Andrew E. Fano et al.Download PDFPatent Trials and Appeals BoardNov 12, 201914142160 - (D) (P.T.A.B. Nov. 12, 2019) Copy Citation UNITED STATES PATENT AND TRADEMARK OFFICE UNITED STATES DEPARTMENT OF COMMERCE United States Patent and Trademark Office Address: COMMISSIONER FOR PATENTS P.O. Box 1450 Alexandria, Virginia 22313-1450 www.uspto.gov APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO. 14/142,160 12/27/2013 Andrew E. Fano 12587-0225004 1398 26212 7590 11/12/2019 FISH & RICHARDSON P.C. (ACCENTURE) P.O. BOX 1022 MINNEAPOLIS, MN 55440-1022 EXAMINER HAMILTON, MATTHEW L ART UNIT PAPER NUMBER 3682 NOTIFICATION DATE DELIVERY MODE 11/12/2019 ELECTRONIC Please find below and/or attached an Office communication concerning this application or proceeding. The time period for reply, if any, is set in the attached communication. Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the following e-mail address(es): PATDOCTC@fr.com PTOL-90A (Rev. 04/07) UNITED STATES PATENT AND TRADEMARK OFFICE BEFORE THE PATENT TRIAL AND APPEAL BOARD Ex parte ANDREW E. FANO, CHAD M. CUMBY, RAYID GHANI, and MARKO KREMA Appeal 2018–008711 Application 14/142,160 Technology Center 3600 Before MURRIEL E. CRAWFORD, PHILIP J. HOFFMANN, and BRADLEY B. BAYAT, Administrative Patent Judges. CRAWFORD, Administrative Patent Judge. DECISION ON APPEAL STATEMENT OF THE CASE Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the Examiner’s final decision to reject claims 8–13 and 22–33. We have jurisdiction under 35 U.S.C. § 6(b). We AFFIRM. 1 We use the word Appellant to refer to “applicant” as defined in 37 C.F.R. § 1.42. Appellant identifies the real party in interest as Accenture Global Services Limited. Appeal Br. 1. Appeal 2018–008711 Application 14/142,160 2 CLAIMED SUBJECT MATTER The claims are directed to a system for individualized customer interaction. Claim 8, reproduced below, is illustrative of the claimed subject matter: 8. A computer-implemented method comprising: obtaining, by one or more computers and over a network, transaction data from one or more input devices that each include a respective card reader, the transaction data comprising customer identifying information obtained by the input devices using the respective card readers; associating, by the one or more computers, the transaction data with a plurality of customers based on the customer identifying information; training a plurality of machine learning models on the transaction data associated with the plurality of customers, each machine learning model corresponding to a respective customer and configured to predict a probability that the corresponding respective customer will purchase products belonging to a product category during a predetermined period of time; determining that a plurality of potential customers do not have a corresponding machine learning model; associating each of the plurality of potential customers that do not have a corresponding machine learning model with an aggregate machine learning model; determining, by the one or more computers and for each customer of the plurality of customers, a respective predicted probability that the customer will purchase products belonging to the product category during the predetermined period of time using the machine learning models corresponding to customers; determining, by the one or more computers and for each potential customer of the plurality of potential customers, a respective predicted probability that the potential customer will Appeal 2018–008711 Application 14/142,160 3 purchase products belonging to the product category during the predetermined period of time using the aggregate machine learning model associated with the plurality of potential customers; generating, by the one or more computers and based on the respective predicted probabilities for the customers and the respective predicted probabilities for the potential customers, a prediction of an amount of products in the product category that will be purchased during the predetermined period of time; and determining a sufficient amount of products in the product category that should be maintained in inventory based at least on the prediction of an amount of products in the product category that will be purchased during the predetermined period of time. REJECTION Claims 8–13 and 22–33 are rejected under 35 U.S.C. § 112, first paragraph, as failing to comply with the written description requirement. Claims 8–13 and 22–33 are rejected under 35 U.S.C. § 101 as directed to ineligible subject matter, in the form of abstract ideas. OPINION Rejections under 35 U.S.C. § 112, first paragraph The Examiner separately finds that each of the “associating,” “training,” and “determining” limitations, a total of six complete limitations, of independent claim 8, and corresponding limitations in independent claims 22 and 28, are “not disclosed by the applicant’s [Specification]2.” 