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 action is in response to the response filed 07/09/2026.
Claims 1, 3-4, 7-9, 13, 15-16, 19-21, 25, and 27-33 are pending and have been examined.
Claims 1, 3-4, 7-9, 13, 15-16, 19-21, 25, and 27-33 are rejected.
Information Disclosure Statement
The information disclosure statement (IDS) is submitted on 10/07/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Some of the references on the IDS are not considered and indicated by strikeout.
All the references with strike-out are pixelated and cannot be read.
The reference by author Yuya Ogawa et al. requires an English translation.
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 1-9, 13-21, and 25-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim(s) 1-9, 13-21, and 25 is/are directed to the abstract idea of Mental Process and/or mathematical algorithm. The claim recites comparing records to find two records and two records that are similar. The claim(s) does/do not include additional elements that are sufficient to rise to the level of practical application nor significantly more than the judicial exception because the additional elements do not add meaningful limits to practicing the abstract idea.
Regarding:
Claim 1:
Claim 1 recites, in part, A method for matching information, the method comprising:
Identifying . . . a first center node in a first subgraph and a second center node in a second subgraph; identifying, . . . , groups of neighboring nodes from the first subgraph and the second subgraph by comparing node types, wherein all neighboring nodes in each group of neighboring nodes are of a same node type; identifying, . . . , a best matching node pair in each of at least one group of neighboring nodes to form a set of best matching node pairs by determining shortest neighbor distance, wherein each best matching node pair comprises a first neighboring node from the first subgraph and a second neighboring node from the second subgraph; determining, . . ., whether the first center node and the second center node match using the first center node, the second center node, and the best matching node pair in each group of neighboring nodes; and performing, by the information manager of the computer system, responsive to the determining, at least one duplicate record action including deduplicating, emerging, matching, combining, and correcting; creating, by the information manager of the computer system, a set of clusters from each group of neighboring nodes such that each cluster in the set of clusters has at least one neighboring node from both the first subgraph and the second subgraph; and identifying, by the information manager of the computer system, the best matching cluster node pair in each cluster in the set of clusters to form the set of best matching node pairs, wherein each best matching node pair comprises the first neighboring node from the first subgraph and the second neighboring node from the second subgraph, wherein identifying, by the information manager of the computer system, the best matching node pair in each cluster in the set of clusters comprises: determining . . . neighbor distances for the neighboring nodes being compared in a cluster based on the neighboring nodes being compared, links for the neighboring nodes being compared, and depths for the neighboring nodes being compared; and identifying . . . the best matching node pair for each cluster in the set of clusters as two nodes in the cluster having a shortest neighbor distance to form the set of best matching node pairs for the set of clusters, and wherein the neighbor distances for the neighboring nodes in the cluster based on the neighboring nodes being compared, links for the neighboring nodes being compared, and depths for the neighboring nodes being compared are calculated using one of the following equations: where distance(x,y) is a distance between a node x and a node y in the cluster, depth(x,y) is an average depth of a first depth for the node X and a second depth for the node y, and const is a constant value that is greater than 0 and less than or equal to 1; and
d(x,y) = 1 ((1 - * (1 - distance(link,, linkY)) * constᵈᵉⁿᵗʰ)
where distance(x,y) is the distance between the node x and the node y in the cluster, depth(x,y) is an average depth of the first depth for the node X and the second depth for the node y, and const is the constant value that is greater than 0 and less than or equal to 1.
As explained above, the steps recited above are directed to mental process and mathematical algorithm where records are compared to find similar record pairs. Applicant’s Specification on paragraph 0040 states comparing two records for a person.
The additional elements, taken alone or in combination fail to integrate the judicial exception into a practical application.
The additional element is by an information manager of a computer system which is simply just a high-level recitation of a generic computer similar to stating apply on a computer. MPEP 2106.05(f). Furthermore, the additional elements do not rise to the level of significantly more because the additional elements that are recited at a high generality does not, alone or in combination, improve functioning of a computer or improve technological field.
Independent claims 13 and 25 are similarly rejected as claim 1 above. Claim 13 includes additional element of “information manager of the computer system” and “information management system” which is rejected similarly as “computer system” in claim 1. Claim 25 is also similarly rejected as claim 1 and includes an additional element of “computer program product” and “computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer system to cause the computer to perform a method . . .”. These additional elements are also similarly rejected with “computer system” as generic computer above.
