DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The amendment filed 09/30/2025 has been received and considered. Claims 24 and 25 are new. Claims 1, 3, 7, 8, 10, 14-16, and 20-25 are presented for examination.
Election/Restrictions
Newly submitted claims 24 and 25 are directed to inventions independent or distinct from the invention originally claimed for the following reasons:
I. Claims 1, 3, 7, 8, 10, 14-16, and 20-23 drawn to electronic devices for incremental lossless summarization of a massive graph and an operating method, classified in G06F 16/9024 - graphs (the invention originally claimed).
II. Claim 24 drawn to a World Wide Web system, classified in G05B 2219/35008 - www cad, world wide design and manufacturing.
III. Claim 25 drawn to a deep learning model system, classified in G06T 2211/441 - AI-based methods, deep learning or artificial neural networks.
Newly submitted claims 24 and 25 are directed to inventions independent or distinct from the invention originally claimed for the following reasons:
Inventions I, II, and III are unrelated. Inventions are unrelated if it can be shown that they are not disclosed as capable of use together and they have different designs, modes of operation, and effects (MPEP § 802.01 and § 806.06). In the instant case, as to invention II, these limitations are absent from invention I: a World Wide Web system comprising: web page nodes and a network coupled to each of the web page nodes; as to invention III, these limitations are absent from invention I: a deep learning model system comprising nodes and a network coupled to each of the nodes.
Examiner notes that these limitations absent from invention I are also absent from the original disclosure and do not satisfy the written description requirement. Applicant argues, (see page 15, last paragraph) – underline emphasis added:
‘New claim 24 relates to a world wide web system that may use the modified graph according to the other independent claims to obtain information on web page nodes adjacent one of the web page nodes. New claim 25 relates to a neural network that may use the modified graph according to the other independent claims to obtain information on neural network nodes adjacent one of the neutral network nodes. These claims are thus separately eligible as being directed toward a particular system, which is a practical application of the alleged abstract concepts’.
Examiner notes that the Application description is silent regarding "a world wide web system that may use the modified graph", "web page nodes", "a neural network that may use the modified graph", and "neural network nodes", as argued.
The Application description is also silent regarding "a world wide web system", "web page nodes", "a deep learning model system", and "executing the neural network", as claimed. As to the limitations "World Wide Web", "nodes", and "deep learning", the Application description merely reads (underline emphasis added):
'[2] A graph is a data structure that represents objects and the connections between them, which may express various and numerous data. Representative examples of the graph include an online social network (connection between users), the World Wide Web (connection between webpages), a purchase history on e-commerce (connection between a customer and a product), a deep learning model (connections between neurons), and so on. With the recent rise of the big data era, large-scale graph data is emerging. For example, the World Wide Web is connecting 5.5 billions of webpages, and a particular social network is connecting 2.4 billions of users.
[3] Such massive data exceeds the capacity of main memory or cache memory of a computer, making analysis difficult. This is because most graph analysis algorithms assume that an entire graph is stored in main memory. A solution to this problem is to compress graph data so that it is stored in main memory'
Graphs representing objects and their connections between them, i.e. data representing the World Wide Web (connection between webpages) and a deep learning model (connections between neurons), are not the same as "a world wide web system" and "a deep learning model system that may use the modified graph" , as argued. The claimed invention further reads "22. The method of claim 1, wherein the dynamic massive graph represents an online social network, the World Wide Web, a purchase history on e-commerce, or a deep learning model".
The current claims restricted out belong to unrelated inventions, which requires performing a new art search, a new 101 analysis, and a new 112 analysis.
Since Applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 24 and 25 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
Claim Objections
Claims 1, 8, and 15 include the typo “that that” ("… performing a Markov Chain Monte Carlo (MCMC)-based random sampling method that that…"). Examiner interprets as “that" for examination purposes.
Appropriate correction or clarification is required.
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 1, 3, 7, 8, 10, 14-16, and 20-23 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 applicant regards as the invention.
