as encompassing non-statutory (transitory) embodiments merely having tangible causes and/or effects, such as electromagnetic, infrared, or propagating signals (each of which is transitory, though being "tangible” via its association with "tangible causes and effects"). Thus, while it is acknowledged that claim 6 describes the medium as being "tangible," it is noted that transitory signals are within the scope of “tangible,” as per the analysis in Nuijten:
"While such a transmission is man-made and physical - it exists in the real world and has tangible causes and effects - it is a change in electric potential that, to be perceived, must be measured at a certain point in space and time by equipment capable of detecting and interpreting the signal. In essence, energy embodying the claimed signal is fleeting and is devoid of any semblance of permanence during transmission. (Emphasis added). Moreover, any tangibility arguably attributed to a signal is embodied in the principle that it is perceptible - e.g., changes in electrical potential can be measured. All signals within the scope of the claim do not themselves comprise some tangible article or commodity. This is particularly true when the signal is encoded on an electromagnetic carrier and transmitted through a vacuum-a medium that, by definition, is devoid of matter."
In re Nuijten at 1356-57.
Accordingly, the claimed computer program product comprises a tangible computer-readable medium may be construed as encompassing transitory signals and therefore claims 6-11 fail to satisfy Step 1 of the eligibility inquiry because the claims encompass embodiments outside the scope of §101.
With respect to claim 11-15, when evaluated under Step 1 of the subject matter eligibility inquiry (as set forth in MPEP 2106.03), the system, which comprises a server hosing a web application (comprising software modules) and two or more storage devices, does not fall within at least one of the four categories of patent eligible subject matter. The server and its application and software modules lack any physical elements (e.g., hardware) but instead may be embodied entirely as software. Similarly, the two or more data storage devices lack any physical elements (e.g., hardware) and encompass software per se embodiments (e.g., database, virtualized server, virtual memory. The Specification is open-ended and does not provide a special definition for the system or its elements to disavow software embodiments of the system of its claim elements. Accordingly, when given a broadest reasonable interpretation, the system of claims 11-15 may take the form of a software-per-se embodiment, which is not a machine or article of manufacture. Dependent claims 12-15 fail to add any physical elements (hardware) that would render these claims as a machine or article of manufacture, but instead these claims similarly encompass software-per-se embodiments. Therefore, claims 11-16 fail to satisfy Step 1 of the subject matter eligibility inquiry.
However, because claims 6-15 could be amended to include physical/hardware elements to satisfy Step 1, these claims are further evaluated under Step 2 of the eligibility inquiry along with claims 1-5.
With respect to Step 2A Prong One of the eligibility inquiry (as explained in MPEP 2106.04), it is next noted that the claims recite an abstract idea that falls under the “Certain methods of organizing human activity” abstract idea grouping by reciting limitations for managing personal behavior or relationships (community engagement) and steps that, but for the generic computer/software implementation, could be implemented as “Mental Processes” (e.g., observation, evaluation, judgment, or opinion). The limitations reciting the abstract idea, as set forth in independent claim 1 are identified in bold text below, whereas the additional elements are presented in plain text and are separately evaluated under Step 2A Prong Two and Step 2B:
a. hosting a web application comprising one or more software modules operating within a network, wherein the one or more software modules comprise at least an input module, an analysis module, an optimization module, and a feedback module; b. controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network (These are additional elements to be evaluated under Step 2A Prong Two and Step 2B below);
c. collecting personal information of community members through the input module, wherein the personal information includes income, employment status, social activity, and civic engagement and comprises collected data (The “collecting” step describes activity for managing personal behavior or relationships because the collected data describe personal behavior or interactions and may be directly tied to analysis, recommendations, or optimization strategies for community members, and but for the generic computer implementation by the input module, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion. In addition, the “collecting” step may be considered insignificant extra-solution data gathering activity, which is not enough to amount to a practical application (MPEP 2106.05(g)), and such extra-solution data gathering activity has also been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network));
d. processing the collected data using the analysis module to identify trends, patterns, and opportunities for optimizing personal attributes and community interactions to produce analyzed data (The “processing…to identify” step describes activity for managing personal behavior or relationships because the processing and identification of trends/patterns/opportunities is directly tied to personal behavior or interactions and may be employed for analysis, recommendations, or optimization strategies for community members, and but for the generic computer implementation by the analysis module, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion);
e. generating optimization strategies based on the analyzed data using the optimization module, wherein the optimization strategies include job recommendations, social activity suggestions, and initiatives to boost civic participation (The “generating optimization strategies” step describes activity for managing personal behavior or relationships because the generating of strategies is directly tied to personal behavior or interactions and may be employed for optimizing activities of community members, and but for the generic computer implementation by the optimization module, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion);
f. receiving user feedback on the optimization strategies via the feedback module to produce received feedback (The “receiving user feedback” step describes activity for managing personal behavior or relationships because the received feedback is directly tied to personal behavior or interactions and may be employed for evaluating or optimizing personal behavior or interactions of community members, and but for the generic computer implementation by the feedback module, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion. In addition, the “receiving” step may be considered insignificant extra-solution data gathering activity, which is not enough to amount to a practical application (MPEP 2106.05(g)), and such extra-solution data gathering activity has also been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)); and
g. refining the optimization strategies based on the received feedback to continuously improve (The “refining the optimization strategies” step describes activity for managing personal behavior or relationships because the strategy optimization is directly tied to personal behavior or interactions or their refinement based on feedback of community members, and but for the generic computer implementation, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion).