Claims 15-16, 19-21, and 25 are rejected similarly as claims 3-4, 7-9, and 13 and claim 26 similarly with claim 2.
Claims 3-4, 7-9, 15-16, 19-21, and 27-33 are mere further recitation of the abstract idea of mental process and/or mathematical algorithm and do not rise to the level of practical application nor significantly more similar to claims 1, 13 and 25 rejections above. Examiner finds no additional elements that meaningfully limit the judicial exception both individually or as a combination. Congruently, the claims and elements do not rise to the level of significantly more.
As per claim 2 The method of claim 1 further comprising:
creating, [by the informational manager of the computer system], a set of clusters from each group of neighboring nodes such that each cluster in the set of clusters has at least one neighboring nodes from both the first subgraph and the second subgraph; and identifying, [by the informational manager of the computer system], the best matching cluster node pair in each cluster in the set of clusters to form the set of best matching node pairs, wherein each best matching node pair comprises the first neighboring node from the first subgraph and the second neighboring node from the second subgraph. (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
As per claim 3 The method of claim 1, wherein identifying, [by the informational manager of the computer system], groups of neighboring nodes from the first subgraph and the second subgraph, wherein all neighboring nodes in each group of neighboring nodes are of the same node type comprises: placing, [by the informational manager of the computer system], the neighboring nodes from each subgraph into initial groups based on a node type for the neighboring nodes; and selecting, [by the informational manager of the computer system], each initial group in the initial groups that has neighboring nodes from both of the first subgraph of the neighboring nodes and the second subgraph of the neighboring nodes to form the groups of neighboring nodes (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
As per claim 4 The method of claim 2, wherein creating, [by the informational manager of the computer system], the set of clusters from each group of the neighboring nodes such that each cluster in the set of clusters has the neighboring nodes from both the first subgraph and the second subgraph comprises: creating, [by the informational manager of the computer system], candidate clusters within each group of the neighboring nodes in the groups of the neighboring nodes; and selecting, [by the informational manager of the computer system], each cluster in the candidate clusters that has neighboring nodes from both the first subgraph of the neighboring nodes and the second subgraph of the neighboring nodes to form the set of clusters. (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
As per claim 5 The method of claim 2, wherein identifying, [by the informational manager of the computer system], the best matching node pair in each cluster in the set of clusters comprises:
determining, []by the informational manager of the computer system], neighbor distances for the neighboring nodes being compared in a cluster based on the neighboring nodes being compared, links for the neighboring nodes being compared, and depths for the neighboring nodes being compared; and identifying, [by the informational manager of the computer system], the best matching node pair for each cluster in the set of clusters as two nodes in the cluster having a shortest neighbor distance to form the set of best matching node pairs for the set of clusters. (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
As per claim 6 The method of claim 5, wherein the neighbor distances for the neighboring nodes in the cluster based on the neighboring nodes being compared, links for the neighboring nodes being compared, and depths for the neighboring nodes being compared are calculated using one of the following equations: (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
(see formula in claim) where distance(x,y) is a distance between a node x and a node y in the cluster, depth(x,y) is an average depth of a first depth for the node x and a second depth for the node y, and const is a constant value that is greater than O and less than or equal to 1; and (see formula in claim) where distance(x,y) is the distance between the node x and the node y in the cluster, depth(x,y) is an average depth of the first depth for the node x and the second depth for the node y, and const is the constant value that is greater than 0 and less than or equal to 1. (Abstract Idea reciting Mathematical formula.)
As per claim 7 The method of claim 2, wherein determining, by the informational manager of the computer system, whether the first center node and the second center node match using the first center node, the second center node, and the set of best matching node pairs comprises: determining, [by the informational manager of the computer system], an overall distance between the first center node and the second center node using the first center node, the second center node, and the set of best matching node pairs in the set of clusters as follows (Mental process extension of independent claim.:
overall distance (see formula in claim) (Abstract Idea reciting Mathematical formula.)
where distance(CenterNode1, CenterNodez) is a distance between the first center node and the second center node, dH(x,y) is a distance between neighboring node x and neighboring node y in the best matching node pair, and M is a number of node types with a best matching neighboring node pair in the groups; (Abstract Idea reciting Mathematical formula.)
