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 .
This action is in response to the amendment filed 12 June 2025. Claim 1 and 16 have been amended. Claims 2-6, 8-11, 17-20 have been canceled. Claims 1, 7, 12-16 are pending and have been considered below.
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, 7, 12-16 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Is Claim 1 a statutory category of invention? Claim 1 is directed to an eclectic classifier including an input module and other modules. Claim 1 appears to be directed to a system, therefore Claim 1 is directed to a statutory category of invention.
Does Claim 1 include a judicial exception, such as an abstract idea? Claim 1 is directed to developing classifiers for sample data and sample data is assigned to buckets.
Does the judicial exception fall within one of the abstract idea groupings? The abstract idea is not meaningful different from the judicial exception found by the courts to be abstract (See: Collecting information, analyzing it, and outputting [displaying] certain results of the collection and analysis - Electric Power Group).
Are there additional elements beyond the judicial exception? Additional elements in the claim include an input module, a classifier combination module, a bucket creation module, a membership assignment module, and an output module.
Do the additional elements individually or in combination with the claim as a whole integrate the judicial exception into a practical application? This judicial exception is not integrated into a practical application. The courts have recognized various implementations as integrating abstract ideas into a practical application. For example, if the overall claim limitations including the judicial exception improve the functioning of a computer or other technology or technical field, or if implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture is integral to the claim, or if the overall claim limitations including the judicial exception effect a transformation or reduction of a particular article to a different state or thing, then the courts have recognized that the judicial exception is integrated into a practical application. However, the judicial exception in the claim merely classifies and assigns data to memberships, but does not improve a computer, another technology or other technical field, is not implemented with or in conjunction with a machine or manufacture that is integral to the claim, or does not effect a transformation or reduction of a particular article to a different state or thing. Therefore, the judicial exception is not integrated into a practical application.
Does the claim provide an inventive concept, i.e. does the claim recite additional elements or a combination of elements that amount to significantly more than the judicial exception? The additional elements included in Claim 1 are not sufficient to amount to significantly more than the judicial exception. The additional elements of the recited modules do not add significantly more because they merely recite one or more generic algorithms that do not meaningfully limit the claim.
The applicant has amended Claims 1 and 16 with limitations directed to an input module is a hardware device comprising a physical phenomena detector or a data receiver, and the sample data (x) is digital data received from the hardware device. While these limitations requires the input data is provided from a source that cannot be generated by a human, the overall claimed invention in Claim 1 and 16 must process the data so as to improve a computer, another technology, or other technical field. To accomplish this, for example, the claims could include a processing step such that the eclectic classifier improves a computer, another technology, or other technical field.
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Claim 1 is therefore not drawn to eligible subject matter as it is directed to an abstract idea without significantly more.
Claim 16 is drawn to a method, which falls within one of the statutory categories of invention.
Under analysis similar to that of Claim 1, independent Claim 16 recites limitations that describe the abstract idea of “Collecting information, analyzing it, and outputting [displaying] certain results of the collection and analysis” capable of being performed by the human mind without reciting elements which, individually or collectively, amount to significantly more than the abstract idea, or without being integrated into a practical application. Therefore, independent Claim 16 is rejected under similar rationale as set forth above.
Claims 7 and 12-15 do not include elements that amount to significantly more than the abstract idea, and do not integrate the abstract idea into a practical application, because all of the elements in those claims merely add extra-solution activity to the abstract idea.
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(s) 1 and 16 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.
Referring to applicant’s Claim 1, an eclectic classifier comprises a hardware input module configured to receive digital sample data (x) from a physical phenomenon. The data from the input module comprises a collection of data (Ω) including a training set (Ωtr) and/or a test set (Ωtt) and sample data from m memberships or data categories. A classifier combination module develops k classifiers that are trained on the training data. The k classifiers are combined to from a vector function V(x), and the outcome of V(x) is denoted by a k-dimensional vector, I. It is important to note that the V(x) operates on the whole set of sample data (x), therefore the k-dimensional vector I, represents the whole set of sample data (x)
A bucket creation module B(I), operates on the vector I, which is a function of the sample set (x), to partition the training set (Ωtr) into a disjoint union of subsets, called buckets. Empty buckets and/or small buckets are merged into large buckets according to their cardinalities.
Here, the claim states that each bucket (B(I)) has respective identities (I) associated with the characteristics of the data. However, as noted above, I is a k-dimensional vector representing the outcome of V(x), the vector representing the combined classifiers. Also, as noted above, V(x) operates on the whole set of sample data (x), therefore, the k-dimensional vector I represents all of the sample data set (x). That is, the claim does not describe how identities I are associated with the individual buckets derived from B(I).
Therefore, it is unclear how the identities denoted by I are distinguished from the k-dimensional vector I which represents the outcome of the combined classifier vector V(x). Applicant must provide a description distinguishing the k-dimensional vector I from the bucket identities I, and how the identities I are assigned to each respective bucket.
