Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This communication is a Non-Final Office Action in response to communications received on 3/2/26.
Claims 1, 8, 15 have been amended.
Claims 7, 14, 21 have been previously cancelled
Therefore, Claims 1-6, 8-13, 15-20 are now pending and have been addressed below.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/2/26 has been entered.
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 1-6, 8-13, 15-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1: Identifying Statutory Categories
In the instant case, claims 1-6 are directed to a method, Claims 15-20 are directed to a non-transitory medium and Claims 8-13 are directed to a system. Thus, this claim falls within one of the four statutory categories. Nevertheless, the claim falls within the judicial exception of an abstract idea.
Step 2A: Prong 1 Identifying a Judicial Exception
Under Step 2A, prong 1, Claims 1-6, 8-13, 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1, 8 and 15 recite methods that retrieving at least first data and second data that comprises different type of data, wherein the first data comprises datasets of case records and the second data comprises in-process sales order data, in-preparation sales order data, open sales order data, and pre-sales opportunity data and are each associated with one of a plurality of identifiers; enable identification and association of the first data and the second data with the identifier; based on the different type of the first data and the second data associated with the identifiers to generate one of a plurality of rankings on a predicted likelihood of encountering an issue for each of the identifiers; function that evaluates an established case rate from the first data against planned shipments from the second data to determine a probability that up to a number of cases will be created after receipt of planned orders; applying a filter that determines a percentage of the first data and the second data to use and applies one of a plurality of severity levels with respect to the issue; generation of one of the plurality of rankings;; optimize the generation of one of the plurality of rankings for each of the identifiers based on control parameters; assessment of textual input in one of a plurality of assessment categories; one or more of: a confidence interval time period over which an evaluation is executed: a warranty return rate for each of the customer identifiers; a win probability to classify a pre-sales opportunity as part of n orders in process; one or more adjustments to what is summed into the n orders in process, in-preparation sales order data, open sales order data, or pre-sales opportunity data for the customer identifiers: warranty data on a number of warranty returns; or prior issue data on any repeated issue previously documented as known by any of the customer identifiers; and initiating, at least one automated action based on the rankings for the one or more identifiers and a set of threshold, wherein the method is continuously executed with a sliding time period to enable ongoing monitoring of the identifiers, wherein the sliding time period adds and eliminates portions of the first data and the second data as the time period slides forward in time to alter the generated rankings; wherein the at least one action to one or more of the identifiers based on the generated customer confidence rankings for each of the one or more identifiers and the set threshold comprises: transmit an automated notification to one or more client representative devices; transmit an automated direct communication to one or more computing devices; execute an automated adjustment with respect to future costs; or an automated initiation of a particular service.
These limitations as drafted, are a process that, under its broadest reasonable interpretation, covers methods of organizing human activity (managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)) and mathematical calculations (a binomial probability cumulative distribution function, confidence ranking based on predicted likelihood), but for the recitation of generic computer components. That is, other than reciting the structural elements (such as computing device, one or more database, a mapping module, customer database systems; executing predictive risk modeling algorithm configured with the computing device, a binomial probability cumulative distribution function, machine learning technique, natural language processing processor, medium), the claims are directed to assessing risk with customers and initiating action to address the issue based on confidence ranking. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of organizing human activity but for the recitation of generic computer components, the claim recites an abstract idea.
Step 2A Prong 2 - This judicial exception is not integrated into a practical application because the claim merely describes how to generally “apply” the concept of receiving data, analyzing it, and providing confidence ranking. In particular, the claims only recites the additional element – computing device, one or more database, a mapping module, customer database systems; executing predictive risk modeling algorithm configured with the computing device, a binomial probability cumulative distribution function, machine learning technique, natural language processing processor, medium. The additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Simply implementing the abstract idea on generic components is not a practical application of the abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. a) The additional elements merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). Further, the limitation of “executing a predictive risk modeling algorithm; machine learning technique executed on the predictive risk modeling algorithm” is simply application of a computer model, itself an abstract idea. Furthermore, such applying of a model is no more than putting data into a black box machine learning operation, devoid of technological implementation and application details. Each step requires a generic computer to perform generic computer functions. Further, in alternative, the limitation of initiating at least one automated action including transmit an automated notification; transmit an automated direct communication..” is simply transmitting notification/response which is merely a post solution step of transmitting data output. The claims are directed to an abstract idea. When considered in combination, the claims do not amount to improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a), applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b), effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c), or applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they does not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
Step 2B: Considering Additional Elements
