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 papers filed on 11/24/2025.
No claims have been amended.
No claims have been cancelled.
No claims have been added.
Claims 1-20 are pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/24/2025 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
The claims are directed to a process (method as introduced in Claim 1), system (Claim 8), and/or non-transitory computer readable storage medium (Claim 15), thus Claims 1-20 fall within one of the four statutory categories. See MPEP 2106.03.
Step 2A, Prong 1:
The claimed invention recites an abstract idea according to MPEP §2106.04. The independent claims which recite the following claim limitations as an abstract idea, are underlined below.
Claims 1, 8, and 15 recite:
scanning a publisher system of a set of publisher systems to identify a
published merchant listing associated with the publisher system, wherein the published merchant listing comprises a first set of data fields and a first set of data field values associated with a merchant system;
executing a transformation on the first set of data field values, wherein the
transformation comprises decoding the first set of data field values;
following the transformation, comparing, on a field-by-field basis, the
published merchant listing to a target merchant listing comprising a second set of data fields and a second set of data field values associated with the merchant system, wherein the comparing comprises calculating a probability that describes the likelihood of a first data value of a first data field of the published merchant listing transforming into a second data value of a second data field of the target merchant listing based at
least on an optimum path comprising one or more edit types taken to transform the first data value into the second data value, wherein the probability comprises a prior probability and the prior
probability is calculated based on the one or more edit types;
identifying, based on the comparing, a discrepancy between the first data value
and the second data value;
accepting or rejecting the published merchant listing, by the merchant system
based on the discrepancy; and
publishing, in response to rejecting the published merchant listing, the target
merchant listing to the publisher system.
The underlined claim limitations as emphasized above, as drafted, recite a process that, covers the performance of commercial or legal interactions (including advertising, marketing or sales activities or behaviors; or business relations). Other than reciting a computer implementation, nothing in the claim elements precludes the step from encompassing the performance of commercial or legal interactions which represents the abstract idea of certain methods of organizing human activity. But for the recitation of generic implementation of computer system components, the claimed invention merely recites a process for comparing sets of merchant information to determine if they are related to the same merchant, thus facilitating reconciliation of multiple data sets.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application. In particular, the claims recite additional elements such as processing device, publisher system, and memory/computer readable storage medium with executable instructions for performing the above limitations. These additional elements are recited at a high-level of generality (i.e., as a generic processor performing a generic computer functions such as collecting data, transmitting data, analyzing data, storing data, and displaying data, see specification at [0020] and [0075]) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, These claimed additional elements merely recite the words “apply it" (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
Thus, the additional claim elements are not indicative of integration into a practical application, because the claims do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e)). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea and the claims are directed to an abstract idea.
Step 2B:
The claims do not include additional elements, individually or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Dependent Claims:
Claims 2-7, 9-14, and 16-20 recite further elements related to the analysis, scoring, and message improvement steps of the parent claims. These activities fail to differentiate the claims from the related activities in the parent claims and fail to provide any material to render the claimed invention to be significantly more than the identified abstract ideas, as outlined below.
Claims 2, 9, and 16 recite “causing generation of a graphical user interface comprising an indication of the discrepancy”. The graphical user interface used in these steps is recited at a high-level of generality and is recited merely as a tool for displaying data. The claims are directed to the same abstract ideas identified in the independent claims the general use of a graphical user interface to perform the display of an indication does not integrate the abstract idea into a practical application or provide an inventive concept.
Claims 3, 4, 10, 11, and 17 recite “wherein the comparing is performed according to a set of comparison rules comprising a first rule associated with a first field type of the target merchant listing and a second field type of the target merchant listing” which narrows how the abstract idea may be performed but does not make the claim any less abstract.
Claims 5, 12, and 18 recite “identifying the first data field of the first set of data fields of the published merchant listing is the first field type” which narrows how the abstract idea may be performed but does not make the claim any less abstract.
Claims 6, 13, and 19 recite “wherein the first data field of the published merchant listing is compared to the second data field of the target merchant listing in accordance with the first rule” which narrows how the abstract idea may be performed but does not make the claim any less abstract.