Continuing with the limitations of the claim, a membership assignment module, assigns respective memberships js to the respective buckets (B(I)), the memberships js referring to data categories of the training data set (Ωtr), wherein Y(B(I))=j. The memberships js are assigned to the respective buckets (B(I)) if a ratio of the cardinality of sample data (x) with membership j in a bucket (B(I)) to the cardinality of a subset (Ωtr(j)) of the training set (Ωtr) with membership in (j) is maximal among ratios of all memberships, and the membership of the sample data (x) in the collection of data (Ω) is also the membership of the bucket (B(I)) to which the sample data (x) is distributed.
However, it is unclear if the m memberships of the data samples (x), presented as S={1, 2, …, m) are the same memberships as the memberships js, that is, the claim does not describe any association between the m memberships of the sample data (x) and the memberships js. As a result, it is not clear how the limitation, “wherein in this assignment, Y(B(I))=j, the memberships (js) are assigned to the respective buckets (B(I)) if a ratio of the cardinality of sample data (x) with the membership (j) in a bucket (B(I)) to the cardinality of a subset (Ωtr(j)) of the training set (Ωtr) with the membership (j) is maximal among ratios of all memberships, and the membership of sample data (x) in the collection of data (Ω) is also the membership of the bucket (B(I)) to which the sample data (x) is distributed” is implemented. The claims will have to be clarified to define the relationship between the memberships m of the sample data (x) and the memberships (js).
Furthermore, the equation:
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needs to be clarified. That is, the claim states with regard to the limitations in the immediately preceding paragraph: “wherein a step to assign respective memberships (js) to the respective buckets (B(I)) is expressed as: [the equation above]. Given the inconsistencies in the referenced limitations, the above equation also includes these inconsistencies. In addition, the equation seems to be self-referential. That is, the equation defines membership j based on operations performed on the membership j. Once the inconsistencies in the limitations referenced in the immediately preceding paragraph are resolved, the equation above will have to be modified to reflect these clarifications, presuming the modifications are supported in Applicant’s specification.
Claim 16 includes similar limitations and is rejected with the same rationale.
Response to Arguments
Applicant's arguments filed 12 June 2025 have been fully considered but they are not persuasive.
Regarding the amendments intended to overcome the unpatentable subject matter under 35 USC 101, The applicant has amended Claims 1 and 16 with limitations directed to an input module is a hardware device comprising a physical phenomena detector or a data receiver, and the sample data (x) is digital data received from the hardware device. While these limitations requires the input data is provided from a source that cannot be generated by a human, the overall claimed invention in Claim 1 and 16 must process the data so as to improve a computer, another technology, or other technical field. To accomplish this, for example, the claims could include a processing step such that the eclectic classifier improves a computer, another technology, or other technical field.
Regarding the amendments to the claims, Claim 1 states that each bucket (B(I)) has respective identities (I) associated with the characteristics of the data. However, I is a k-dimensional vector representing the outcome of V(x), the vector representing the combined classifiers. Also, V(x) operates on the whole set of sample data (x), therefore, the k-dimensional vector I represents all of the sample data set (x). That is, the claim does not describe how identities I are associated with the individual buckets derived from B(I).
Therefore, it is unclear how the identities denoted by I are distinguished from the k-dimensional vector I which represents the outcome of the combined classifier vector V(x). Applicant must provide a description distinguishing the k-dimensional vector I from the bucket identities I, and how the identities I are assigned to each respective bucket.
it is unclear if the m memberships of the data samples (x), presented as S={1, 2, …, m) are the same memberships as the memberships js, that is, the claim does not describe any association between the m memberships of the sample data (x) and the memberships js. As a result, it is not clear how the limitation, “wherein in this assignment, Y(B(I))=j, the memberships (js) are assigned to the respective buckets (B(I)) if a ratio of the cardinality of sample data (x) with the membership (j) in a bucket (B(I)) to the cardinality of a subset (Ωtr(j)) of the training set (Ωtr) with the membership (j) is maximal among ratios of all memberships, and the membership of sample data (x) in the collection of data (Ω) is also the membership of the bucket (B(I)) to which the sample data (x) is distributed” is implemented. The claims will have to be clarified to define the relationship between the memberships m of the sample data (x) and the memberships (js).
Furthermore, the equation:
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needs to be clarified. That is, the claim states with regard to the limitations in the immediately preceding paragraph: “wherein a step to assign respective memberships (js) to the respective buckets (B(I)) is expressed as: [the equation above]”. Given the inconsistencies in the referenced limitations, the above equation also includes these inconsistencies. In addition, the equation seems to be self-referential. That is, the equation defines membership j based on operations performed on the membership j. Once the inconsistencies in the limitations referenced in the immediately preceding paragraph are resolved, the equation above will have to be modified to reflect these clarifications, presuming the modifications are supported in Applicant’s specification.
Claim 16 includes similar limitations and is rejected with the same rationale.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication should be directed to JOHN M HEFFINGTON at telephone number (571)270-1696.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN M HEFFINGTON whose telephone number is (571)270-1696. The examiner can normally be reached on Monday through Friday from 9:30 am to 5:30 pm Eastern.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cesar B Paula, can be reached at telephone number 571-272-4218. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/J.M.H/Examiner, Art Unit 2145 9/4/2025
/CESAR B PAULA/Supervisory Patent Examiner, Art Unit 2145