Claim 1 recites the limitation "the changed node" in line(s) 29. There is insufficient antecedent basis for this limitation in the claim. There is a plurality of changed nodes anteceding this limitation. The recitation of “the changed node” is unclear because it is uncertain which of the plurality was intended.
As to claims 8 and 15, they are objected for the same deficiency.
Dependent claims inherit the defect of the claim from which they depend.
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, 3, 7, 8, 10, 14-16, and 20-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claim 1, Step 1: operating method (process = 2019 PEG Step 1 = yes).
Independent claim 1, Step 2A, Prong One: Claim recites:
the summary graph includes at least one supernode and at least one superedge connecting the at least one supernode, which are obtained from a plurality of nodes detected from a dynamic massive graph and edges connecting the plurality of nodes, created from the dynamic massive graph and storing differences between the dynamic massive graph and the summary graph (mathematical concepts)
detecting a changed edge from the dynamic massive graph…
detecting changed nodes connected by the changed edge based on the changed edge; and via the processor,
updating the summary graph stored in the memory and the plurality of and the edge corrections based on each of the changed nodes; deciding whether to change the at least one supernode for at least one adjacent node of each of the changed nodes or not by: updating coarse clusters; constructing a testing pool with a fixed number of randomly selected adjacent nodes for each of the changed nodes; selecting part of the testing pool as a testing node; and selecting a supernode for the testing node through a trial related to the testing node by: checking for a coarse cluster containing the testing node; constructing a candidate pool with nodes belonging to both the testing pool and the coarse cluster containing the testing node, wherein the candidate pool is formed by intersecting the testing pool with the coarse cluster including the testing node; performing a Markov Chain Monte Carlo (MCMC)-based random sampling method that that avoids retrieving all of the adjacent nodes for the changed node to select a candidate node from the candidate pool; (mental concepts)
calculating an amount of change caused by the updating of the summary graph and the edge corrections based on movement of the testing node to the supernode of the candidate node, wherein the amount of change is calculated based on an objective function for the summary graph (mathematical concepts)
determining an acceptance probability for the movement based on the calculated amount of change; and maintaining the supernode as the testing node when the movement is accepted based on the acceptance probability and otherwise returning the testing node to an original supernode;
and updating the summary graph and the edge corrections based on a change of the at least one supernode for the at least one adjacent node into the summary graph in response to changes of edges and nodes occurring in the dynamic massive graph, without re-processing the entire dynamic massive graph (mental concepts)
Independent claim 1 is substantially drawn to mathematical concepts: relationships, formulas or equations, calculations and mental concepts: observation, evaluation, judgment, opinion but for the recitation of generic computer components. Information and data also fall within the realm of abstract ideas because information and/or data are intangible. See Electric Power Group1 (Electric Power hereinafter): “Information… is an intangible”.
As to the limitations "dynamic massive graph", the term is not elaborated but merely repeated in the Application description.
As to the limitations “the summary graph includes at least one supernode and at least one superedge connecting the at least one supernode, which are obtained from a plurality of nodes detected from a dynamic massive graph and edges connecting the plurality of nodes, created from the dynamic massive graph and storing differences between the dynamic massive graph and the summary graph” and “calculating an amount of change caused by the updating of the summary graph and the edge corrections based on movement of the testing node to the supernode of the candidate node, wherein the amount of change is calculated based on an objective function for the summary graph“, these limitations are substantially drawn to mathematical concepts. Graph operations are substantially drawn to mathematical relationships/calculations. The specification reads (underline emphasis added):
"[25] Given a summary graph G* = (S, P) of a graph G = (V, E), a graph
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may be obtained by connecting every pair of nodes between two neighboring supernodes, i.e., {u, v} ϵ E if and only if u≠v and {Su, Sv} ϵ P. It can be said that G* roughly describes G if ^G is similar to G. Moreover, with edge corrections C = (C+, C-) where C+:= E -
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and C-:=
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E, the original graph G = (V, E) is exactly recovered from G* as follows in [Mathematical Formula 1]. That is, G* and C losslessly summarize G. Given G, the lossless summarization problem is to find the most concise G* and C…".