2 For the first “associating” limitation the Examiner finds the language is “not disclosed by the [A]pplicant’s invention.” Final Act. 3 (emphasis added). We interpret that to be essentially the same as the Appellant’s Specification. Appeal 2018–008711 Application 14/142,160 4 Final Act. 3–8. The Examiner finds, for example, that “Paragraph 0044 does not disclose one or more computers associating the transaction data with a plurality of customers based on the customer identifying information.” Final Act. 4. As noted by the Examiner in the Final Office Action, the Appellant argued that paragraph 101 discloses implementing the invention on computers, but the Examiner responds that “paragraph 0101 does not disclose the limitation, ‘associating, by the one or more computers, the transaction data with a plurality of customers based on the customer identifying information.’”3 Final Act. 13. In the Appeal Brief, the Appellant argues there is support for the first “associating” limitation at paragraphs 44 and 113 of the Appellant’s Specification. Appeal Br. 5–6. In response, the Examiner “notes paragraph 0044 discloses grocery stores using loyalty card programs to capture information associated with customers making purchase transactions,” and concludes “[p]aragraphs 0044 and 0113 do not disclose the limitation, ‘associating, by the one or more computers, the transaction data with a plurality of customers based on the customer identifying information.’” Answer 4–5. New or amended claims, which introduce elements or limitations which are not supported by the as-filed disclosure, violate the written 3 Prior to the Final Action, the Appellant refers to paragraph numbers in the Appellant’s disclosure in US 2014–0114743 A1, published April 24, 2014. In the Appeal Brief, the Specification cites paragraphs “numbered as filed.” Appeal Br. 1. Paragraph 101 of the ’743 publication corresponds to paragraph 113 of the originally-filed Specification. We use the originally- filed Specification paragraph numbers except in this quotation from the Final Action. Appeal 2018–008711 Application 14/142,160 5 description requirement. See, e.g., In re Lukach, 442 F.2d 967 (CCPA 1971). “The purpose of the written description requirement is to prevent an applicant from later asserting that he invented that which he did not; the applicant for a patent is therefore required ‘to recount his invention in such detail that his future claims can be determined to be encompassed within his original creation.’” Amgen Inc. v. Hoechst Marion Roussel Inc., 314 F.3d 1313, 1330 (Fed. Cir. 2003) (citing Vas Cath Inc. v. Mahurkar, 935 F.2d 1555, 1561 (Fed. Cir. 1991)). While there is no in haec verba requirement, newly added claim limitations must be supported in the specification through express, implicit, or inherent disclosure. The fundamental factual inquiry is whether the Specification conveys with reasonable clarity to those skilled in the art that, as of the filing date sought, applicant was in possession of the invention as now claimed. See, e.g., Vas-Cath, Inc., 935 F.2d at 1563–64. When an explicit limitation in a claim is not present in the written description it must be shown that a person of ordinary skill would have understood that the description requires that limitation. Hyatt v. Boone, 146 F.3d 1348, 1353, (Fed. Cir. 1998). The Examiner is essentially arguing that the precise words of the limitation do not appear in the paragraphs cited by the Appellant, but this is not a proper application of the law. Paragraph 44 of the Appellant’s Specification describes that “stores often use loyalty card programs to capture information about millions of transactions and purchases, where such information may be associated with the customers making the transactions and purchases.” Spec. ¶ 44 (emphasis added). Paragraph 113 describes that “any or all of the runtime system 300 . . . may be implemented on one or more computers.” Spec. ¶ 113 (emphasis Appeal 2018–008711 Application 14/142,160 6 added). As can be seen, paragraph 44 of the Specification describes associating transaction data with customer data, and paragraph 113 describes implementing this on a computer. The ordinary artisan would recognize this shows possession of the concepts relevant to the claim language “associating, by the one or more computers, the transaction data with a plurality of customers based on the customer identifying information.” In addition, in response, the Examiner introduces the assertion that “the Appellant is claiming a specific embodiment recited in the Specification,” but the Examiner interprets that embodiment is disclosed in paragraph 225, which does not recite the specific language of the various claim limitations. See Answer 6–8 (“This particular embodiment [in paragraph 225] does not disclose training a plurality of machine learning models on the transaction data associated with the plurality of customers, each machine learning model corresponding to a respective customer.”).4 The situation is