Independent claims 6 and 11 recite limitations similar to the limitations discussed above and have been determined to recite the same abstract idea(s) as claim 1.
With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP 2106.04(d)), the judicial exception is not integrated into a practical application. Independent claims 1/6/11 include additional elements directed to hosting a web application comprising one or more software modules operating within a network, wherein the one or more software modules comprise at least an input module, an analysis module, an optimization module, and a feedback module; controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network; computer program product comprising a tangible computer-readable medium comprising executable instructions; a server hosting a web application. The additional computer based elements (web application, software modules, computer program product, data storage devices) have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (network computing environment, e.g., the Internet). The step for controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network describes, at a high level of generality, activity tying the invention to a particular operating environment, e.g., network or cloud based storage/retrieval using access control features (e.g., authentication, login, passwords). See MPEP 2106.05(f) and 2106.05(h). Furthermore, even if the collecting and receiving steps are evaluated as additional elements, this activity at most amounts to insignificant extra-solution activity, which is not enough to amount to a practical application. See MPEP 2106.05(g). In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry (as explained in MPEP 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent claims 1/6/11 include additional elements directed to hosting a web application comprising one or more software modules operating within a network, wherein the one or more software modules comprise at least an input module, an analysis module, an optimization module, and a feedback module; controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network; computer program product comprising a tangible computer-readable medium comprising executable instructions; a server hosting a web application. The additional elements have been evaluated, but fail to add significantly more to the claims because they amount to using generic computing elements or instructions/software (web application, software modules, computer program product, data storage devices) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (network computing environment, e.g., the Internet) and does not amount to significantly more than the abstract idea itself. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
With respect to controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network, Official Notice is taken that controlling access of software to computer resources (e.g., hard drive, network/cloud storage) is well-understood, routine, and conventional in the art, which does not add significantly more to the claims.
Furthermore, even if the collecting and receiving steps are evaluated as an additional element, this activity at most amounts to insignificant extra-solution activity, and such extra-solution activities have been recognized as well-understood, routine, and conventional and thus insufficient to add significantly more to the abstract idea, as noted by the CAFC with respect to storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. See also, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent claims 2-5, 7-10, and 12-15 recite the same abstract idea as recited in the independent claims, and have been determined to recite further steps/details that, with the exception of the additional elements in claims 2-3, 5, 7-8, 10, 12-13, and 15 addressed below, fall under the “Certain methods of organizing human activity” abstract idea grouping by reciting limitations that describe managing personal behavior or relationships, and which recite activities falling under the “Mental Processes” abstract idea grouping by reciting limitations that, but for the generic computer implementation, could be implemented as mental activity such as by human observation, evaluation, judgment, or opinion.
With respect to the collection of the data through a smartphone interface as recited by dependent claims 2/7/12, when evaluated under Step 2A Prong Two, the smartphone interface is recited at a high level of generality and is recited for insignificant extra-solution data gathering activity, and fails to improve upon the computer, the input module, the smartphone or any technology or otherwise add anything that amounts to a practical application. Under Step 2B, Official Notice is taken that smartphones and their interfaces are well-understood, routine, and conventional in the art, which is insufficient to add significantly more to the claims.