Claims 7, 14, and 20 recite “wherein the comparing is performed according to a machine learning process”. The machine learning process used in these steps is recited at a high-level of generality and is recited merely as a tool for performing these steps. The claims are directed to the same abstract ideas identified in the independent claims the general use of a machine learning process to perform the comparing does not integrate the abstract idea into a practical application or provide an inventive concept.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Spehr et al. (Pub. No. US 2011/0029467 A1) in view of Agarwal et al. (EP 3133511 A1) in further view of Wang et al. (US 2003/0225579 A1).
In regards to Claims 1, 8, and 15, Spehr discloses:
A method/system comprising:
a memory [and/or non-transitory computer readable storage medium] to store instructions; and a processing device, operatively coupled to the memory, to execute the instructions to perform operations comprising: ([0027])
scanning, by a processing device, a publisher system of a set of publisher systems to identify a published merchant listing associated with the publisher system, wherein the published merchant listing comprises a first set of data fields and a first set of data field values associated with a merchant system; ([0018]; [0019], data records from various published sources (including, but not limited to, commercial websites that provide published listings, such as review websites), records are periodically received from the sources (comparable to “scanning” the publisher systems/sources to identify records); [0017], entities include merchants; [0021], business records for the multiple data sources are compared, including between fields (see [0032], showing that fields include values); see also Fig. 1; [0003]; [0004], reconciles records to determine if related to the same entity)
executing, by the processing device, a transformation on the first set of data field values, wherein the transformation comprises decoding the first set of data field values; ([0019], the incoming data may be encoded using different types of encoding (“…SOAP, XML, or any of a variety…”); [0020]; [0021]; [0029], pre-processing is applied to clean (normalize, transform) the data to a format that is uniform among the data sets for comparison, the transformation would apply to transforming data from various types of source encoding to a standardized format (decoding); [0041]-[0051], multiple examples of transforming/decoding data to a standardized format (cleaned, normalized), one example includes transforming a phone number field that is encoded as “2065551234” in a source format to the standardized/normalized (decoded) format of “206-555-1234”)
following the cleaning operation, comparing, on a field-by-field basis, the published merchant listing to a target merchant listing comprising a second set of data fields and a second set of data field values associated with the merchant system; ([0004]; [0021], business records for the multiple data sources are compared, including between each field, the multiple records would include a first record and a target record (see [0032], showing that fields include values); [0020]; [0021], as described above, comparing performed after cleaning/normalizing)
identifying, based on the comparing, a discrepancy between the first data value of a first data field and the second data value; ([0004]; [0023], significant differences/discrepancies are identified based on the comparison (as described above, comparisons are made on a field-by-field basis))
accepting or rejecting the published merchant listing, by the merchant system based on the discrepancy; ([0023], based on discrepancies, it is determined whether or not the records are similar enough to be reconciled, not reconciled, discarded, etc., this would be comparable to rejecting or accepting a record based on its comparisons to another record accepting it for reconciliations and/or rejecting it for being too different)
publishing, in response to rejecting the published merchant listing, the target merchant listing to the publisher system (describes at least one situation where a record can be replaced by a different record that is determined to be related to the same entity, see [0024], “…the data from all fields in one business record may be selected over the data in the fields of the other business record.”; [0040], “…detect the similarity between any two business records (i.e., between two new records or between one new record and one existing record) and merge or otherwise utilize the data contained in the records.”, also discusses sources of records (incudes records maintained and not maintained by a facility, includes publisher system))
Spehr discloses the above method/system in which similarities are analyzed between records to determine probabilities and likelihoods of the records pertaining to the same entity. Additionally, Spehr discloses the processing and normalizing of data to determine matching data that originates in different formats (as described above, Spehr compares pairs of records to reconcile and demine if they are the same entity, see also [0021]; [0031], determines level of similarity between records; [0023], determine likelihood/probability that two records refer to same entity; [0030]; [0033], uses matrices and tokenizing of fields; [0041]-[0051], examples of normalizing of data in order to compare the records for similarity, also shows edits that can be applied to data in order to normalize different formats into a standard format for matching, these edits include deletion of words/characters, addition of words/characters, and converting (swapping)).
