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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3 of U.S. Patent No. 12321358 in view of U.S. Patent Application Publication 20210365344 by Bui et. al. (hereafter Bui).
Claim 1:
U.S. Patent 12321358 discloses at claim 1 : “A computing system, comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor;
and a memory device storing executable code that, when executed, causes the at least one processor to:” [col. 45 lines 39-43]
“access, from one or more data storage locations, at least two separate datasets;”[col. 46 lines 32-35]
“perform data analysis on the at least two separate datasets to identify any redundancies, the data analysis including:
comparing at least one first column name of one or more first columns of first data values of a first dataset of the at least two separate datasets with at least one second column name of one or more second columns of second data values of a second dataset of the at least two separate datasets, the comparing including evaluating similarities of the at least one first column name and the at least one second column name;”[col. 45 lines 44-col. 46 line 7; evaluating similarities (col. Evaluating similarities is anticipated by deriving semantic meanings col. 46 lines 5-7 and col. 46 lines 8-10, same meaning) of the at least one first column name and the at least one second column name (cool 46 lines 5-7) ]
determining the at least one first column name has a same meaning as the at least one second column name;[ col. 46 lines 8-10]
transmit one or more electronic communications to one or more computing devices that includes a notification of the likelihood of similarity between the first dataset and the second dataset;
receive, from the one or more computing devices, one or more responses indicating that the first dataset and the second dataset are to be consolidated; and
consolidate, based on the one or more responses, the first dataset and the second dataset thereby saving storage space at one or more storage locations for retaining both the first dataset and the second dataset.
U.S. Patent 12321358 does not explicitly disclose in claim 1:
determining whether statistical information of the first data values and the second data values are replicas; and
deriving semantic logic from the first dataset and the second dataset to interpret importance of retaining both the first dataset and the second dataset, the interpreting including ascertaining a likelihood of similarity between the first dataset and the second dataset;
On the other hand, Bui discloses:
“determining whether statistical information of the first data values and the second data values are replicas; and” [determining whether statistical information (fig. 5 508-510, output value) of the first data values (0056, encoding data included in the particular field of the first dataset, using the particular encoder module, to generate the first encode value) and the second data values (0057, retrieving the previous encode value, which was generated by encoding data included in the second field of the previously analyzed dataset using the particular encoder module.) are replicas (fig. 5 510, first data set matches previously analyzed data set)]
“deriving semantic logic from the first dataset and the second dataset to interpret importance of retaining both the first dataset and the second dataset, the interpreting including ascertaining a likelihood of similarity between the first dataset and the second dataset;” [deriving semantic logic (0016, determine whether a particular data set matches a previously analyzed dataset) from the first dataset and the second dataset (0016, a particular data set ; 0016, previously analyzed dataset) to interpret importance of retaining both the first dataset and the second dataset (0016, techniques may be used to identify and delete redundant datasets to preserve storage space; if they don’t match they are retained; 0024), the interpreting (0016, matching; determining if they match is interpreting) including ascertaining a likelihood of similarity (0014, similarity) between the first dataset and the second dataset (0014, two data sets may be said to match if, when comparing one or more encode values generated based on the two data sets, the one or more corresponding similarity scores satisfy a similarity criterion)]
Both U.S. Patent 12321358 and Bui are directed to systems of comparing two datasets in order to consolidate data. It would have been an obvious variation to a person of ordinary skill in the art to have included the limitations above based on the disclosure of Bui for the purpose of monitoring for matches in order to determine whether to delete or store data from a new dataset (Bui: 0016, 0024).