The claimed invention is directed to an abstract idea without significantly more. The claim does not include additional elements that are sufficient to amount significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claims describe how to generally “apply” to; assessing risk with customers. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The independent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. The claims are not patent eligible. The dependent claim(s) when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail to establish that the claim(s) is/are not directed to an abstract idea. The dependent claims are not significantly more because they are part of the identified judicial exception. See MPEP 2106.05(g). The claims are not patent eligible. With respect to the computing device, one or more database, a mapping module, customer database systems; executing predictive risk modeling algorithm configured with the computing device, a binomial probability cumulative distribution function, machine learning technique, natural language processing processor, medium, these limitations are described in Applicant’s own specification as generic and conventional elements. See Applicants specification, Paragraph [0014] details “ computing device includes one or more processors and memory, [0015] computing device includes general purpose processors. [0013] computing device enables automated predictive modeling” These are basic computer elements applied merely to carry out data processing such as, discussed above, receiving, analyzing, transmitting and displaying data. As discussed in Step 2A, Prong Two above, the recitations of “transmitting steps” in automated action limitation amount to transmitting data over a network and are well understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. Furthermore, the use of such generic computers to receive or transmit data over a network has been identified as a well understood, routine and conventional activity by the courts. See Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); 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); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result-a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added)); Also see MPEP 2106.05(d) discussing elements that the courts have recognized as well-understood, routine and conventional activities in particular fields. Lastly, the additional elements provides only a result-oriented solution which lacks details as to how the computer performs the claimed abstract idea. Therefore, the additional elements amounts to mere instructions to apply the exception. See MPEP 2106.05(f). Furthermore, these steps/components are not explicitly recited and therefore must be construed at the highest level of generality and are mere instructions to implement the abstract idea on a computer. Therefore, the claimed invention does not demonstrate a technologically rooted solution to a computer-centric problem or recite an improvement to another technology or technical field, an improvement to the function of any computer itself, applying the exception with, or by use of, a particular machine, effect a transformation or reduction of a particular article to a different state or thing, add a specific limitation other than what is well-understood, routine and conventional in the field, add unconventional steps that confine the claim to a particular useful application, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment such as computing. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. Taking the additional claimed elements individually and in combination, the computer components at each step of the process perform purely generic computer functions. Viewed as a whole, the claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field. Use of an unspecified, generic computer does not transform an abstract idea into a patent-eligible invention. Thus, the claim does not amount to significantly more than the abstract idea itself. Further, claims to a system and computer-readable storage medium are held ineligible for the same reason, e.g., the generically-recited computers add nothing of substance to the underlying abstract idea. Dependent claims 2-6, 9-13, and 16-20 add additional limitations, for example but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as representative claims 1, 8 and 15. Claims 2, 9 and 16 recites mapping one or more descriptors with the first data and second data to one or more identifiers. Claims 3-4, 10-11, 17-18 recites customer service records include identifier, in process sales, open sales data. Claims 5, 12, 19 recite binomial distribution on customer data. Claims 6, 13 and 20 recites predictive modeling using data over set period of time. The limitation of executing a binomial distribution algorithm (claim 5) merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The dependent claims do not integrate into a practical application. As such, the additional elements individually or in combination do not integrate the exception into a practical application, but rather, the recitation of any additional element amounts to merely reciting the words “apply it” (or equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (See MPEP 2106.05(f)). The dependent claims also do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a computing system is merely being used to apply the abstract idea to a technological environment. These limitations do not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. See MPEP 2106.05d. Thus, the claims do not add significantly more to an abstract idea. The claims are ineligible. Therefore, since there are no limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, the claims are rejected under 35 USC 101 as being directed to non-statutory subject matter. See (Alice Corporation Pty. Ltd. v. CLS Bank International, et al.).
Response to Arguments
Applicant's arguments filed 3/2/26 have been fully considered but they are not persuasive.
Regarding 101 rejection, applicant on pages 1-2, states that claims are not directed to abstract idea.
Examiner has considered all arguments and respectfully disagrees. The claim limitations as drafted, are a process that, under its broadest reasonable interpretation, covers methods of organizing human activity (managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)) and mathematical calculations (confidence ranking based on predicted likelihood), but for the recitation of generic computer components. That is, other than reciting the structural elements (such as computing device, customer database systems, predictive risk modeling algorithm, processor, medium), the claims are directed to assessing risk with customers.
Applicant states claims are similar to example 39 and do not recite a judicial exception. In example 39, claims are directed to training a neural network for facial detection. The current claims do not include training of model or ML, the technology/additional elements are recited at “apply it” level. Therefore, the current claims are not similar to example 39.
Examiner notes claims are similar to example 47 Claim 2, where additional elements (a) and (f) were both found to be insignificant extra-solution activity in Step 2A, Prong Two, because they were determined to be insignificant limitations as necessary data gathering and outputting. However, a conclusion that an additional element is insignificant extra-solution activity in Step 2A, Prong Two should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g). As discussed in Step 2A, Prong Two above, the recitations of “(a) receiving continuous training data” and “(g) outputting the anomaly data from the trained ANN” are recited at a high level of generality. These elements amount to receiving or transmitting data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. In the instant case, claims recite a predictive risk modeling algorithm/a machine learning technique at high level of generality i.e. “apply it “ level. The limitation of initiating at least one automated action including transmit an automated notification; transmit an automated direct communication..” is simply transmitting notification/response which is merely a post solution step of transmitting data output. Specific to ‘initiating a particular service or execute an automated adjustment”, specification does not disclose how these automated actions are achieved. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea.