As to the limitations dealing with graph updates, edges, nodes, supernodes, clusters containing nodes, and pools with nodes, they are mental in nature (mental processes). These activities can be characterized as entailing a user performing graph operations that can be performed in the human mind or by a human using a pen and paper.
As to the limitations “updating the summary graph and the edge corrections based on a change of the at least one supernode for the at least one adjacent node into the summary graph in response to changes of edges and nodes occurring in the dynamic massive graph, without re-processing the entire dynamic massive graph”, these limitations are substantially drawn to mental concepts. The specification reads (underline emphasis added):
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[75] The processor 140 may detect a changed edge from the massive graph and detect changed nodes connected by the changed edge based on the changed edge. Here, the changed edge may include at least one of an edge added to the massive graph and an edge deleted from the massive graph. Also, the processor 140 may update the summary graph and the edge corrections based on each of the changed nodes. To this end, the processor 140 may decide whether to change the supernode for at least one adjacent node of each of the changed nodes or not…
[97]… efficiently manage a summary graph created from a massive graph and edge corrections according to a lossless graph summarization technique… update a summary graph created from a massive graph and edge corrections, without summarizing the massive graph again, each time a change is made to the massive graph… update the summary graph and the edge corrections in a time-efficient manner, in spite of changes in the massive graph".
About “performing a Markov Chain Monte Carlo (MCMC)-based random sampling method that that avoids retrieving all of the adjacent nodes for the changed node to select a candidate node from the candidate pool”, these limitations are substantially drawn to mental concepts. The specification reads (underline emphasis added):
"[54]… we come up with getRandomNeighbor, described in Algorithm 2 illustrated in FIG. 4. It is an MCMC method for rapidly sampling nodes from N(u) in an unbiased manner without retrieving the entire N(u)"
If a claim limitation, under its broadest reasonable interpretation, covers mathematical or mental concepts, then it falls within groupings of abstract ideas (2019 PEG Step 2A, Prong One: Abstract Idea Grouping? = Yes).
Independent claim 1, Step 2A Prong two: The claim recites the additional elements an electronic device including a memory and a processor. They are interpreted as drawn to a generic computer.
Independent claim 1 also recites the additional elements "structuring the memory according to a summary graph and a plurality of edge corrections via the processor" and "based on a communication signal received from an external device”. The limitations appear to be just “apply it” limitations, because these claim limitations recite only the idea of a solution or outcome, i.e. the claim fails to recite details of how a solution to a problem is accomplished.
The additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (2019 PEG Step 2A, Prong Two: Additional elements that integrate the Judicial Exception/Abstract idea into a practical application?= NO).
Independent claim 1, Step 2B: As discussed with respect to Step 2A, the claim recites the additional elements an electronic device including a memory and a processor. They are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Their collective functions merely provide conventional computer implementation. See MPEP 2106.05. The implementation on a computing system is described in the specification (underline emphasis added): "[89]… a computer device (e.g., electronic device 100)”. The use of a computer to implement the abstract idea of a mathematical or mental algorithm has not been held by the courts to be enough to qualify as “significantly more”.
As discussed with respect to Step 2A, Prong two, the limitations "structuring the memory according to a summary graph and a plurality of edge corrections via the processor" and "based on a communication signal received from an external device" appear to be just “apply it” limitations, because these claim limitations recite only the idea of a solution or outcome, i.e. these claim limitations fail to recite details of how a solution to a problem is accomplished.
As to the limitations "structuring the memory according to a summary graph and a plurality of edge corrections via the processor", Examiner notes that both the claimed invention and the specification are mute about how the memory is structured. The structuring is not elaborated. The specification reads (underline emphasis added):
' Related Art
[2] A graph is a data structure that represents objects and the connections between them, which may express various and numerous data. Representative examples of the graph include an online social network (connection between users), the World Wide Web (connection between webpages), a purchase history on e- commerce (connection between a customer and a product), a deep learning model (connections between neurons), and so on. With the recent rise of the big data era, large-scale graph data is emerging. For example, the World Wide Web is connecting 5.5 billions of webpages, and a particular social network is connecting 2.4 billions of users.
