DETAILED ACTION
This Office action has been issued in response to amendment filed August 26, 2025.
Claims 1, 7, 9, 15, 16 and 19 have been amended. Claims 4, 8, 12 and 20 have been canceled. Currently, claims 1-3, 5-7, 9-11 and 13-19 are pending. Applicant’s arguments are carefully and respectfully considered and some are persuasive, while others are not. Accordingly, rejections have been removed where arguments were persuasive, but rejections have been maintained where arguments were not persuasive. Also, a new rejections based on the newly added amendments have been set forth. Accordingly, claims 1-3, 5-7, 9-11 and 13-19 are rejected and this action has been made FINAL, as necessitated by amendment.
Response to Arguments
Applicant’s remarks and arguments directed to 35 USC 103 rejection, presented on 08/26/25 have been fully considered. The amended claims changed the scope of the claimed invention. The remarks and arguments are moot in view of the new ground of rejection presented in this office action.
Objection
Claims 1-3, 5-7, 9-11 and 13-19 are objected for the following reasons:
In claims 1, 9 and 16 recited the limitations of “applying a frequentist inference 1 – (the number of relevant documents in the database/the total number of documents in the database)”. It is unclear why the claims have number “1”. There is not number “2” or any other number recited in the claims. Further, the claim recited limitations in a parenthesis is ambiguous. The limitations within the parenthesis are not given weight and does not distinguish from the prior art of record. Applicant is require to delete or rewrite these limitations from the claims.
Dependent claims are objected for incorporating the same deficiencies of their respective base claims.
Claim Rejections- 35 USC § 103
5. 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 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.
6. Claims 1-3, 5-7, 9-11 and 13-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Denninghoff et al. (US 2014/0164352 A1), hereinafter Denninghoff in view of Singh et al. (US 2004/0049517 A1), hereinafter Singh.
As for claim 1, Denninghoff teaches an evaluation method for estimating….for technology assisted review (TAR) workflows, the method comprising: a. assigning a unique key to each document of a total number of documents in a database for an evaluation, wherein the database comprises a number of relevant documents and non-relevant documents (see [0003], e.g., a user can type an arbitrary string, or copy an arbitrary string, into a "find" box of a browser and then search for that string. Search for additional instances in that same document. Find instances of that content in other documents. [0077], e.g., a distinct identifier that is computer readable. Sequences of symbols may represent sequences of any set, such as characters from a language script or set of scripts, [0706], e.g., two or more documents are measures, [0806], e.g., technology discloses as a form of or application of deduplication, rolling has function);
b. generating a random permutation of the database; c. accessing a set of coding decisions associated with one or more documents of the database; d. determining a longest prefix of the random permutation of the database for which corresponding documents have a coding decision (see [0106], e.g., the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0120], e.g., an array of code units, the length n of a match string, the value of the rolling hash function <DistHash> over the n-length match string, the number of high order hash bits used <bitCount>, and optionally the match string itself, [0290], e.g., many permutations whereby functionality illustrated in the Figures is performed by different devices and embodiments also have many combinations of functionality, [0892], e.g., script based redirection from the scripts of the URI Service document from which the user expressed his decision, [0186], e.g., the prefix and suffix are extended until they are either unique or the end of the canonical form is reached);
e. calculating a number of documents where the coding decision is defined as relevant; and f. executing a confidence sequence generating…..comprising: i. determining a set of confidence intervals on an estimated population under……from a finite population; ii. truncating the set of confidence intervals to be consistent with the number of documents that are relevant documents and where the coding decision is defined as relevant; and iii. applying a frequentist interference 1- (the number of relevant documents in the data database/the total number of documents in the database) (see [0106], e.g., the context on each side of the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0126], e.g., a decision to rely only on the hash can be based on easily meeting any required level of confidence; the probability of error drops exponentially as the number of bits in the hash increases, [0878], e.g., indexing the URI plus the minimum time interval for re-indexing the URI, which is computed (for part of the computation) the MIIE and access statistics for the URI, [0183], individual ranges in fragment identifiers that are created using `alt` attributes are identified, [0187], the prefix, target, and suffix would be the same but the value of the right offset 588 would be 1 instead of 0. If the selection included the space before the selected "For", then the value of the left offset 587 would be -1 instead of 0 (e.g., these features describing a range where the true value is likely to fall which is confidence intervals), [0268], e.g., the longest range is truncated until the configured maximum limit (again by default 4000) of characters is achieved. Whole terms (words) are eliminated instead of single characters, [0634], e.g., set is populated with a single string, having the same length as the segment, using a code unit length character that appears nowhere in the canonical form, [0857], e.g., statistics are used to help decide when and how often to re-index a URI, frequency statistics are affected by the passage of time even if an event does not occur (in which case the average frequency tends to be falling, retrieval procedure is executed).