and determining, [by the informational manager of the computer system], whether the first center node and the second center node match based on the overall distance calculated between the first center node and the second center node. (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
As per claim 8 The method of claim 2, wherein determining, by the informational manager of the computer system, whether the first center node and the second center node match using the first center node, the second center node, and the best matching node pair in each group of neighboring nodes comprises: (Mental process extension of independent claim. The additional element of informational manager of the computer system is part of a generic computer as explained above.)
comparing, by the informational manager of the computer system, the first center node and the second center node to determine a set of comparison features for the first center node and the second center node (Mental process extension of independent claim that compares known information.);
determining, by the informational manager of the computer system, distance features from a lowest distance between neighboring nodes in each cluster in the set of clusters; determining, by the informational manager of the computer system, an overall distance between the first center node and the second center node using the set of comparison features and the distance features; and determining, by the informational manager of the computer system, whether the overall distance is within a threshold for the first center node and the second center node to be matching (Mental process extension of independent claim.).
As per claim 9 The method of claim 8, wherein the overall distance between the first center node and the second center node is determined as follows:
overall distance = max(ccv)-(Sum(n,i=0) cv(i))/(Sum(n,i=0) fv(i)) /max(cv) – min(cv); where cv(i) is a coefficient vector, fv(i) is a feature vector comprising the set of comparison features and the distance features, max(cv) is an element in the coefficient vector with a maximum value, min(cv) is the element in the coefficient vector with a minimum value, i is an index value, and n is a number of elements in the feature vector (Abstract idea of Mathematical concept).
Claims 27-33 include further recitation of abstract idea of mathematical concept and mental process as above explained. The claims are rejected because there is no practical application nor finding of significantly more similar to claims above.
Response to Arguments
Applicant’s arguments regarding 103 and 112 rejections are persuasive and the rejections are effectively withdrawn.
Applicant's arguments filed 01/20/2026 have been fully considered but they are not persuasive.
Applicant argues that the various steps found in claims 1, 13, and 25 specifies technological limitations, such as information manager, that cannot be performed in mind of a human.
Further Applicant argues that the “information manager” is not a generic computer. Rather, it is method, machine, or article of manufacture implemented by a computer system.
Examiner respectfully disagrees with Applicant’s arguments.
Firstly, an abstract idea can be performed on a computer. The determination of abstract idea and use of a computer must be determined separately. The steps being performed found in the claims are rejected under 101 as being directed to abstract ideas. The use of an “information manager” that could be a computer is rejected as an “apply it” step consistent with the MPEP and the Supreme’s Court’s decision. (MPEP 2106.05(f)); See Alice Corp., 573 U.S. at 223 (The “mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”); see also McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1312 (Fed. Cir. 2016) (“The abstract idea exception prevents patenting a result where ‘it matters not by what process or machinery the result is accomplished.’” (quoting O Reilly v. Morse, 56 U.S. 62, 113 (1854)); Consistent with Alice, simply performing abstract idea on a generic computer is still an abstract idea. (i.e., the rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim for the “special purpose” of executing the algorithm or software) was also superseded by the Supreme Court’s Bilski and Alice Corp. decisions. Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (“[W]e note that Alappat has been superseded by Bilski, 561 U.S. at 605–06, and Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 110 USPQ2d 1976 (2014)”); Intellectual Ventures I LLC v. Capital One Bank (USA), N.A., 792 F.3d 1363, 1366, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015) (“An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer”).
Secondly, although Applicant points to the specification as evidence of “information manager of the computer system” not being a generic computer, the claims are not so clear. There are no features of a computer system, hardware or software components, that is described in the claims to determine an existence of a specialized computer. Further, Applicant has not supplied any evidence why a generic computer with proper software cannot perform the above generic functions.
As above mentioned, looking at the claims as a whole, there is no limitation together with use of an “information manager of a computer system” that provides improvement to a functioning of a computer or technological field. The generic computer that is recited in the claims are used to simply apply abstract steps meaning the computer is used to provide a simple solution or invoked merely as a tool to perform the process stated in the claims. McRo, Enfish, and DDR Holdings that applicant recites are different in that McRo talks about a process that necessarily requires a machine by providing calculations using a 3D model to interpret facial expressions. Enflish, similarly, claims a data structure that is necessarily implemented in data base design. DDR Holdings include claim limitations that is directly tied to how a web page is displayed by maintaining “look and feel” of a webpage improving how computers display information on a display using a computer browser.