the same for every limitation the Examiner finds unsupported by the Specification. The Examiner is looking for the exact claim limitation to appear, verbatim, in a single location in the Specification, and additionally is selecting the place in the Specification the Examiner expects that disclosure to be located. See generally Final Act. 3–10; see also Answer 3–20. This is overly restrictive, and is contrary to the law that 4 A similar statement appears at the end of recited paragraph 225 for each limitation (Answer 6–20) except the Response to Argument for the first “associating” limitation. See Answer 5. For this particular “training” limitation, the Appellant argues support in paragraphs 13, 51–64, and 228 of the Specification. Appeal 2018–008711 Application 14/142,160 7 applies here. The rejection, therefore, is in error for these reasons, for each and every limitation rejected. On this basis, we do not sustain any of the rejections of claims as lacking written description support. Rejection under 35 U.S.C. § 101 An invention is patent-eligible if it claims a “new and useful process, machine, manufacture, or composition of matter.” See 35 U.S.C. § 101. However, the Supreme Court has long interpreted 35 U.S.C. § 101 to include implicit exceptions: “[l]aws of nature, natural phenomena, and abstract ideas” are not patentable. E.g., Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 216 (2014). In determining whether a claim falls within an excluded category, we are guided by the Supreme Court’s two-step framework, described in Mayo and Alice. Id. at 217–18 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 75–77 (2012)). In accordance with that framework, we first determine what concept the claim is “directed to.” See Alice, 573 U.S. at 219 (“On their face, the claims before us are drawn to the concept of intermediated settlement, i.e., the use of a third party to mitigate settlement risk.”); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) (“Claims 1 and 4 in petitioners’ application explain the basic concept of hedging, or protecting against risk.”). Concepts determined to be abstract ideas, and thus patent ineligible, include certain methods of organizing human activity, such as fundamental economic practices (Alice, 573 U.S. at 219–20; Bilski, 561 U.S. at 611); mathematical formulas (Parker v. Flook, 437 U.S. 584, 594–95 (1978)); and Appeal 2018–008711 Application 14/142,160 8 mental processes (Gottschalk v. Benson, 409 U.S. 63, 69 (1972)). Concepts determined to be patent eligible include physical and chemical processes, such as “molding rubber products” (Diamond v. Diehr, 450 U.S. 175, 191 (1981)) “tanning, dyeing, making water-proof cloth, vulcanizing India rubber, smelting ores,” (id. at 182 n.7 (quoting Corning v. Burden, 56 U.S. 252, 267–68 (1854))); and manufacturing flour (Benson, 409 U.S. at 69 (citing Cochrane v. Deener, 94 U.S. 780, 785 (1876))). In Diehr, the claim at issue recited a mathematical formula, but the Supreme Court held that “[a] claim drawn to subject matter otherwise statutory does not become nonstatutory simply because it uses a mathematical formula.” Diehr, 450 U.S. at 187, 191 (“We view respondents’ claims as nothing more than a process for molding rubber products and not as an attempt to patent a mathematical formula.”). Having said that, the Supreme Court also indicated that a claim “seeking patent protection for that formula in the abstract . . . is not accorded the protection of our patent laws,[] and this principle cannot be circumvented by attempting to limit the use of the formula to a particular technological environment.” Id. at 187 (“It is now commonplace that an application of a law of nature or mathematical formula to a known structure or process may well be deserving of patent protection.”), 191 (citing Benson and Flook). If the claim is “directed to” an abstract idea, we turn to the second step of the Alice and Mayo framework, where “we must examine the elements of the claim to determine whether it contains an ‘inventive concept’ sufficient to ‘transform’ the claimed abstract idea into a patent- eligible application.” Alice, 573 U.S. at 221 (quotation marks omitted). “A claim that recites an abstract idea must include ‘additional features’ to Appeal 2018–008711 Application 14/142,160 9 ensure ‘that the [claim] is more than a drafting effort designed to monopolize the [abstract idea].’” Id. (quoting Mayo, 566 U.S. at 77). “[M]erely requir[ing] generic computer implementation[] fail[s] to transform that abstract idea into a patent-eligible invention.” Id. The PTO recently published revised guidance on the application of § 101. 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019) (“Guidance”). Under the Guidance, we first look to whether the claim recites: (1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity such as a fundamental economic practice, or mental processes); and (2) additional elements that integrate the judicial exception into a practical application (see Manual of Patent Examining Procedure (“MPEP”) § 2106.05(a)–(c), (e)–(h)). Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look to whether the claim: (3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, conventional” in the field (see MPEP § 2106.05(d)); or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. See Guidance. Appeal 2018–008711 Application 14/142,160 10 Prong One of Revised Step 2A of the Guidance The Appellant argues all claims together as a group. Appeal Br. 9–11. We select claim 8 as representative. See 37 C.F.R. § 41.37(c)(1)(iv). The Examiner finds claim 8 is directed to mathematical calculations and relationships. Final Act. 11. Claim 8 recites “training . . . models . . . to predict a probability,” “determining . . . a respective probability,” “generating . . . a prediction of an amount,” and “determining a sufficient amount.” These steps rely on the performance of mathematical calculations, and as such are abstract steps. See Guidance 52; see also MPEP § 2106.04(a)(1)(IV)(B). Claim 8 also recites “associating . . . transaction data with a plurality of customers based on the customer identifying information,” and “determining that a plurality of potential customers do not have a corresponding machine learning model.” App. Br. 13, Claims App. As with the steps that perform mathematical calculations, these steps can be performed mentally by a human, because they involve “observation, evaluation, judgment, [and] opinion.” See Guidance 52; see also MPEP § 2106.04(a)(1)(III)(A). The claim recites that the models are “machine learning models.” The Specification does not define “machine learning,” but describes there “are several examples of machine learning methodologies, such as decision-tree based and linear based methodologies. The examples of machine learning methodologies are merely for illustrative purposes. “Other types of machine learning methodologies are possible.” Spec. ¶ 61 (cited Appeal Br. 2). The Specification describes that customer models: Appeal 2018–008711 Application 14/142,160 11 may comprise one or more sub-models, such as a shopping list sub-model, or may comprise one or more attributes, such as behavior, brand loyalty, wallet share, price sensitivity, promotion sensitivity, product substitution, basket variability, frequency of shopping, etc. The customer model may thus be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning, to customer interaction (such as before, during, or after the retail experience). Spec. ¶ 32. The Specification further describes that the claimed invention “may use the customer models for customers of the retail establishment in order to estimate purchases of a product category for a predetermined period. The estimated purchases of the product for the individual customers may be summed in order to provide an estimate for the predetermined period.” Spec. ¶ 36. Based on the descriptions in the Specification, we construe the “machine learning model” of the claims to be a simulation of customer behavior. Because a simulation is an abstract idea that imitates a customer, and can be analogized to mental thought, the “machine learning models” of the claims are encompassed within the abstract ideas recited in the claims. The Specification describes an embodiment that provides an “inventory planning component configured to estimate purchases for the product category in a pre-determined period and configured to aggregate the estimated purchases.” Spec. ¶ 13. Based on this, and the recited claim limitations, under Prong One of Revised Step 2A of the Guidance, claim 8 recites an abstract idea involving mathematical calculations and steps that can be performed mentally. Prong Two of Revised Step 2A of the Guidance Appeal 2018–008711 Application 14/142,160 12 Turning to Prong Two of our Guidance, we evaluate whether claim 8 as a whole integrates the abstract idea into a practical application of the abstract idea. Guidance 54. Here, claim 8 recites a step that gathers data, by “obtaining, over a network, transaction data from one or more input devices that each include a respective card reader, the transaction data comprising customer identifying information obtained by the input devices using the respective card readers.” This is insignificant extra-solution activity, because it is merely a data- gathering step. See Guidance 55; see also MPEP § 2106.05(g). Other than the steps above that are encompassed within the abstract idea, claim 8 recites that the “associating” step, second and third-recited “determining,” and “generating” steps are performed “by the one or more computers.” Also, in the data-gathering “obtaining” step, the claim recites a “network,” and “input devices that each include a respective card reader.” This means that the only “additional elements,” beyond the abstract ideas to which the claims are directed, are the “one or more computers,” as well as the “network” and “card readers” that are used for gathering data. The method does not improve the underlying “computers,” “network,” or “card readers,” recited as performing the limitations of claim 8. For example, any computer can be used to execute the claimed method, and its operation is essentially unaffected by the claimed method. See Spec. ¶ 113 (“The computer may include one or more processors. The processor may include any type of device or devices used to process digital information.”). The “network” is merely a tool for data collection or presenting output, and similarly is unaffected by the claimed method. Spec. ¶ 139. The “card reader” is just a generic data-gathering device. Spec. ¶ 140 (“[A] card reader Appeal 2018–008711 Application 14/142,160 13 or other such device that can obtain a customer’s identifying information from a credit card, bank card, frequent shopper card, loyalty card, or any other such card containing information that uniquely identifies the customer.”). In addition, the method is directed to “improv[ing] the accuracy and robustness of predictive models used by retail establishments for inventory control.” Appeal Br. 1 (citing Spec. ¶¶ 7, 160–66).5 As such the claimed method does not improve another technology. See Guidance 55; see also MPEP § 2106.05(a). Because a particular computer is not required, the claim also does not define or rely on a “particular machine.” See MPEP § 2106.05(b). Further, the method does not transform matter. See MPEP § 2106.05(c). Instead, the claim gathers, gathers, analyzes, and generates data. As such, the method has no other meaningful limitations, and thus merely recites instructions to execute the abstract idea on a computer. See MPEP §§ 2106.05(f), (g). As such, we determine that claim 8 does not integrate the judicial exception into a practical application, and thus, is directed to an abstract idea. Step 2B of the Guidance Because we have determined that claim 8 recites, and is directed to, abstract ideas, and does not integrate the abstract ideas into a practical application, we turn to Step 2B and consider whether an additional element 5 Paragraphs 160–66 of the Specification describe a shopping list prediction module, not an inventory prediction module. We are unclear on its descriptive value in the context of the pending claims. Appeal 2018–008711 Application 14/142,160 14 or combination of elements adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, or simply appends well-understood, routine, conventional activities previously known to the industry. See Guidance 56. The only additional elements, beyond the abstract idea of performing mathematical calculations or performing steps that can be performed mentally, is the “one or more computers,” “network,” and “card readers.” These computer components, however, include only a general-purpose computer, network, and data gathering devices. Spec. ¶¶ 113, 139, 140. Considering the claimed method steps as an ordered combination, the claim involves gathering data (“obtaining”), linking data elements (“associating”), and simulating human behavior to make predictions from the data (“training,” predicting, “determining,” and “generating . . . a prediction”). However, the operations of storing, analyzing, receiving, and writing data are primitive computer operations found in any computer system. See In re Katz Interactive Call Processing Patent Litig., 639 F.3d 1303, 1316 (Fed. Cir. 2011). Thus, the only additional functional or structural elements, beyond the abstract idea, are well-understood, routine, and conventional. See MPEP § 2106.05(d). Therefore, claims 8–13 and 22–32 are directed to abstract ideas, and do not recite limitations that transform the abstract ideas into eligible subject matter, by integrating the abstract ideas into a practical application, or by reciting an inventive concept. We turn to and consider next the Appellant’s arguments. The Appellant argues the claims “represent improvements to computer technology, in particular, in the area of machine learning-based Appeal 2018–008711 Application 14/142,160 15 predictive models.” Appeal Br. 10 (citing Spec. ¶¶ 60–64). As we established above, however, we discern no improvement to the underlying computer technology. Any improvement to the algorithms to make predictions are encompassed by the abstract ideas, because the techniques described at paragraphs 60–64 can be performed mentally. We are unpersuaded by the Appellant’s assertion that the claimed features “are not generic mental steps.” Appeal Br. 10. The Appellant has provided no evidence the steps would be unable to be performed mentally, other than the nominal recitations that they are intended to be performed by a computer. We are similarly unpersuaded by the Appellant’s assertion that the “claims address a problem arising in computer technology and improve” computer technology described, or improved, in the cited portion of the Specification. Appeal Br. 10. The