Denninghoff teaches the claimed invention including the limitations of technology assisted review (TAR) workflows, a confidence sequence generating, determining a set of confidence intervals on an estimated population under, from a finite population ([0183], [0187], [0634]). Denninghoff does not explicitly teach the limitations of recall for technology assisted review (TAR); generating algorithm; nested sequential simple random samples without replacement (SRSWORs). Although, Denninghoff teaches URI fragment identifiers is reviewed; Matching algorithms across the document to find any matches. Perform an accurate determination for measuring ([0084], [0115], [0888]). However, in the same field of endeavor, Singh teaches the limitations of recall for technology assisted review (TAR) workflows; generating algorithm; nested sequential simple random samples without replacement (SRSWORs) (see Singh, [0088], if the record is substituted, and is taken as inversely proportional to the substitution rate if the record is not substituted. This choice is reasonable since with more substitution (e.g., obtaining proportion of relevant record which is a recall),. [0115], e.g., resulting subsample can be viewed as a (within PSU) nested two-phase sample, [0136], e.g., clustering algorithms can be used, [0048], e.g., statistical information obtained from databases, [0097], e.g., a simple random sample without replacement).
Denninghoff and Singh both references teach features that are directed to analogous art and they are from the same field of endeavor, such as analyzing document, text, file or record in a distributed databases. Obtaining statistical measurement for the data records.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Singh’s teaching to Denninghoff 's system for a protection sought against inside intruders who know the target's presence in the database. Thus, also protects against outside intruders who do not know the target's presence in the database. Employing a conservative goal of protecting against known database uniques, which is feasible to objectively quantify the protection of data utility and confidentiality (see Singh, [0039]).
As for claim 9, Denninghoff teaches an evaluation method for estimating…for technology-assisted review (TAR) workflows, the method comprising: a. assigning a unique key to each document of a total number of documents in a database, for an evaluation, wherein the database comprises a number of relevant documents and non-relevant documents; b. generating a random permutation of the database (see [0003], e.g., a user can type an arbitrary string, or copy an arbitrary string, into a "find" box of a browser and then search for that string. Search for additional instances in that same document. Find instances of that content in other documents. [0077], e.g., a distinct identifier that is computer readable. Sequences of symbols may represent sequences of any set, such as characters from a language script or set of scripts, [0806]);
c. estimating….for technology assisted review (TAR) workflows at a first point in time; d. receiving notification of an insertion or deletion to the database at a second point in time; e. accessing a set of coding decisions associated with one or more documents of the database after the second point in time; f. determining, after the second point in time, a longest prefix of the random permutation of the database for which corresponding documents have a coding decision (see [0106], e.g., the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0120], e.g., an array of code units, the length n of a match string, the value of the rolling hash function <DistHash> over the n-length match string, the number of high order hash bits used <bitCount>, and optionally the match string itself, [0290], e.g., many permutations whereby functionality illustrated in the Figures is performed by different devices and embodiments also have many combinations of functionality, [0892], e.g., script based redirection from the scripts of the URI Service document from which the user expressed his decision, [0279], e.g., time stamp to the current time. Verify a perfectly matching association between the new fragment identifier and the common document object model form and persist that association);
g. calculating, after the second point in time, a number of documents where the coding decision is defined as relevant; h. executing, after the second point in time, a confidence sequence generating….comprising: i. determining a set of confidence intervals on an estimated population under……from a finite population; ii. truncating the set of confidence intervals to be consistent with the number of documents that are relevant documents and where the coding decision is defined as relevant; and iii. applying a frequentist interference 1- (the number of relevant documents in the data database/the total number of documents in the database) (see [0106], e.g., the context on each side of the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0126], e.g., a decision to rely only on the hash can be based on easily meeting any required level of confidence; the probability of error drops exponentially as the number of bits in the hash increases, [0878], e.g., indexing the URI plus the minimum time interval for re-indexing the URI, which is computed (for part of the computation) the MIIE and access statistics for the URI, [0183], [0187], [0268], [0634], [0857]).