Claim 2:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the one or more electronic communications indicate the first dataset and the second dataset are likely redundant.”[ wherein the one or more electronic communications (0020, match determination may be provided to a user)indicate the first dataset and the second dataset are likely redundant (0020, match)]
Claim 3:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the consolidating comprises merging the at least two separate datasets.”[ wherein the consolidating comprises merging the at least two separate datasets (0024, store new dataset in one or more of the data stores of system 200)]
Claim 4:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the consolidating comprises deleting at least one of the at least two separate datasets.”[ wherein the consolidating comprises deleting at least one of the at least two separate datasets(0016, delete redundant datasets to preserve storage space)]]
Claim 5:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the data analysis further comprises identifying a percentage of similarity between the first dataset and the second dataset, and the notification indicates the percentage of similarity.” [ wherein the data analysis further comprises identifying a percentage of similarity (0052, the similarity score(s) for those two datasets satisfy a “similarity criterion,”; 0053, percentage of similarity scores ) between the first dataset and the second dataset (0052, for the two datasets under comparison), and the notification indicates (0020, match determination may be provided to a user)the percentage of similarity (0052, match determination module may determine whether two datasets “match” by determining whether the similarity score(s) for those two datasets satisfy a “similarity criterion,”; provided determination indicates percentage of similarity set was met)]
Claim 6:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the data analysis further comprises calculating a checksum of the at least two separate datasets to determine how the at least two separate datasets have changed over time, and wherein the prompt indicates one or more changes identified from determining how the at least two separate datasets have changed over time.” [ wherein the data analysis further comprises calculating a checksum (0029, time intervals, every week, every two weeks every month)of the at least two separate datasets (0029, existing data set; fig. 2 2 216/218) to determine how the at least two separate datasets (0029, existing data set; fig. 2 2 216/218) have changed over time (0029, a given dataset used by the system 200 may vary over time), and wherein the prompt indicates (0020, match determination may be provided to a user) one or more changes identified (0052, comparing a given pair of encode values; 0029, re-calculate encode values 112 )from determining how the at least two separate datasets have changed over time(0029, a given dataset used by the system 200 may vary over time)]
Claim 7:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the executable code, when executed, further causes the at least one processor to perform a data cleaning process on procured data, the data cleaning processing including scouring and auditing data values of the procured data in accordance with predefined rules to correct errors that would render the data values incongruent with the data analysis, the data cleaning facilitating improving accuracy of the data values to be analyzed during the data analysis.” [ wherein the executable code, when executed, further causes the at least one processor (fig. 8) to perform a data cleaning process (0016, techniques may be used to identify and delete redundant datasets to preserve storage space) on procured data (fig. 2 110 dataset / 216, 218 existing data sets), the data cleaning processing including scouring and auditing data values (0016, identify and delete redundant datasets) of the procured data (fig. 2 110 dataset / 216, 218 existing data sets) in accordance with predefined rules to correct errors (0027, corrective actions) that would render the data values incongruent with the data analysis (0027, determines that the new data set matches one or more previously analyzed data sets; corrective actions leave incongruent data (data sets do not match), if there is a match it may be deleted see 0020), the data cleaning facilitating (0016, techniques may be used to identify and delete redundant datasets to preserve storage space) improving accuracy of the data values to be analyzed during the data analysis(0016, match the desired dataset)]
Claim 8:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the data analysis further comprises ascertaining a deviation amount of the first dataset and the second dataset.” [ wherein the data analysis further comprises ascertaining a deviation amount (0052, determine whether two datasets “match” by determining whether the similarity score(s) for those two datasets satisfy a “similarity criterion,” )of the first dataset and the second dataset (0052, two datasets )]
Claim 9:
The combination of U.S. Patent 12321358 and Bui discloses in U.S. Patent 12321358 claim 1: The computing system of claim 1, wherein the data analysis further comprises: ascertaining a first maximum value of the first data values, first mean value of the first data values, and a first range of values of the first data values, a second maximum value of the second data values, a second mean value of the second data values, and a second range of values of the second data values; comparing the first maximum value to the second maximum value, the first mean value to the second mean value, and the first range to the second range; and determining, from the comparing, whether the first dataset and the second dataset are identical. [claim 1 col. 46 lines 8-23]
Claim 10:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the deriving the semantic logic incorporates natural language processing to interpret meaning of words included in the at least two separate datasets, and based thereon determine whether the meaning of the words is the same.” [ wherein the deriving the semantic logic (0016, determine whether a particular data set matches a previously analyzed dataset) incorporates natural language processing (0039, NLP) to interpret meaning of words included in the at least two separate datasets (0039, semantic content of data in new dataset to the semantic content of data in previously analyzed datasets), and based thereon determine whether the meaning of the words is the same (0039 matching dataset detection module to compare the semantic content of data in new dataset to the semantic content of data in previously analyzed datasets)]
Claim 11:
The combination of U.S. Patent 12321358 and Bui discloses in Bui: “The computing system of claim 1, wherein the data analysis includes determining whether one dataset of the first dataset and the second dataset is a subset of another dataset of the first dataset and the second dataset.” [ wherein the data analysis includes determining whether one dataset (0020, new dataset) of the first dataset and the second dataset (0020, new dataset / previously analyzed dataset) is a subset (0020, new dataset is …a subset) of another dataset (0020, previously analyzed dataset) of the first dataset and the second dataset(0020, new data set / previously analyzed dataset)]
Claim 12:
Claim 12 is not patentably distinct in view of U.S. Patent 12321358 claim 1 and Bui similarly discussed in claim 1 above.
