DETAILED ACTION
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 .
Status of Claims
Claims 1-11 are pending and are examined herein.
Claims 1-11 are rejected under 35 USC 112(b).
Claims 1-11 are rejected under 35 USC 101 as being directed to an abstract idea without significantly more.
Claim 1 is rejected under 35 USC 102.
Claim 1 is rejected on the grounds of non-statutory double patenting.
Examiner Remarks
This Office action includes a Non-statutory Double Patenting rejection. Please note that MPEP § 804 states:
A complete response to a nonstatutory double patenting (NSDP) rejection is either a reply by applicant showing that the claims subject to the rejection are patentably distinct from the reference claims or the filing of a terminal disclaimer in accordance with 37 CFR 1.321 in the pending application(s) with a reply to the Office action (see MPEP § 1490 for a discussion of terminal disclaimers). Such a response is required even when the nonstatutory double patenting rejection is provisional. As filing a terminal disclaimer, or filing a showing that the claims subject to the rejection are patentably distinct from the reference application’s claims, is necessary for further consideration of the rejection of the claims, such a filing should not be held in abeyance. Only objections or requirements as to form not necessary for further consideration of the claims may be held in abeyance until allowable subject matter is indicated. Replies with an omission should be treated as provided in MPEP § 714.03.
Claim Objections
Claims 1, 5, and 10 are objected to because of the following informalities:
Claims 1 and 5 do not end with a period.
Claim 10 recites “extracting, key values comprising;”. This is being treated as a typographical error for “extracting[[,]] key values comprising[[;]]:”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
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.
Claims 1-11 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 1 recites “temporary files”; however, “temporary” is a relative term which renders the scope of the claim indefinite. The claims and specification provide no standard by which it may be determined whether or not any particular length of time would be considered “temporary”. For the purposes of examination, any file would be interpreted as falling within the scope of a “temporary” file. Dependent claims 2-11 do not resolve the issue and are rejected with the same rationale.
Claim 2 recites “calculating whether each pattern of size 1 extracted from the key value pairs”; however, it is not clear what patterns of size 1 extracted from the key value pairs is being quantified over as the claim does not recite extracting patterns of size 1 from key value pairs. For the purposes of examination, the claim is being interpreted as requiring extracting at least one pattern of size 1 from the key value pairs. Dependent claims 3-11 do not resolve the issue and are rejected with the same rationale.
Claim 2 recites “reliable pattern”; however, this term is not a term of art and is not defined by the claim or the specification (while published [0037] provides what would appear to be a definition, published [0042] indicates that no definitions should not be taken as limiting definitions). Consequently, a person of ordinary skill in the art would not be reasonably apprised of the scope of the claimed invention. For the purposes of examination, a “reliable pattern” will be interpreted as indicated at [0037]. Dependent claims 3-11 do not resolve the issue and are rejected with the same rationale.
Claim 2 recites “calculating whether a reliable pattern of size 1 is a significant pattern for any class if a class probability for such class is higher than the class probability for another class in said dataset;”. Interpreted in view of the specification, the “if” part of the limitation appears to specify what it means to be a reliable pattern of size 1 rather than a condition which much be met before the calculating is performed in the first place (see also instant published specification at [0039, 0074]). The claim language is ambiguous whether the “if” states a precondition (making the limitation a contingent limitation) or states the condition/definition for a reliable pattern of size 1 to be considered a significant patter. For the purposes of examination, the second interpretation is being taken (i.e., the limitation is not a contingent limitation and a reliable pattern of size 1 would be calculated/determined to be a significant pattern when a class probabili8ty for such class is higher than the class probability for another class in said dataset”. Dependent claims 3-11 do not resolve the issue and are rejected with the same rationale.
Claim 2 recites “the refinable pattern”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this is being interpreted as a reference to the previously recited “refined pattern”. Dependent claims 3-11 do not resolve the issue and are rejected with the same rationale.