Spehr does not explicitly disclose calculating a likelihood/probability of transformations between records based on an optimal path, but Agarwal teaches:
wherein the comparing comprises calculating a probability that describes the likelihood of a first data value of a first data field of the published merchant listing transforming into a second data value of a second data field of the target merchant listing based at least on an optimum path comprising one or more edit types taken to transform the first data value into the second data value, (Abstract (57) and throughout reference, drawn to determining that records refer to the same entity; [0050], reconciles pairs of records from different lists to determine if they refer to the same entity (including at least one edit example); [0085], shows the applying of edits in analysis, including deletions, additions, and swapping (“switching”), see also the above description of “cleaning” and “transformations” performed by Spehr; [0115]; [0131]; [0132]; [0134]; [0147], example of pair comparison to determine how closely (likelihood, probability) the records may be related, including how similar or different the records are (percent based on the level of difference); [0157]; [0158], provides examples of comparisons, including a “longest common substring” between the data (which would be related to the number of edits required to transform from one into the other) and uses Levenshtein distance (which is a measurement of edit including insertions, deletions or substitutions)) [The relationship between optimum path and edits of fields is addressed in the “Examiner’s Notes on Interpretation”, provided below. Please see that note for additional detail.]
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Spehr so as to have included wherein the comparing comprises calculating a probability that describes the likelihood of a first data value of a first data field of the published merchant listing transforming into a second data value of a second data field of the target merchant listing based at least on an optimum path comprising one or more edit types taken to transform the first data value into the second data value, as taught by Agarwal in order to process disparate data into useful fields for comparison for determining if the data matches (Agarwal, [0040]; [0050]; Spehr, [0004]; [0041]-[0051], as described above).
Examiner’s Notes on Interpretation: One of ordinary skill in the art would recognize that the percent of difference (including based on the examples provided in the reference) would indicate the amount of editing required to transform one version into the other. Although the reference does not use the term “optimal path”, one of ordinary skill in the art would understand that the least number of edits required (highest percent match) would indicate an optimal path for transformation. For example, using the least number of edits to transform the data fields of a first record into the data fields of a second record would indicate a stronger match, a higher likelihood/probability that the record can be transformed into the other record, and a higher probability that the records are the same entity (in other words, if there are multiple set of edits that can be used, the set with the least number of edits would be optimal for determining a probability of matching and provide stronger proof). See also, Agarwal, [0157]; [0158] (provides examples of comparisons, including a “longest common substring” between the data fields (which would be related to the number of edits required to transform from one into the other) and uses Levenshtein distance (which is also used in Applicant’s specification for similar activities)).
It is also noted that Applicant’s specification does not explicitly define “optimum path”, therefore it is being interpreted under broadest reasonable interpretation. In light of the specification and based on the descriptions for determining the likelihood of transformation (see at least [0048]-[0054] in applicant’s specification), Examiner asserts that the optimum path can be interpreted as determining the optimal (minimum, etc.) number of edits to determine likelihood that records match. It is also noted that, although the references do not include the term “optimal path”, the combination of references describe a comparable method/system as described in Applicant’s specification. Comparable activities include tokenizing data, cleaning of data (edits using deletions, additions, and swapping), determining a score (or percentage) for the likelihood/probability of match based on how similar the strings are (how much editing would be required, including using Levenshtein distance calculations, see notes above), aggregating calculations for multiple tokens using methods such as matrices, etc. The steps described in the specification and the combination of references describe similar processes that would produce similar results that can be interpreted as an optimal path for transformation of one data/record into another data/record.
Spehr/Agarwal discloses the above system/method for comparing words to determine similarity using the above recited comparison methods, including edit types. Spehr/Agarwal does not explicitly disclose wherein the probability comprises a prior probability and the prior probability is calculated based on one or more edit types.
However, Wang teaches wherein the probability comprises a prior probability and the prior probability is calculated based on one or more edit types ([0049], “…the edit score is obtained from the prior probabilities of the edit operations…”, the edit score (probabilistic scoring of edits in regards to correcting language is discussed in Abstract, [0012]; Claim 2; etc.), includes prior probabilities for edit operations (“prior probabilities of the edit operations” ids interpreted as probabilities calculated for those edit operations), multiple types of edit operations are discussed throughout the reference (such as deleting, inserting, substituting, etc.))