Claim 13:
The combination of U.S. Patent 12321358 and Bui discloses in U.S. Patent 12321358 claim 2: “The computing system of claim 12, wherein the transmitting of the one or more electronic communications is based on the likelihood of similarity surpassing a predefined threshold similarity value that indicates the first dataset and the second dataset are sufficiently similar to be redundant. “[claim 2 col. 46 lines 36-40]
Claim 14:
Claim 14 is not patentably distinct in view of U.S. Patent 12321358 claim 1 and Bui similarly discussed in claim 4 above.
Claim 15:
The combination of U.S. Patent 12321358 and Bui discloses in U.S. Patent 12321358 claim 3: “The computing system of claim 12, wherein the consolidating comprises determining whether one dataset of the one or more datasets comprises personally identifiable information that has not been tokenized and based thereon deleting the one dataset with the non- tokenized personally identifiable information.” [claim 3 col. 46 lines 41-46]
Claim 16-20:
Claims 16-20 are not patentably distinct in view of U.S. Patent 12321358 claim 1 and Bui similarly discussed in claims 1-5 above.
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.
Claim 2, 13, and 17 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 the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 13 recites the phrase “sufficiently similar”, the term sufficiently is indefinite.
Claims 2 and 17 recite the phrase “likely redundant”, the term likely is indefinite.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 13-15 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 12 is a method claim; however dependent claims 13-15 are reciting a system claim. Claims 13-15 fail to further limit claim 12. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8, 10-14, and 16-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. 20210365344 by Bui et. al. (hereafter Bui).
Claim 1:
Bui discloses “A computing system, comprising:
at least one processor; a communication interface communicatively coupled to the at least one processor; and a memory device storing executable code that, when executed, causes the at least one processor to:” [fig. 8]
“access, from one or more data storage locations, at least two separate datasets;” [ access, from one or more data storage locations (fig. 2; 0023 data store within or external to system 200), at least two separate datasets (fig. 5 502, first data set; fig. 5 504 previously analyzed data set)]
“perform data analysis on the at least two separate datasets to identify any redundancies, the data analysis including:” [perform data analysis (fig. 5) on the at least two separate datasets (fig. 5 502, first data set; fig. 5 504 previously analyzed data set) to identify any redundancies (fig. 5 504, first data set matches the previously analyzed data set)]
“comparing at least one first column name of one or more first columns of first data values of a first dataset of the at least two separate datasets with at least one second column name of one or more second columns of second data values of a second dataset of the at least two separate datasets, the comparing including evaluating similarities of the at least one first column name and the at least one second column name;” [comparing (fig. 5) at least one first column name (fig. 5, first encode value corresponds to a particular field) of one or more first columns (fig. 5, particular field of the first plurality of fields)of first data values (0056, data included in the particular field of the first dataset)of a first dataset (0056, first dataset) of the at least two separate datasets (fig. 5 502, first data set; fig. 5 504 previously analyzed data set) with at least one second column name (fig. 5 506, previous encode value that corresponds to a second field)of one or more second columns (fig. 5, second field of the second plurality of fields) of second data values (0057, data included in the second field of the previously analyzed dataset) of a second dataset (0057, previously analyzed data set) of the at least two separate datasets(fig. 5 502, first data set; fig. 5 504 previously analyzed data set), the comparing including evaluating (fig. 5) similarities (fig. 5 508, similarity between the first encode value and the previous encode value) of the at least one first column name (fig. 5 508, first encode value) and the at least one second column name (fig. 5 508, previous encode value)]
“determining the at least one first column name has a same meaning as the at least one second column name;”[ determining the at least one first column name(fig. 5, first encode value corresponds to a particular field) has a same meaning (fig. 5 504, match)as the at least one second column name(fig. 5 506, previous encode value that corresponds to a second field)]
“determining whether statistical information of the first data values and the second data values are replicas; and” [determining whether statistical information (fig. 5 508-510, output value) of the first data values (0056, encoding data included in the particular field of the first dataset, using the particular encoder module, to generate the first encode value) and the second data values (0057, retrieving the previous encode value, which was generated by encoding data included in the second field of the previously analyzed dataset using the particular encoder module.) are replicas (fig. 5 510, first data set matches previously analyzed data set)]