In regards to BASCOM -
The BASCOM court agreed that the additional elements were generic computer, network, and Internet components that did not amount to significantly more when considered individually, but explained that the district court erred by failing to recognize that when combined, an inventive concept may be found in the non-conventional and non-generic arrangement of the additional elements, i.e., the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user (note that the term "inventive concept" is often used by the courts to describe additional element(s) that amount to significantly more than a judicial exception). (Page 3, emphasis added).
In BASCOM, as in the instant case, the claimed invention was directed to an abstract idea, and only contained additional elements not amounting to significantly more when considered individually. However, the distinction between BASCOM and the instant case is that the claimed invention had a “non-conventional and non-generic arrangement of the additional elements.” This non-conventional arrangement was “installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user.” (BASCOM, 827 F.3d at 1345). In the instant case, there is no indication that the arrangement of the components is non-conventional or non-generic. Instead, the computer appears to be a generic computer (Figure 2 #22 of Applicants specification [0015] The processor(s) 22 of the customer confidence management computing device 12 may include one or more CPUs or general purpose processors with one or more processing cores, for example, although other types of processor(s) can also be used.) used to display career paths of members in a social network. Therefore, the arrangement of elements is conventional and generic.
Regarding Applicant’s ordered combination argument, Examiner notes that the additional elements were considered "as an ordered combination," and determined that "the computer components … ‘[a]dd nothing … that is not already present when the steps are considered separately’" and simply recite functions as performed by a generic computer." 573 U.S. at 225 (citing Mayo, 566 U.S. at 79, 101 USPQ2d at 1972). The claims do not recite additional elements either individually or in an ordered combination that amount to significantly more than the judicial exception.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mitchell US 2014/0304032 teaches wherein the customer service data comprises datasets of customer service case records for the customer identifiers and wherein the customer order data comprises in-process sales order data, in-preparation sales order data, open sales order data, and pre-sales opportunity data for the plurality of customers ([0071] order data includes attributes such as customer identity, ordered items, quantities/price, [0072] customer data 412 comprises information concerning the particular customer placing the order, and may include attributes such as customer name/ID, size, type, location)
Kannan (US 2018/0374108) discloses building a user profile for each user is essential for personalized services, such as product recommendation, proactive notifications, and personalized offers.
Rogynskyy (US 2020/0372075) discloses maintaining confidence scores of entity associations derived from systems of record. The system can access a record objects of systems of record. The system can identify, from a record object corresponding to a first group entity, an account relationship data structure specifying a relationship. The system can identify a first group node profile corresponding to the first group entity.
Cassel et al. (US 11,461,751 B2) discloses confidence rankings for each of the customer identifiers (Fig 11 # 112 showing ranking for various user ID, Col 30 lines 47-54 The set of results 1022 may be a set of user identifiers and/or historical record identifiers for historical records associated with respective user identifiers, and may include a score (confidence ranking) for each of the user identifiers reflecting a level of confidence that a supervised model of the record matching service 1014 has that the respective user identifier is associated with the same user Col 31 lines 6-10 determination of a user identity 1148 of a user whose record-related details yielded the set of results received from a supervised model of a record matching system, Col 39 lines 13-34The risk prediction system configured to perform a risk assessment of the user based on the user identity, past information about the user, and the details 1516. For example, if the user is a new user with no payment history, the risk prediction system 1550 may determine that the risk that the user will default on payment is higher, and consequently the value output in the user credit risk 1522 may reflect this risk., Col 44 lines ).
Kannan (US 11,080,721 B2) teaches predictive risk modeling…to generate one of a plurality of customer confidence rankings on a predicted likelihood of encountering an issue for each of the customer identifiers. (Col 3 lines 20-41 a predictive engine which compiles the data from the data warehouse and organizes the data into clusters known as contributing variables., Fig 2 # 1215 shows customer type and probability of issue CT1 20.2% CT2 19.7% (customer confidence ranking on predicted likelihood) and Col 8 lines 9-11 The model displays the likelihood that a certain type of customer 1215 at that engagement stage 1210 will have a problem (likelihood of encountering issue). , Col 8 lines 42-67 Dimension refers to attributes of an entity for analysis, for example, customer interaction as a product of geography. Measures refer to variables that can be measured. For example, number of products purchased, number of issues associated with a product, The predictive engine predicts information, such as the probability of a customer to face a particular problem, based on the customer's engagement stage with a particular problem)
Malalel (US 10,402,737) discloses providing proactive customer care for issues associated with billing or ordering processes. In use, a likelihood that a customer is going to call a call center to address at least one issue associated with at least one of an ordering process or a billing process is predicted
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/SANGEETA BAHL/Primary Examiner, Art Unit 3626