The present application differs in that although a generic computer is recited a human can perform all the steps of clustering, calculating distance between nodes, comparing distances using similarity analysis, etc. All the steps found in the claims have been historically performed by a human using simple calculators. There is no improvement to database schema, continuous calculation of real time data points from monitored sensors, nor how data is displayed using a computer as disclosed by the court cases recited above.
Applicant argues that there are two improvements (Remarks p.21). First, improvement of “determining whether pieces of information 402 match using at least one of less time or less resources as compared to current techniques”. Second, “provide increased accuracy in determining whether a match is present between two pieces of information”.
Firstly, applicant’s argument that “less resources” are used is not rooted in applicant’s disclosure. The argued paragraphs do not analyze how the invention optimizes resources to perform the functions compared to historical use of a generic computer.
Secondly, the argument regarding “less time” is unclear. There is no discussion found in the argued paragraphs that compare how a computer uses the steps to improve time because there is no comparison between the use of computer functions found in the claims and a generic computer. Examiner finds no specific ties to a computer of the abstract steps to find practical application as currently presented. All the steps that applicant argues can be performed by a human without the assistance of a computer such as “deduplicating, merging, matching, combining, and correcting”. (Remarks p.21).
Applicant argues that the invention is specifically tied to a computer technology using “models”. (Remarks p.22). Looking into applicant’s specification, there are only two mentions of learning models. One is used to determine coefficients, but is negated in the same sentence as being able to be performed by a “subject matter expert”. (Specification in publication para. 119). Also, mentions use of “learning model” for clustering. (Specification para.107). Again, this use is negated by stating that known mathematical methods that can be performed by a human can be used. Id.
Therefore, consistent with the MPEP and the decisions made by various courts, Examiner finds that the claims recite abstract steps and statement to “apply it” on an existing and general computer.
Similarly, Examiner finds that there is no improvement by simply reciting mathematical algorithms and as a whole there is nothing in the claims that rises to the level of significantly more similar to the rationale provided above.
Also, note below:
Applicant argues for finding of practical application because the invention improves technological field of best matching pair of neighboring nodes.
Applicant brings up McRo, a lip-syncing invention, Enfish, a database scheme invention, and DDR Holdings, internet search engine to produce manipulated results, to analogize the present invention as incorporating an improvement to a technological field. However, the facts and details of the similarities, other than being in a computer technology, are not provided and no similarities seem to exist that are significant to the facts of the present application. Therefore, merely being within a computer field does not provide evidence of technological improvement further evidenced by the fact that Alice court decided that the database retrieval technique did not recite subject eligible concepts even though it is well based in computer technology.
Applicant argues that practical application should be found for claim 1 due to the step of “the best matching pair in each group of neighboring nodes” providing improvement to computer function. Applicant states that matching large numbers of records is enhanced. Looking into Applicant cited paragraphs 0096-0098, an improvement to a technological field or functioning of a computer is described generally. It describes on paragraph 0098 that making a determination two center nodes made necessarily improves functioning of a computer. This implication seems to be a general statement missing specific reasons why certain aspects of a computer such as hardware functions are improved. The generic statement that less resources are used is also broad and does not specifically describe the necessary information required to make such a determination. The same can be said of the claims. There are general description of matching steps, but it does not specifically show how computer functions are improved and nothing found in the claims to determine that the claimed steps improve the functioning of a computer in some meaningful way.
Applicant argues that the steps of "deduplicating, merging, matching, combining, and correcting" are specific steps that is not simply applied to a generic computer due to the detail found in the claims. Examiner respectfully submits that the position of the Examiner is that the abstract ideas, including the amount of complexity, is simply applied to an existing computer. Therefore, the additional element of computer components do not rise to the level of practical application.
Regarding step 2B, similar to above, there is no finding of significantly more because there is no improvement of technological field nor functioning of a computer. As a whole, and without more, the invention seems to implement general abstract idea onto a generic computer. Although the claim includes software steps and functions, the invention as a whole does not rise to the level of significantly more.
Therefore, 101 rejection is sustained.
Comments
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tantrum et al. (US 20080126523) – Tantrum discloses clustering nodes and using neighbors to determine node pair similarity.
The examiner requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111(c).
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 extension fee 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 date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Taelor Kim whose telephone number is (571) 270-7166. The examiner can normally be reached on Monday-Thursday (11AM-5PM) EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ajay Bhatia can be reached on 571-272-3906. The fax phone number for the organization where this application or proceeding is assigned is 571-270-8166. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TAELOR KIM/Supervisory Patent Examiner, Art Unit 2836
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