It would have been obvious to one of ordinary skill in the art, before to the effective filing date of the claimed invention, to have further modified the system of Spehr/Agarwal so as to have included the probability comprising a prior probability and the prior probability calculated based on one or more edit types, as taught by Wang.
Spehr/Agarwal discloses a “base” method/system for comparing words and phrases to determine the probability that they represent the same words and phrases, as shown above. Wang teaches a comparable method/system for comparing words and language to determine and correct errors based on similarities between the words/language, as shown above. Wang also teaches an embodiment in which the probability comprises a prior probability and the prior probability is calculated based on one or more edit types, as shown above. One of ordinary skill in the art would have recognized the adaptation of the probability comprising a prior probability and the prior probability calculated based on one or more edit types to Spehr/Agarwal could be performed with the technical expertise demonstrated in the applied references. (See KSR [127 S Ct. at 1739] "The combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.")
In regards to Claims 2, 9, and 16, Spehr discloses:
causing generation of a graphical user interface comprising an indication of the discrepancy. ([0023], provides indication that records have discrepancies and should be reconciled; [0054], unreconciled records (discrepancies) can be output; Fig. 6; [0056], business records re output on a graphical user interface for users to reconcile (this output could include the unreconciled records in [0054] that can then be identified by a user as belonging to the same entity despite any indicated discrepancies))
In regards to Claims 3, 4, 10, 11, and 17, Spehr discloses:
wherein the comparing is performed according to a set of comparison rules comprising a first rule associated with a first field type of the target merchant listing and a second field type of the target merchant listing. ([0021], fitness function are associated with multiple fields (which would include first and second fields); [0030], describes fitness functions, comparable to comparison rules; [0031], shows different field types in the records that are compared)
In regards to Claims 5, 12, and 18, Spehr discloses:
identifying the first data field of the first set of data fields of the published merchant listing is the first field type. ([0031], shows different field types in the records that are compared)
In regards to Claims 6, 13, and 19, Spehr discloses:
wherein the first data field of the published merchant listing is compared to the second data field of the target merchant listing in accordance with the first rule. ([0021]; [0030]; [0031], as described in parent claims)
In regards to Claims 7, 14, and 20, Spehr discloses:
wherein the comparing is performed according to a machine learning process. ([0011]-[0015], describes the training of the “facility” and “fitness functions”, the facility and related fitness function represent a machine learning model used to perform the comparison)
Additional Relevant Prior Art Identified but not Relied Upon
Baker, Jr. et al. (US 11,269,841 B1). Discloses determination of matching text, including cleaning/converting the data and using Levenshtein distance calculations (see at least Abstract; column 2, SUMMARY OF THE INVENTION, paragraph 1; column 3, paragraph 3; column 7, paragraph 2; column 10, paragraphs 2-4).
Bhattacharjee et al. (Pub. No. US 2018/0089258A1). Discloses a related system/method as described in the Written Opinion of The ISA (included with the IDS filed on 10/30/2023) (see at least [0311]; [0312]; [0329]; [0475]; [0614]).
Fuchs et al. (Pub. No. US 2007/0260628 A1). Discloses data integration including identifying discrepancies in data (such as address information) between data sources (see at least [0131]).
Godeby et al. (Pub. No. US 2005/0055324 A1). Discloses business data reconciliation for data from different data sources (see at least [0012]).
Guha et al. (CA 3141742 A1). Discloses correlating data from different sources and identifying discrepancies and includes cleaning operations (see at least [009]; [042]; [045]; [131]; [134]-[138]; [146]-[148]; [153]-[156]).
Jagota et al. (US 2020/0250576 A1). Discloses matching of input user data to previous user data to determine matches between data for that user (see at least [0006]; [0086]). See also, Jagota et al. (WO 2020191355 A1).