Claim 3 recites “the record set”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this is being interpreted as a reference to the dataset from claim 1. Dependent claims 3-11 do not resolve the issue and are rejected with the same rationale. Dependent claims 4-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 3 recites “refinable patterns of size k-1”. While claim 2 appears to define “refinable pattern” for size 1, it does not define it for other sizes. The term “refinable pattern” is not a term of art. [0041] provides a description, but [0042] makes it clear that the definitions are not meant to be limiting. Consequently, a person of ordinary skill in the art would not be reasonable apprised of the scope of “refinable pattern” for sizes other than 1. For the purposes of examination, a refinable pattern is being interpreted as described at [0041]. Dependent claims 4-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 3 recites “the updated record id”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this is being interpreted as “an updated record id”. Dependent claims 4-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 3 recites “the frequency of the size k patterns” and “the maximum frequency for each class”; however, these limitation lack proper antecedent basis. For the purposes of examination, these are being interpreted as “a frequency of the size k patterns” and “a maximum frequency for each class”. Dependent claims 4-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 4 recites “the refined pattern for each class which has a higher end value of the confidence interval of that class probability”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “a refined pattern for each class which has a higher end value of the confidence interval of that class probability”. Dependent claims 5-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 4 recites “the maximum of the higher end of the confidence interval of that class probability”; however, these limitations lack proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “a maximum of a higher end of the confidence interval of that class probability”. Dependent claims 5-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 4 recites “the given probability”; however, this limitation lack proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “a given probability”. Dependent claims 5-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 5 recites “the significant patterns”; however, this limitation lack proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “significant patterns”. Dependent claims 6-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 5 recites “the entire dataset”; however, this limitation lack proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “the dataset”. Dependent claims 6-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 5 recites “the class probability”; however, this limitation lack proper antecedent basis. For the purposes of examination, this limitation is being interpreted as “a class probability”. Dependent claims 6-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 5 recites “if found to be significant”. The term “significant” is not a term of art and is not defined by the specification or the claim. This concept is described at [0039], but [0042] indicates that it is not a definition. For the purposes of examination, “significant’ is being interpreted as indicated at [0039]. Dependent claims 6-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 5 recites “that particular class”; however it is unclear which particular class is being referenced. For the purposes of examination, this limitation is being interpreted as “a class”. Dependent claims 6-7 and 10-11 do not resolve the issue and are rejected with the same rationale.
Claim 6 recites “wherein in order to compute statistics to discretize continuous attributes and obtain a class distribution of a data set”; however, it is unclear what previous step or steps is being referred to. For the purposes of examination, the claim is being interpreted as requiring a step of computing statistics to discretize continuous attributes and obtain a class distribution of a dataset. Dependent claims 10-11 do not resolve the issue and are rejected with the same rationale. Furthermore, claim 10 recites the same indefinite language.
Claim 7 recites “wherein in order to determine said significant class probabilities to be reliably significant relevant class patterns for a dataset, further comprises”; however, the claim does not recite a step of determining significant class probabilities to be reliably significant relevant class patterns. Furthermore, “reliably significant relevant class patterns” is not a term of art and is not defined by either the claims or the specification. For the purposes of examination, the claim is being interpreted as requiring a step of determining that the significant class probabilities are reliable significant relevant class patterns for the dataset, with the terms reliable, significant and relevant interpreted as indicated at [0037-0041].
Claim 7 recites “the minimum class probability for each class”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as “a minimum class probability for each class”.
Claim 8 recites “the attribute index”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as “an attribute index”. Claim 9 does not resolve the issue and is rejected with the same rationale.
Claim 8 recites “the pattern class distribution”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as “a pattern class distribution”. Claim 9 does not resolve the issue and is rejected with the same rationale.
Claim 8 recites “weighted average improvement (positive lift)”. It is unclear what limiting effect, if any, the parenthetical is meant to have. For the purposes of examination, the parenthetical portion is being interpreted as providing an example that is not limiting. Claim 9 does not resolve the issue and is rejected with the same rationale.
Claim 9 recites “the descending discernibility strength”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as “
Claim 10 recites “updating an expectation of squares value by;”. It appears that the limitation was mean to continue. For the purposes of examination, This limitation is being interpreted as “updating an expectation of squares value
Claim 11 recites “the difference of attribute value from an attribute minimum value”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as “a difference...”.
Claim 11 recites “the converted attribute set”; however, this limitation lacks proper antecedent basis. For the purposes of examination, this limitation will be interpreted as a reference to the attribute that was converted in the previous limitation.
Claim Rejections - 35 USC § 101 – Abstract Idea
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis
Each of the claims fall within one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter).
Step 2 Analysis
Claim 1 includes the following recitation of an abstract idea:
for searching for patterns in datasets (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...generating pattern key-value pairs from each discretized record of a dataset by taking an attribute and attribute value combination as a key and record identification (id) and decision value from computing buckets of said system; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
Claim 1 recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
A computer implemented method (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
...in a system having multiple computer processors comprising: (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
writing key value pairs for each partition of records to temporary files via a computing bucket; and (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
sending key value pairs to different computing buckets in a sorted key order so that pairs with the same pattern key will be sent to the same computing bucket; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
Claim 1 does not reflect an improvement to computer technology or any other technology.
Claim 2 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
calculating whether each pattern of size 1 extracted from the key value pairs is a reliable pattern for any class; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating whether a reliable pattern of size 1 is a significant pattern for any class if a class probability for such class is higher than the class probability for another class in said dataset; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating whether a pattern of size 1 is a refinable pattern where at least one class has a minimum frequency and does not have 1 as an upper end value of an estimated population probability confidence interval; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating a minimum significant probability for a refined pattern for each class for which the higher end value of a confidence interval of a class probability of the refinable pattern is a significant pattern; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating attribute variability and discernibility strength of each attribute; and (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating a minimum refined pattern frequency for each class that has a class frequency that is higher than said minimum frequency and has a lower end of a confidence interval of a pattern class probability that is higher than a predetermined probability. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 2 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 2 does not reflect an improvement to computer technology or any other technology.