With respect to the machine learning algorithms recited in dependent claims 3/8/13, it is first noted that the machine learning algorithms are recited at a high level of generality and could be implemented with mathematical algorithms as noted in par. [0033] of the Specification, and thus fall under the “Mathematical Concepts” abstract idea grouping. “Adding one abstract idea (math) to another abstract idea” (fundamental economic practice) “does not render the claim non-abstract.” See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1326-27, 122 USPQ2d 1377, 1379-80 (Fed. Cir. 2017) (claim reciting multiple abstract ideas, i.e., the manipulation of information through a series of mental steps and a mathematical calculation, was held directed to an abstract idea and thus subjected to further analysis in part two of the Alice/Mayo test)). Nevertheless, even if evaluated as an additional element, the machine learning algorithms fail to provide an improvement to the functioning of a computer or to any other technology or technical field or otherwise integrate the abstract idea into a practical application when evaluated under Step 2A Prong Two, whereas under Step 2B, the machine learning algorithms are noted as well-understood, routine and conventional in the art. See, e.g., Sun et al., US 2014/0372351, noting in par. [0038] that “machine learning algorithm used to implement the classifier 304 may include any machine learning algorithm known in the art, including, for example, a supervised or unsupervised learning algorithm, active learning algorithm, or the like.” Tomkins et al., US 2007/0112704, noting in par. [0013] that “…well known in the art that a neural network employing supervised learning algorithm.” See also, Smallwood et al., US 2013/0151311, noting in par. [0031] that “ For example, possible techniques include supervised machine learning, Bayesian techniques, or weighting segments, each of which is known to one of skill in the art.”
Lastly, with respect to dependent claims 5/10/15, deploying one or more software modules on various types of computing devices has been evaluated under Step 2A Prong Two, but is recited at a high level of generality and merely serves to link the use of the judicial exception to a particular technological environment (network computing environment), and thus fails to integrate the abstract idea into a practical application. See MPEP 2106.05(f) and 2106.05(h). Under Step 2B, such activity that operates to link the use of the judicial exception to a particular technological environment (network computing environment) does not amount to significantly more than the abstract idea itself. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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 1-15 are rejected under 35 U.S.C. §103 as unpatentable over Thomas (US 2010/0198724) in view of Veeneman et al. (US 2012/0101896, hereinafter “Veeneman”).
Claims 1/6/11: Thomas teaches a computer-implemented method for community engagement and optimization (pars. 139 and 220: invention also includes a system and method; Although the invention has been described as a method, it is contemplated that it may be embodied as computer program instructions on a tangible computer-readable medium), comprising
a. hosting a web application comprising one or more software modules operating within a network, wherein the one or more software modules comprise at least an input module, an analysis module, an optimization module, and a feedback module (pars. 81, 84, 126, 161, 171, 204, and 208: provide a suitable website or other Internet-based graphical user interface which is accessible by users, hosts or operators of the system; host 5 provides a web page within a website which is hosted at a server, wherein the webpage facilitates obtaining personal financial information from the user by, for example, menu driven interactive procedures; includes various software modules, … enrollment module 412 and an authentication module 414 for example; data analysis module 516; Data analysis application 1214 may be any suitable application for analyzing data; empowerment engine that captures, compiles, arranges, organizes, learns from, uses and/or analyzes community knowledge. Community knowledge includes information (e.g., stored in a database) such as historical facts, experiences, user feedback, successful strategies, best practices, investment and savings rules, etc.; empowerment engine aggregates a plurality of users' data (e.g., demographics, profile information, preferences, savings data, debt data, etc.), feedback, recommendations and/or results into community knowledge);
b. controlling access of the one or more software modules to two or more data storage devices via independent data access layers of the network (pars. 83, 108, 143, and 159: e.g., Enrollment module 412 accesses and stores information in storage device 420. Authentication and/or validation of the identity and status of participants, including any of the other system components, may be performed by the authentication module 414, which preferably has access to the records residing in storage device 420; authentication module 821 may have access to a suitable storage device, such as database 822 for example, which maintains records identifying authorized consumers; restrict/permit only certain actions such as accessing, modifying, and/or deleting data sets. In one example, the data set annotation indicates that only the data set owner or the user are permitted to delete a data set, various identified merchants are permitted to access the data set for reading, and others are altogether excluded from accessing the data set; may consist of any combination thereof at a single location or at multiple locations, wherein each database or system includes any of various suitable security features, such as, for example, firewalls, access codes, encryption, decryption, compression, decompression, and/or the like; access restriction parameters may also be used allowing various entities to access a data set with various permission levels as appropriate);