“deriving semantic logic from the first dataset and the second dataset to interpret importance of retaining both the first dataset and the second dataset, the interpreting including ascertaining a likelihood of similarity between the first dataset and the second dataset;” [deriving semantic logic (0016, determine whether a particular data set matches a previously analyzed dataset) from the first dataset and the second dataset (0016, a particular data set ; 0016, previously analyzed dataset) to interpret importance of retaining both the first dataset and the second dataset (0016, techniques may be used to identify and delete redundant datasets to preserve storage space; if they don’t match they are retained; 0024), the interpreting (0016, matching; determining if they match is interpreting) including ascertaining a likelihood of similarity (0014, similarity) between the first dataset and the second dataset (0014, two data sets may be said to match if, when comparing one or more encode values generated based on the two data sets, the one or more corresponding similarity scores satisfy a similarity criterion)]
transmit one or more electronic communications to one or more computing devices that includes a notification of the likelihood of similarity between the first dataset and the second dataset; [transmit one or more electronic communications to one or more computing devices that includes a notification of the likelihood of similarity 0020, match determination may be provided to a user)between the first dataset and the second dataset(fig. 4, dataset 110; fig. 4 previously analyzed data set)]
“receive, from the one or more computing devices, one or more responses indicating that the first dataset and the second dataset are to be consolidated; and” [receive, from the one or more computing devices, one or more responses indicating(provided by user; 0053, the number or percentage of similarity scores that must exceed their respective threshold values in order to satisfy a similarity criterion may be provided by a user of the system that is trying to determine whether a new dataset 110 matches any of the previously analyzed datasets.) that the first dataset and the second dataset are to be consolidated(0016, techniques may be used to identify and delete redundant datasets to preserve storage space;)]
“consolidate, based on the one or more responses, the first dataset and the second dataset thereby saving storage space at one or more storage locations for retaining both the first dataset and the second dataset.” [consolidate(0016, techniques may be used to identify and delete redundant datasets to preserve storage space;), based on the one or more responses((provided by user; 0053, the number or percentage of similarity scores that must exceed their respective threshold values in order to satisfy a similarity criterion may be provided by a user of the system that is trying to determine whether a new dataset 110 matches any of the previously analyzed datasets.) , the first dataset and the second dataset thereby saving storage space at one or more storage locations(0016, delete redundant datasets to preserve storage space) for retaining both the first dataset and the second dataset(0024, if it is determined that new dataset does not match any of the previously analyzed data sets, data publisher may store the new dataset in one or more of the data stores in the system 200)]
Claim 2:
Bui discloses “The computing system of claim 1, wherein the one or more electronic communications indicate the first dataset and the second dataset are likely redundant.”[ wherein the one or more electronic communications (0020, match determination may be provided to a user)indicate the first dataset and the second dataset are likely redundant (0020, match)]
Claim 3:
Bui discloses “The computing system of claim 1, wherein the consolidating comprises merging the at least two separate datasets.”[ wherein the consolidating comprises merging the at least two separate datasets (0024, store new dataset in one or more of the data stores of system 200)]
Claim 4:
Bui discloses “The computing system of claim 1, wherein the consolidating comprises deleting at least one of the at least two separate datasets.”[ wherein the consolidating comprises deleting at least one of the at least two separate datasets(0016, delete redundant datasets to preserve storage space)]]
Claim 5:
Bui discloses “The computing system of claim 1, wherein the data analysis further comprises identifying a percentage of similarity between the first dataset and the second dataset, and the notification indicates the percentage of similarity.” [ wherein the data analysis further comprises identifying a percentage of similarity (0052, the similarity score(s) for those two datasets satisfy a “similarity criterion,”; 0053, percentage of similarity scores ) between the first dataset and the second dataset (0052, for the two datasets under comparison), and the notification indicates (0020, match determination may be provided to a user)the percentage of similarity (0052, match determination module may determine whether two datasets “match” by determining whether the similarity score(s) for those two datasets satisfy a “similarity criterion,”; provided determination indicates percentage of similarity set was met)]
Claim 6:
Bui discloses “The computing system of claim 1, wherein the data analysis further comprises calculating a checksum of the at least two separate datasets to determine how the at least two separate datasets have changed over time, and wherein the prompt indicates one or more changes identified from determining how the at least two separate datasets have changed over time.” [ wherein the data analysis further comprises calculating a checksum (0029, time intervals, every week, every two weeks every month)of the at least two separate datasets (0029, existing data set; fig. 2 2 216/218) to determine how the at least two separate datasets (0029, existing data set; fig. 2 2 216/218) have changed over time (0029, a given dataset used by the system 200 may vary over time), and wherein the prompt indicates (0020, match determination may be provided to a user) one or more changes identified (0052, comparing a given pair of encode values; 0029, re-calculate encode values 112 )from determining how the at least two separate datasets have changed over time(0029, a given dataset used by the system 200 may vary over time)]