[3] Such massive data exceeds the capacity of main memory or cache memory of a computer, making analysis difficult. This is because most graph analysis algorithms assume that an entire graph is stored in main memory. A solution to this problem is to compress graph data so that it is stored in main memory…
[18] An electronic device for incremental lossless summarization of a dynamic massive graph and an operating method thereof according to various embodiments may summarize a massive graph according to a lossless graph summarization technique. The lossless graph summarization technique is a technique for compressing a plurality of nodes detected from a massive graph and edges connecting the nodes into a summary graph consisting of at least one supernode and at least one superedge connecting the supernodes and edge corrections representing the differences between the massive graph and the summary graph. A supernode comprises a set containing at least one node, and a superedge is taken from one supernode and inserted, and connects two supernodes, and the presence of a superedge may represent that edges are present between all nodes. Such a lossless graph summarization technique aims to summarize the massive graph, while minimizing the size of the summary graph, especially relative to the number of superedges and the size of the edge corrections. According to the lossless graph summarization technique, the original massive graph may be recovered by using the summary graph and the edge corrections together'.
As to the limitations "based on a communication signal received from an external device", Examiner notes that both the claimed invention and the specification are mute about how the “detecting a changed edge from the dynamic massive graph based on a communication signal received from an external device” is actually done. The basis is not elaborated. The “communication signal received from an external device" is recited at a high level of generality and as performing generic one-way communications functions routinely used in one-way communication applications. The specification reads (underline emphasis added):
“[68] The input module 110 may receive a signal to be used for at least one element of the electronic device 100. The input module 110 may include at least one of an input device configured for a user to give a signal input directly into the electronic device 100, a sensor device configured to detect a change in the surroundings and generate a signal, and a receiving device configured to receive a signal from an external device…
[70]… the receiving device and the transmitting device may be implemented as a communication module. The communication module may perform communication between the electronic device 100 and an external device. The communication module may establish a communication channel between the electronic device 100 and an external device. Here, the external device may include at least one of a satellite, a base station, a server, and another electronic device… the long-range communication module may communicate with an external device through a network. The network may include, for example, at least one of a cellular network, the internet, and a computer network such as LAN (local area network) or WAN (wide area network)”
Thus, taken alone the individual additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the additional elements taken individually. There is no indication that their combination improves the functioning of a computer itself or improves any other technology (underline emphasis added). Therefore, the claim does not amount to significantly more than the abstract idea itself (2019 PEG Step 2B: NO).
Independent claims 8 and 15, Step 2A Prong two and 2B: As to the further additional elements computer device, computer-readable storage medium, processor, and memory, they are interpreted as drawn to a generic computer. (See Independent claim 1, Step 2B above).
Dependent claims, Step 2A, Prong One: Dependent claims limitations further the mental and mathematical concepts of their independent claims. The claims recite "7/14/20… calculating another/the amount of change caused by the updating of the summary graph and the edge corrections based on the creation of the singleton supernode for the testing node…”. These limitations are substantially drawn to mathematical calculations. Also, as described in the specification, "lossless graph summarization" is substantially drawn to mathematical relationships/calculations. (See Independent claim 1, Step 2A, Prong One above). If a claim limitation, under its broadest reasonable interpretation, covers mathematical or mental concepts, then it falls within groupings of abstract ideas (2019 PEG Step 2A, Prong One: Abstract Idea Grouping? = Yes).