c. collecting personal information of community members through the input module, wherein the personal information includes income, employment status, social activity, and civic engagement and comprises collected data (pars. 44, 171-172, 184, and 215: user may use user interface 25 to enter into a web page the requested financial information, wherein the financial information may include, for example, user income information; user pledges a series of contributions (e.g., monthly contribution for a year) to a charity on Facebook and system 1 obtains the pledge information and stores it as a debt obligation [social activity, civic engagement]; user income may include any monetary or non-monetary income, asset or benefit related to the user, wherein the income may be obtained from an income source of the user (e.g., employer); the user is paid (after deductions) $500.00 a week from an employer [which is indicative or employment status], then the system 1 may prompt the user to pay himself some portion of that $500.00 (e.g., $100.00) before the analysis of the recommendation phase commences; "consumer profile" shall also be understood to include non-purchase behaviors of a consumer, such as consumer enrollment data, visiting a Web site, referrals of prospective participants in the system, completion of a survey or other information gathering instrument);
d. processing the collected data using the analysis module to identify trends, patterns, and opportunities for optimizing personal attributes and community interactions to produce analyzed data (pars. 52-53, 122, 206, 208, and 213-218: e.g., Data analysis…to comprise quantitative and qualitative research, statistical modeling, regression analyses, market segmentation analyses, econometrics, financial analyses, budgeting analyses, and/or the like. Such analyses may be used to predict consumer behaviors and/or correlate consumer profiles, retailer data, manufacturer data, and/or product or service data. Such analyses may also be used to … track their spending behaviors and patterns; consumer's specific purchasing patterns across retailers; may include community recommendation trends, changes, historical information and/or the like; user may be presented with a community recommendation regarding a refinancing opportunity based upon an analysis of users; rich opportunities to take advantage of community knowledge and to benefit individual users; analyze the results and update community knowledge with rules and/or recommendations; system 1 may use the data to enhance the community knowledge and provide relevant and insightful recommendations to the user);
e. generating optimization strategies based on the analyzed data using the optimization module, wherein the optimization strategies include job recommendations, social activity suggestions, and initiatives … (pars. 187, 190, and 193: system may recommend prioritizing bills to be paid in the following order from highest priority to lowest priority: (i) Bills that are for essentials…e.g.,…job-related expenditures [i.e., job recommendation]; recommendation that the user should change the goal completion date to two years or the user should obtain additional income sources [i.e., job recommendation]; recommends that the user pay himself first…can also budget discretionary money for entertainment purposes, dining out, etc. [i.e., social activity suggestions]);
f. receiving user feedback on the optimization strategies via the feedback module to produce received feedback (pars. 57 and 204: e.g., system may compile any of the above data across multiple participants for the purpose of data analysis, such as analyses which may be employed in strategic planning; empowerment engine that captures, compiles, arranges, organizes, learns from, uses and/or analyzes community knowledge. Community knowledge includes information (e.g., stored in a database) such as historical facts, experiences, user feedback, successful strategies); and
g. refining the optimization strategies based on the received feedback to continuously improve and adapt the computer-implemented method to evolving community dynamics (pars. 189, 204, 208, and 211: e.g., system may also "learn" the user's preferences over time by analyzing the user's inputs and override suggestions such that debt analyzer 15 may provide recommendations that more appropriately conform to more common user inputs and override requests; system 1 includes an empowerment engine that captures, compiles, arranges, organizes, learns from, uses and/or analyzes community knowledge).
Thomas does not explicitly teach optimization strategies include…initiatives to boost civic participation.
Veeneman teaches optimization strategies include…initiatives to boost civic participation (pars. 15-17: e.g., sponsoring civic institutions communicating to their membership to shop participating businesses, ongoing search engine optimization, enabling cause fundraising by selling marketing artifact that allows purchasers to download special coupons from local businesses, emailing offers from participating businesses to all community residents who sign up with an email address, providing a membership badge to display in the store and on the website of each participating store, thus subsequently strengthening the community connection, donating funds to local civic and educational programs in exchange for promoting the participating businesses).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Thomas with Veeneman because the references are analogous since they are each directed to computer implemented features for managing and engaging with a community of users, which is within Applicant’s field of endeavor of utilizing personal information for community enhancement, and because modifying the optimization strategies of Thomas to incorporate initiatives to boos civic participation, as taught by Veeneman, would provide the benefit of strengthening community connection through localized engagement (Veeneman at par. 17) and which already suggested by Thomas’s social network based charitable contribution capability (Thomas at par. 215), which is a slightly more generalized form of civic participation; and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 6 and 11 are directed to a computer program product and system for performing substantially similar limitations as those recited in claim 1 and discussed above. Thomas, in view of Veeneman, teaches a computer program product and system for performing the limitations discussed above (Thomas at pars. 139, 148, and 220: e.g., system and method; may be embodied as computer program instructions on a tangible computer-readable medium; See also, Veeneman at pars. 43-45 and 47), and claims 6 and 11 are therefore rejected using the same references and for substantially the same reasons as set forth above.