Claim 7:
Bui discloses “The computing system of claim 1, wherein the executable code, when executed, further causes the at least one processor to perform a data cleaning process on procured data, the data cleaning processing including scouring and auditing data values of the procured data in accordance with predefined rules to correct errors that would render the data values incongruent with the data analysis, the data cleaning facilitating improving accuracy of the data values to be analyzed during the data analysis.” [ wherein the executable code, when executed, further causes the at least one processor (fig. 8) to perform a data cleaning process (0016, techniques may be used to identify and delete redundant datasets to preserve storage space) on procured data (fig. 2 110 dataset / 216, 218 existing data sets), the data cleaning processing including scouring and auditing data values (0016, identify and delete redundant datasets) of the procured data (fig. 2 110 dataset / 216, 218 existing data sets) in accordance with predefined rules to correct errors (0027, corrective actions) that would render the data values incongruent with the data analysis (0027, determines that the new data set matches one or more previously analyzed data sets; corrective actions leave incongruent data (data sets do not match), if there is a match it may be deleted see 0020), the data cleaning facilitating (0016, techniques may be used to identify and delete redundant datasets to preserve storage space) improving accuracy of the data values to be analyzed during the data analysis(0016, match the desired dataset)]
Claim 8:
Bui discloses “The computing system of claim 1, wherein the data analysis further comprises ascertaining a deviation amount of the first dataset and the second dataset.” [ wherein the data analysis further comprises ascertaining a deviation amount (0052, determine whether two datasets “match” by determining whether the similarity score(s) for those two datasets satisfy a “similarity criterion,” )of the first dataset and the second dataset (0052, two datasets )]
Claim 10:
Bui discloses “The computing system of claim 1, wherein the deriving the semantic logic incorporates natural language processing to interpret meaning of words included in the at least two separate datasets, and based thereon determine whether the meaning of the words is the same.” [ wherein the deriving the semantic logic (0016, determine whether a particular data set matches a previously analyzed dataset) incorporates natural language processing (0039, NLP) to interpret meaning of words included in the at least two separate datasets (0039, semantic content of data in new dataset to the semantic content of data in previously analyzed datasets), and based thereon determine whether the meaning of the words is the same (0039 matching dataset detection module to compare the semantic content of data in new dataset to the semantic content of data in previously analyzed datasets)]
Claim 11:
Bui discloses “The computing system of claim 1, wherein the data analysis includes determining whether one dataset of the first dataset and the second dataset is a subset of another dataset of the first dataset and the second dataset.” [ wherein the data analysis includes determining whether one dataset (0020, new dataset) of the first dataset and the second dataset (0020, new dataset / previously analyzed dataset) is a subset (0020, new dataset is …a subset) of another dataset (0020, previously analyzed dataset) of the first dataset and the second dataset(0020, new data set / previously analyzed dataset)]
Claim 12:
Claims 12 recite similar limitations as that of claim 1 except they it is directed to a method instead of a computer system. Claim 12 is rejected under similar rationale as that of claim 1.
Claim 13:
Bui discloses “The computing system of claim 12, wherein the transmitting of the one or more electronic communications is based on the likelihood of similarity surpassing a predefined threshold similarity value that indicates the first dataset and the second dataset are sufficiently similar to be redundant. “ [wherein the transmitting of the one or more electronic communications(0020, match determination may be provided to a user) is based on the likelihood of similarity surpassing a predefined threshold similarity value (0053, threshold values) that indicates the first dataset and the second dataset (0053 two datasets under comparison) are sufficiently similar to be redundant (0053, similarity criterion)]
Claim 14:
Bui discloses “The computing system of claim 12, wherein the consolidating comprises deleting a dataset of the at least two separate datasets.” [, wherein the consolidating comprises deleting a dataset of the at least two separate datasets (0016, identify and delete redundant datasets to preserve storage space within the various data stores)]
Claim 16-20:
Claims 16-20 recite similar limitations as that of claims 1-5 except they aredirected to a non-transitory computer-readable storage medium instead of a computer system. Claims 16-20 are rejected under similar rationale as that of claims 1-5.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL PHAM whose telephone number is (571)272-3924. The examiner can normally be reached M-F 11-730pm Eastern.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kavita Stanley can be reached at 571-272-8352. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL PHAM/Primary Examiner, Art Unit 2153