Appellant’s argument, citing Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir. 2016), amounts to asserting that any “improvement” in any software automatically is an improvement in computer technology, which is a claimed method out of the realm of abstract ideas. The Appellant has not offered any persuasive evidence or technical reasoning that the computer implementation improves the functioning of the computing system itself. An analytical algorithm for making predictions from data, even if different from known algorithms, does not reflect an improvement to the functioning of the claimed computing system. There is a fundamental difference between computer functionality improvements, on the one hand, and uses of existing computers as tools to perform a particular task, on the other. In Enfish, for example, the court noted that “[s]oftware Appeal 2018–008711 Application 14/142,160 16 can make non-abstract improvements to computer technology just as hardware improvements can.” Enfish, 822 F.3d at 1335. The court asked “whether the focus of the claims is on [a] specific asserted improvement in computer capabilities . . . or, instead, on a process that qualifies as an ‘abstract idea’ for which computers are invoked merely as a tool.” Id. at 1335–36. The court found that the “plain focus of the claims” there was on an improvement to computer functionality itself (a self-referential table for a computer database, designed to improve the way a computer carries out its basic functions of storing and retrieving data), not on economic or other tasks for which a computer is used in its ordinary capacity. Id. Thus, we determine whether the claim as a whole “focus[es] on a specific means or method that improves the relevant technology” or is “directed to a result or effect that itself is the abstract idea and merely invoke[s] generic processes and machinery.” McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314–15 (Fed. Cir. 2016) (Claims determined not abstract because they “focused on a specific asserted improvement in computer animation.”). Unlike Enfish and McRO, we find the focus of the claim as whole here on is on the latter, because the claimed computing system is merely invoked as a tool for gathering and linking data, simulating behavior, and making predictions. The Appellant finally argues that “[l]ike the claims in Bascom, the present claims ‘improve[] an existing technological process’ . . . with a non- obvious arrangement of elements, and are thus patent-eligible.” Appeal Br. 11. We disagree with the Appellant. In Bascom Global Internet Services, Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016), the Federal Appeal 2018–008711 Application 14/142,160 17 Circuit held that “[t]he inventive concept described and claimed in the ’606 patent is the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user.” Id. at 1350. The court explained that the remote location of a filtering tool having customizable user-specific filtering features provides the filtering tool both the benefits of a filter on a local computer and the benefits of a filter on the ISP server, which is a technical improvement over prior art ways of filtering content. Id. at 1350–51. Here, Appellant has not demonstrated any particular arrangement in the claim as providing an inventive concept parallel to Bascom in claiming a technology-based solution. To the extent that the Appellant is arguing that an improvement in an abstract idea is non-abstract because it is new, novel, or not well-understood, routine, or conventional, we disagree because even unconventional abstract ideas are still unpatentable. See SAP America, Inc. v. Investpic, LLC, 890 F.3d 1016, 1018 (Fed. Cir. 2018). “What is needed is an inventive concept in the non-abstract application realm.” SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018). Further, “[i]t has been clear since Alice that a claimed invention’s use of the ineligible concept to which it is directed cannot supply the inventive concept that renders the invention ‘significantly more’ than that ineligible concept.” BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). The Appellant has not persuaded us of error in the Examiner’s rejection of claims as directed to an abstract idea. We thus sustain the rejection of all pending claims under 35 U.S.C. § 101. Appeal 2018–008711 Application 14/142,160 18 CONCLUSION The Examiner’s rejection under 35 U.S.C. § 112, first paragraph, is reversed. The Examiner’s rejection under 35 U.S.C. § 101 is affirmed. DECISION SUMMARY In summary: Claims Rejected 35 U.S.C. § Reference(s)/Basis Affirmed Reversed 8–13, 22–23 112 first paragraph 8–13, 22–33 8–13, 22–33 101 judicial exception 8–13, 22–33 Overall Outcome: 8–13, 22–33 TIME PERIOD FOR RESPONSE No time period for taking any subsequent action in connection with this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R. § 1.136(a)(1)(iv). AFFIRMED Copy with citationCopy as parenthetical citation