Dependent claims, Step 2A Prong Two: dependent claims recite the additional elements "21… wherein the external device is at least one of a satellite, a base station, or a server”, they are recited so generically (no details whatsoever are provided other than "the external device is at least one of a satellite, a base station, or a server ") that they represent no more than just “apply it” limitations. This judicial exception is not integrated into a practical application of the exception (2019 PEG Step 2A, Prong Two: Additional elements that integrate the Judicial exception/Abstract idea into a practical application? = NO).
Dependent claims, Step 2B: As discussed with respect to Step 2A, in the dependent claims, the limitations "21… wherein the external device is at least one of a satellite, a base station, or a server” appear to be just “apply it” limitations, because the limitations invoke computers or other machinery merely as a tool to perform an existing process. See MPEP 2106.05(f). The claims do not provide an inventive concept in Step 2B. Therefore, the claims do not amount to significantly more than the abstract idea itself (2019 PEG Step 2B: NO).
Claims 1, 3, 7, 8, 10, 14-16, and 20-23 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Allowable Subject Matter
Claims 1, 3, 7, 8, 10, 14-16, and 20-23 are allowable over prior art of record. They will be allowed once all outstanding rejections/objections are traversed.
none of the prior art of record taken either alone or in combination discloses
claims 1, 8, and 15, "… constructing a candidate pool with nodes belonging to both the testing pool and the coarse cluster containing the testing node, wherein the candidate pool is formed by intersecting the testing pool with the coarse cluster including the testing node; performing a Markov Chain Monte Carlo (MCMC)-based random sampling method that that avoids retrieving all of the adjacent nodes for the changed node to select a candidate node from the candidate pool; calculating an amount of change caused by the updating of the summary graph and the edge corrections based on movement of the testing node to the supernode of the candidate node, wherein the amount of change is calculated based on an objective function for the summary graph; determining an acceptance probability for the movement based on the calculated amount of change; and maintaining the supernode as the testing node when the movement is accepted based on the acceptance probability and otherwise returning the testing node to an original supernode…",
in combination with the remaining steps, elements, and features of the claimed invention. Also, there is no motivation to combine none of these references to meet these limitations. It is for these reasons that Applicant's invention defines over the prior art of record.
As allowable subject matter has been indicated, Applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Response to Arguments
Regarding the claim objections, some claims remain defective.
Regarding the Claim Rejections - 35 USC § 112, claims remain defective.
Regarding the rejections under 101, Applicant's arguments have been considered, but they are not persuasive. Applicant argues, (see page 13, next to last paragraph to page 14, 2nd paragraph):
‘… claims now recite structuring of a memory according to a summary graph and a plurality of edge corrections. Support for these amendments may be found in at least paragraphs 2, 9 and 18 of the printed publication. This organization of the memory into a unique data structure allows incremental lossless summarization of a dynamic massive graph by summarizing a massive graph according to a lossless graph summarization technique. The lossless graph summarization technique is a technique for compressing a plurality of nodes detected from a massive graph and edges connecting the nodes into a summary graph stored in memory. Thus, the alleged mental and mathematical concepts of claim 1 are integrated into a process that allows for incremental lossless summarization and structuring a memory with a summary of a dynamic massive graph. The summary graph and the updating of the summary graph integrate any alleged abstract idea into a practical application.
The proposed amendments now recite a method to structure memory according to a summary graph and a set of corrected edges as a specialized data structure of nodes, edges and super nodes. This structure and the recited operations solves existing problems of graphs exceeding the capacity of a memory device as explained in paragraphs 2, 3, and 19 of the printed publication. This also increases the speed of summarization of the graph by 10 million times resulting in faster execution of graph-based algorithms such as those used in machine learning as explained in paragraphs 20 and 88 of the printed publication’
MPEP 2106.05 reads (underline emphasis added):
'(f) Mere Instructions To Apply An Exception [R-10.2019]… (3) The particularity or generality of the application of the judicial exception. A claim having broad applicability across many fields of endeavor may not provide meaningful limitations that integrate a judicial exception into a practical application or amount to significantly more. For instance, a claim that generically recites an effect of the judicial exception or claims every mode of accomplishing that effect, amounts to a claim that is merely adding the words "apply it" to the judicial exception'
Examiner's response: Examiner invites Applicant to use the Specification of record in the present Application and not the U.S. Pre–Grant publication. The MPEP reads "2106.05(a) Improvements to the Functioning of a Computer or To Any Other Technology or Technical Field [R-07.2022]… evaluating the specification… if the specification sets forth… described in the specification" and not the U.S. Pre–Grant publication or any other publication.