Claims 2/7/12: Thomas further teaches wherein the input module collects data through a smartphone interface (Thomas at pars. 149 and 216: web client may include any suitable personal computer, network computer, workstation, personal digital assistant, cellular phone, smart phone; user may interact with system 1 via various interfaces and devices. In one embodiment, user accesses the functionality of system 1 via a mobile device (e.g., a mobile phone)).
Claims 3/8/13: Thomas further teaches wherein the analysis module employs machine learning algorithms to process the collected data (pars. 189, 204, 208-209: e.g., system may also "learn" the user's preferences over time by analyzing the user's inputs; generate new data, based upon predetermined rules and/or algorithms; empowerment engine that captures, compiles, arranges, organizes, learns from, uses and/or analyzes community knowledge; empowerment engine develops and evolves community knowledge through automated learning; Empowerment engine may be configured to execute deductive logic, inferential analysis, forecasting, statistical analysis and/or artificial intelligence in order to continually develop the effectiveness and relevance of community knowledge; knowledge based system may comprise an artificial intelligence tool working to provide intelligent decisions with justification. Knowledge is acquired and represented using various knowledge representation techniques rules, frames and scripts; community knowledge is a machine-readable knowledge base used with an artificial intelligence function of system 1, for example, as part of an expert system that focuses on a domain).
Claims 4/9/14: Thomas further teaches wherein the optimization module generates customized solutions tailored to individual attributes and community needs (pars. 191, 204, and 212: e.g., module may communicate with the portfolio integration module to facilitate comparison of the customized strategy to other strategies and projected financial decisions in order to further facilitate the user meeting the user goals; In various embodiments, community recommendations include recommendations based upon a savings strategy, a debtor, a type of debt, a type of user, a type of penalty and/or a plurality of penalty types; empowerment engine that captures, compiles, arranges, organizes, learns from, uses and/or analyzes community knowledge. Community knowledge includes information (e.g., stored in a database) such as historical facts, experiences, user feedback, successful strategies, best practices, investment and savings rules, etc. For instance, in an embodiment, the empowerment engine aggregates a plurality of users' data (e.g., demographics, profile information, preferences, savings data, debt data, etc.), feedback, recommendations and/or results into community knowledge; user may be presented with side-bar information (e.g., separate from but seamlessly integrated with the main data input interface) that presents a plurality of community recommendations to the user. The user may select a community recommendation and be presented with forecasts or models that predict how the recommendation may influence the user's savings, payments, debts, etc.).
Claims 5/10/15: Thomas further teaches deploying the one or more software modules on various types of computing devices to ensure accessibility for all community members (Thomas at pars. 149 and 161: web client may include any suitable personal computer, network computer, workstation, personal digital assistant, cellular phone, smart phone, minicomputer, mainframe or the like. A web client can be in a home or business environment with access to a network; computers discussed herein may provide a suitable website or other Internet-based graphical user interface which is accessible by users, hosts or operators of the system).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
F. Xia, N. Y. Asabere, A. M. Ahmed, J. Li and X. Kong, "Mobile Multimedia Recommendation in Smart Communities: A Survey," in IEEE Access, vol. 1, pp. 606-624, 2013: discloses smart community development and applications, such as mobile social learning, context aware services, and recommender systems.
S. Riaz, M. Khalil and S. F. Hassan, "The Use of Networking for Community Development: A Survey," 2022 IEEE Technology and Engineering Management Conference (TEMSCON EUROPE), Izmir, Turkey, 2022, pp. 267-274: discloses community networking and evolution of technology and applications related thereto, including for social and economic development, sharing information such as recreation and fundraising events, and for job opportunities.
Wang et al. (US 2018/0032615): discloses features for managing attributes of a community of online social network users, including generating optimization strategies/recommendations such as for job postings (pars. 6 and 26).
Abhyanker (US 2014/0123246): discloses features for managing an online community in a geo-spatial environment, including features for providing advice/recommendations among a restricted group of users in a particular neighborhood (at least par. 12).
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Timothy A. Padot whose telephone number is 571.270.1252. The Examiner can normally be reached on Monday-Friday, 8:30 - 5:30. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Brian Epstein can be reached at 571.270.5389. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300.
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/TIMOTHY PADOT/
Primary Examiner, Art Unit 3625
09/15/2025