Denninghoff teaches the claimed invention including the limitations of estimating for technology-assisted review (TAR) workflows, a confidence sequence generating, determining a set of confidence intervals on an estimated population under, from a finite population ([0183], [0187], [0634]). Denninghoff does not explicitly teach the limitations of recall for technology assisted review (TAR); generating algorithm; nested sequential simple random samples without replacement (SRSWORs). Although, Denninghoff teaches URI fragment identifiers is reviewed; Matching algorithms across the document to find any matches. Perform an accurate determination for measuring ([0084], [0115], [0888]). However, in the same field of endeavor, Singh teaches the limitations of recall for technology assisted review (TAR) workflows; generating algorithm; nested sequential simple random samples without replacement (SRSWORs) (see Singh, [0088], if the record is substituted, and is taken as inversely proportional to the substitution rate if the record is not substituted. This choice is reasonable since with more substitution (e.g., obtaining proportion of relevant record which is a recall),. [0115], e.g., resulting subsample can be viewed as a (within PSU) nested two-phase sample, [0136], e.g., clustering algorithms can be used, [0048], e.g., statistical information obtained from databases, [0097], e.g., a simple random sample without replacement).
Denninghoff and Singh both references teach features that are directed to analogous art and they are from the same field of endeavor, such as analyzing document, text, file or record in a distributed databases. Obtaining statistical measurement for the data records.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Singh’s teaching to Denninghoff 's system for a protection sought against inside intruders who know the target's presence in the database. Thus, also protects against outside intruders who do not know the target's presence in the database. Employing a conservative goal of protecting against known database uniques, which is feasible to objectively quantify the protection of data utility and confidentiality (see Singh, [0039]).
As for claim 16, Denninghoff teaches an evaluation method for estimating…for technology-assisted review (TAR) workflows, the method comprising: a. providing an arbitrary seed that remains constant for the evaluation; b. producing, using the arbitrary seed, a unique permanent random number (PRN) associated with each document of a total number of documents in a database, wherein the database comprises a number of relevant documents and non-relevant documents (see [0003], e.g., a user can type an arbitrary string, or copy an arbitrary string, into a "find" box of a browser and then search for that string. Search for additional instances in that same document. Find instances of that content in other documents. [0077], e.g., a distinct identifier that is computer readable. Sequences of symbols may represent sequences of any set, such as characters from a language script or set of scripts);
c. generating a random permutation of the database; d. accessing a set of coding decisions associated with one or more documents of the database; e. determining a longest prefix of the random permutation of the database for which corresponding documents have a coding decision (see [0106], e.g., the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0120], e.g., an array of code units, the length n of a match string, the value of the rolling hash function <DistHash> over the n-length match string, the number of high order hash bits used <bitCount>, and optionally the match string itself, [0290], e.g., many permutations whereby functionality illustrated in the Figures is performed by different devices and embodiments also have many combinations of functionality, [0892], e.g., script based redirection from the scripts of the URI Service document from which the user expressed his decision);
f. calculating a number of documents where the coding decision is defined as relevant; and g. executing a confidence sequence generating……comprising: i. determining a set of confidence intervals an estimated population under……from a finite population; ii. truncating the set of confidence intervals to be consistent with the number of documents that are relevant documents and where the coding decision is defined as relevant; and iii. applying a frequentist interference 1- (the number of relevant documents in the data database/the total number of documents in the database) (see [0106], e.g., the context on each side of the target string equally by one character at a time until the whole of the string is unique in the document; in other words until the prefix, targeted fragment, [0126], e.g., a decision to rely only on the hash can be based on easily meeting any required level of confidence; the probability of error drops exponentially as the number of bits in the hash increases, [0878], e.g., indexing the URI plus the minimum time interval for re-indexing the URI, which is computed (for part of the computation) the MIIE and access statistics for the URI, [0183], [0187], [0268], [0634], [0857]).
Denninghoff teaches the claimed invention including the limitations of estimating for technology-assisted review (TAR) workflows, a confidence sequence generating, determining a set of confidence intervals on an estimated population under, from a finite population ([0183], [0187], [0634]). Denninghoff does not explicitly teach the limitations of recall for technology assisted review (TAR); generating algorithm; nested sequential simple random samples without replacement (SRSWORs). Although, Denninghoff teaches URI fragment identifiers is reviewed; Matching algorithms across the document to find any matches. Perform an accurate determination for measuring ([0084], [0115], [0888]). However, in the same field of endeavor, Singh teaches the limitations of recall for technology assisted review (TAR) workflows; generating algorithm; nested sequential simple random samples without replacement (SRSWORs) (see Singh, [0088], if the record is substituted, and is taken as inversely proportional to the substitution rate if the record is not substituted. This choice is reasonable since with more substitution (e.g., obtaining proportion of relevant record which is a recall),. [0115], e.g., resulting subsample can be viewed as a (within PSU) nested two-phase sample, [0136], e.g., clustering algorithms can be used, [0048], e.g., statistical information obtained from databases, [0097], e.g., a simple random sample without replacement).