Applicant's argument is not persuasive, because the limitations "structuring the memory according to a summary graph and a plurality of edge corrections via the processor" appear to be just “apply it” limitations, because these claim limitations recite only the idea of a solution or outcome, i.e. these claim limitations fail to recite details of how a solution to a problem is accomplished. These limitations are so broad that nothing is known about how the claimed "structuring the memory” is performed. There is no combination of additional elements that improves the functioning of a computer itself or improves any other technology. Examiner notes that the claimed invention, the specification, and Applicant's arguments are mute about how the “structuring the memory” is actually done. (See MPEP 2106.05 supra and Independent claim 1, Step 2B above).
Applicant further argues, (see page 14, 3rd paragraph to page 15, next to last paragraph):
‘The claims are a novel structuring of a memory that is improvement over existing technology in the computer field similar to the database claims configuring memory at issue in Enfish…
The claims constitute an improvement in computer technology analogous to the claims in Enfish noted in MPEP 2106.04(d)(1)… Similar to the referential table solving problems with existing database structures, paragraph 3 of the printed publication notes a problem with present graph structures as requiring an excessive amount of memory or even exceeding the entire memory. The claims solve this specific problem to improve computer capabilities and therefore are not merely "applying" a computer.
… It was the specification's discussion of the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility… The claim was not simply the addition of general purpose computers added post-hoc to an abstract idea, but a specific implementation of a solution to a problem in the software arts…
Similar to the structuring of memory in the present claims that result in decreasing memory required for a massive graph, the claims in Enfish improved the computer function by configuring memory allowing a decrease in memory required for the database as explained in MPEP 2106.05(d)(I) "the features were not conventional and thus were considered to reflect an improvement to existing technology. In particular, they enabled the claimed table to achieve benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements. Enfish…’
The MPEP reads (underline emphasis added):
'2106.05(a) Improvements to the Functioning of a Computer or To Any Other Technology or Technical Field [R-07.2022]
In determining patent eligibility, examiners should consider whether the claim "purport(s) to improve the functioning of the computer itself"…
I. IMPROVEMENTS TO COMPUTER FUNCTIONALITY
In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool. Enfish... In Enfish, the court evaluated the patent eligibility of claims related to a self-referential database. Id. The court concluded the claims were not directed to an abstract idea, but rather an improvement to computer functionality. Id. It was the specification’s discussion of the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility…'
Examiner's response: Applicant's argument is not persuasive, because the claimed invention is not directed to subject matter analogous to Enfish, which claims the steps of configuring a computer memory in accordance with a self-referential table invoking 35 U.S.C. § 112(f). Enfish claims are directed to a specific improvement to the way computers operate, while the claimed invention is not. Thus, Applicant’s arguments do not apply to Enfish.
Examiner invites Applicant to elaborate "the specification’s discussion of the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims". Examiner does not see the required specificity. (See MPEP 2106.05(a)(I) supra and Independent claim 1, Step 2B above).
Therefore, the rejections are maintained.
As to claims 24 and 25, they are withdrawn from consideration as being directed to a non-elected invention. (See supra).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUAN CARLOS OCHOA whose telephone number is (571)272-2625. The examiner can normally be reached Mondays, Tuesdays, Thursdays, and Fridays 9:30AM - 7:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emerson Puente can be reached on (571) 272-3652. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JUAN C OCHOA/Primary Examiner, Art Unit 2187
1 Electric Power Group, LLC v. Alstom S.A., 119 USPQ2d 1739 Fed. Cir. 2016