Johnson et al. (US 11,960,459 B1). Discloses the use of matching and merging customer profiles, including confidence scores, standardizing and normalizing data. Matching data fields, training on prior combinations (see at least Abstract; col 2; col 8, par 1 and 3; col 14, par 4-col 15, par 3; Claim 9).
Li (SG 10201904554T A). Discloses determination of a minimum number of operations and minimum path for transforming one text string into another (see at least [008]; [0044]; [0087]; [00113]).
Musgrove et al. (US 2004/0143600 A1). Discloses the use of prior probability in comparing new product catalog listing to previous products listed in the catalog (see at least [0245]). See also, Musgrove et al. (US 2012/0191719 A1).
Newman et al. (US 11,880,379 B1). Discloses determination of matching text, including normalizing the data and using Levenshtein distance calculations (see at least column 3, paragraph 1; column 4, paragraph 5; column 11, paragraphs 4-6).
Response to Arguments
Applicant’s arguments filed 11/24/2025 have been fully considered but they are not persuasive.
I. Rejection of Claims under 35 U.S.C. §101:
Examiner has reviewed the specification recited by Applicant in regards to Applicant’s remarks regarding sufficient evidence under MPEP §2106.05(a). Examiner still believes this material (or any other material) provides sufficient evidence under MPEP §2106.05(a). As a non-limiting example, [0011] merely asserts that performing verification on merchant listings would be too time consuming or risky for current or previous systems. [0012-0013] merely describes activities performed by the claimed invention and alleges benefits. However, it does not clearly explain or provide evidence to demonstrate how/why the claimed invention improvises over prior systems/methods. For example, there is no explanation regarding prior system and why they could not or would not be able to perform these activities. There is no discussion of the deficiencies of these prior systems (aside from assertions that they are deficient). The specification does not make clear how the alleged improvements are achieved in a meaningful manner beyond the recited abstract ideas. Likewise additional cited paragraphs discuss the operations of the claimed invention, but do not provide sufficient detail regarding how the alleged improvement (to the art or to the technology)is achieved in a meaningful manner. The specification does state the alleged improvements in a conclusory manner, for example, any alleged improvements to stability and accuracy of predictions is not explained but rather just asserted to (see [0049]). It is unclear how/why the use of Levenshtein distance and Bayesian probability would significantly improve stability/accuracy over prior system and why prior system could/would not incorporate them, thus not clearly indicating how the art or computer is improved in this manner.
Applicant fails to explain how/why the claimed invention is similar to or comparable to Example 47.
Some of the above remarks were addressed in previous office action. Please refer to those office action for additional detail (including citations to MPEP 2106.05(a))
II. Rejection of Claims under 35 U.S.C. §112(b):
The rejection has been withdrawn in view of Applicant’s amendments. It is noted that the amendments were made in the claims filed after final (on 10/29/2025) and entered into the record via an Advisory Action (on 11/13/2025).
III. Rejection of Claims under 35 U.S.C. §103:
The Li reference is withdrawn in view of Applicant’s remarks. However, as discussed, the most recent interview and advisory action and updated search and consideration were preformed, resulting in an additional applicable reference being applied.
IV. Additional Remarks:
As discussed in the above rejections, including the “Examiner’s Notes on Interpretation”, Agarwal uses Levenshtein distance (which is a measurement of edit including insertions, deletions or substitutions) which is used in a similar manner as discussed in Applicant’s specification for similar activities.
Additional remarks and resources for prior office actions are provided here for future reference:
Applicant’s argues that “edit types” are not disclosed by Agarwal. However, Agarwal discloses the use of Levenshtein distances. Levenshtein distances includes edits of specific types (insertions, deletions or substitutions). This would be understood by one of ordinary skill in the art before the effective filing date. Examiner is also providing Understanding the Levenshtein Distance Equation for Beginners (published in February of 2019) as additional evidence. It is also noted that Applicant provides the same definition and description of the Levenshtein function and its use in the claimed invention in Applicant’s specification.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAUN D SENSENIG whose telephone number is (571)270-5393. The examiner can normally be reached M-F: 10:00am-4:00pm.
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/S.D.S/Examiner, Art Unit 3629 December 13, 2025
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629