Denninghoff and Singh both references teach features that are directed to analogous art and they are from the same field of endeavor, such as analyzing document, text, file or record in a distributed databases. Obtaining statistical measurement for the data records.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Singh’s teaching to Denninghoff 's system for a protection sought against inside intruders who know the target's presence in the database. Thus, also protects against outside intruders who do not know the target's presence in the database. Employing a conservative goal of protecting against known database uniques, which is feasible to objectively quantify the protection of data utility and confidentiality (see Singh, [0039]).
As to claim 2, this claim is rejected based on the same reason as above to reject the claim above and are similarly rejected including the following:
Denninghoff and Singh teach:
wherein assigning the unique key to each document of the database comprises providing an arbitrary seed that remains constant for the evaluation and that is used to generate the unique key (see Denninghoff, [0078]).
As to claim 3, this claim is rejected based on the same reason as above to reject the claim above and are similarly rejected including the following:
Denninghoff and Singh teach:
wherein assigning the unique key to each document of the database further comprises producing, using the arbitrary seed, a unique permanent random number (PRN) associated with each document of the database (see Denninghoff, [0131], [0158]).
As to claim 5, this claim is rejected based on the same reason as above to reject the claim above and are similarly rejected including the following:
Denninghoff and Singh teach:
further comprising accessing a “working prior” value that remains constant during the evaluation (see Denninghoff, [0153]).
As to claim 6, this claim is rejected based on the same reason as above to reject the claim above and are similarly rejected including the following:
Denninghoff and Singh teach:
further comprising requesting a “working prior” value (see Denninghoff, [0126]).
As to claim 7, this claim is rejected based on the same reason as above to reject the claim above and are similarly rejected including the following:
Denninghoff and Singh teach:
further comprising dropping, from the set of confidence intervals, values that are inconsistent with the number of documents where the coding decision is defined as relevant (see Denninghoff, [0066]).
Claims 10, 11 and 13-15 correspond in scope to claims 2, 3 and 5-7 and are similarly rejected.
Claims 5-7 correspond in scope to claims 4-8 and are similarly rejected.
Prior Arts
7. US 2018/0307857 A1 teaches replacement value is a SHA-256 hash (i.e., an output of a hash function) of a Docuchain insert. The input to the hash function may include (e.g., as an appended suffix or prefix, or a position designated by header) both the value to be replaced and an identifier of an entity controlling the table, e.g., a tenant identifier in multi-tenant software-as-a-service architectures (see [0031]).
US 20210157830 A1 segment content of a document into a plurality of content segments and store the plurality of content segments within a data structure, the data structure including storage blocks having storage portions and buffer portions, and the storage of the plurality of content segments including storage of content segments within a storage portion of the storage blocks of the data structure. The processor may be also configured to, responsive to at least one change to the content of the document, store the at least one change to the content utilizing a buffer portion of at least one storage block ([0011]).
Lewis et al., Certifying One-Phase Technology-Assisted Reviews. ACM 2021, teaches iterative training of text classifier by active learning which is then used to select a subset of a collection for review. Review of documents is done in training phase and review phase (section 1).
Also see, US 20080120129, US 20090248430, US 20190318117, US 10614797, US 20200012622, US 20180067728, US 20140164352, US 20160139893, US 11347878, US 9864584, US 11568423, US 11212107, US 20220253871, US 20190288850, US 20220318417, US 20090271424, US 10936744, US 8001136 these reference also read the claim recited limitation. These references are state of the art at the time of the claimed invention.
Conclusion
13. The examiner suggests, in response to this Office action, support being 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 because:
a. 37 C.F.R. § 1.75(d)(1) requires antecedent basis in the Specification or original disclosure for any new language, including terms and phrases, added to the claims;
and because:
b. 37 C.F.R. § 1.83(a) requires the Drawings to illustrate or show all claimed features.
Applicant must clearly point out the patentable novelty that they think the claims present, in view of the state of the art disclosed by the references cited or the objections made, and must also explain how the amendments avoid the references or objections. See 37 C.F.R. § 1.111(c).
The examiner has cited particular columns and line numbers in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider each of the cited references in entirety
as potentially teaching all or part of the claimed invention, as well as the context of the passage disclosed by the examiner.
14. The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action (see MPEP § 7.96).
Contact Information
15. Any inquiry concerning this communication or earlier communication from the examiner should be directed to Daniel A Kuddus whose telephone number is (571) 270-1722. The examiner can normally be reached on Monday to Thursday 8.00 a.m.-5.30 p.m. The examiner can also be reached on alternate Fridays from 8.00 a.m. to 4.30 p.m.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor Boris Gorney can be reached on (571) 270-5626. The fax phone number for the organization where this application or processing is assigned is 571-273-8300. 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 the 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.
/DANIEL A KUDDUS/Primary Examiner, Art Unit 2154
11/06/25