Claim 3 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
making row based partitions of k-1 size patterns, where k is any value greater than or equal to 2; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
from the partitions, generating size k key-value pairs from refinable patterns of size k-1 by adding one attribute and a value from the record set of size k-1 pattern in such a way that a discernibility index of such attribute is higher than an existing discernibility index of an attribute to the key and the updated record id and decision value as value; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...calculating pattern statistics for each pattern of size k; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
evaluating whether super patterns of pattern of size k are refinable and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
computing a maximum significant probability of patterns that are refinable, and (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
checking whether the frequency of a pattern is greater than a minimum frequency of the super patterns and whether the frequency of the size k pattern is greater than the maximum frequency for each class of the refinable super patterns; and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
evaluating whether the pattern of size k has a probability not less than the minimum significant probability, and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
adding said pattern of size k to a significant pattern list if the pattern has a lower bound of a confidence interval of a pattern class probability that is higher than a class probability of reliable super-patterns of size k-i of same class. (This is practical to perform in the human mind under its broadest reasonable interpretation, perhaps assisted by pen and paper for tracking the list. This is a recitation of a mental process.)
Claim 3 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
writing key value pairs for each partition of records to temporary files via a computing bucket; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
sending key value pairs to different computing buckets in a sorted key order so that pairs with same pattern key will be sent to the same computing bucket; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
Claim 3 does not reflect an improvement to computer technology or any other technology.
Claim 4 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
readjusting pattern statistics for size k-1 super-patterns, where k is any value greater than or equal to 2 of the size k pattern; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
updating a record set for each super-pattern of size k-1 of a size k pattern by removing record ids from a record id set of a super-pattern that occur in a size k pattern ; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
calculating whether a pattern of size k is a refinable pattern for any class where such class has a minimum frequency and does not have 1 as the upper end value of the estimated population probability confidence interval, and adding to the refinable patterns repository of size k; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating a minimum significant probability for the refined pattern for each class which has a higher end value of the confidence interval of that class probability if the refinable pattern is a significant pattern, (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
otherwise determining that the minimum significant probability is the maximum of the higher end of the confidence interval of that class probability of significant super patterns of the refinable pattern; and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
calculating a minimum refined pattern frequency for each class that has a class frequency that is higher than said minimum frequency and a lower end of a confidence interval of a pattern class probability is higher than the given probability . (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 4 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 4 does not reflect an improvement to computer technology or any other technology.
Claim 5 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
making a row based partitioning of the significant patterns ; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
re-evaluating the significant patterns for significance over the entire dataset by calculating the class probability of each class and adding a class to relevant patterns if found to be significant; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
sorting relevant patterns based on descending order of probability and frequency and and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
computing a cumulative coverage of the sorted relevant patterns by finding groups of records of that particular class; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 5 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
storing the sorted relevant patterns after generation of said relevant patterns; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing or retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
Claim 5 does not reflect an improvement to computer technology or any other technology.
Claim 6 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein in order to compute statistics to discretize continuous attributes and obtain a class distribution of a data set, further comprises: (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
making row based partitions of the dataset of records; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
building key value pairs from dataset records; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...processing class frequency and probability values; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
computing continuous attribute statistics of said dataset. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 6 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
writing the key value pairs for each partition of records to temporary files; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
sending the key value pairs in a sorted key order so that pairs with same attribute key will together; and (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
Claim 6 does not reflect an improvement to computer technology or any other technology.
Claim 7 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein in order to determine said significant class probabilities to be reliably significant relevant class patterns for a data set, further comprises: (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
computing the minimum class probability for each class as the lower bound of a confidence interval of a population probability for that class at given confidence levels from the class pattern for that class; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
computing the minimum class frequency as a pattern having a significant class pattern for each class; and (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 7 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
storing all these values in a shared memory for shared access. (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing or retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
Claim 7 does not reflect an improvement to computer technology or any other technology.
Claim 8 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein said attribute variability and discernibility strength calculations of attributes further comprises: (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
finding a pattern probability of the patterns of the discretized data set; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
updating the variability for the attribute index to zero if a confidence interval of the pattern probability has a value of 1; and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...and computing the discernibility strength for each pattern as a weighted average improvement (positive lift) of class probabilities with pattern frequency as weights. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 8 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
obtaining the pattern class distribution (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
Claim 8 does not reflect an improvement to computer technology or any other technology.
Claim 9 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
further comprising removing size 1 significant and refinable patterns with zero variability attributes and sorting the attributes on the descending discernibility strength. (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
Claim 9 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 9 does not reflect an improvement to computer technology or any other technology.
Claim 10 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein computing statistics to discretize continuous attributes and obtain class distributions in a data set further comprising: (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
making row based partitions of the dataset of records; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
building key value pairs from data set records; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...extracting a decision attribute index value as a key and decision attribute value; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...extracting a continuous attribute index value as a key and continuous attribute value; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
...sorting key value pairs in a sorted key order so that pairs with same attribute key will be together; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
calculating a class frequency and a probability; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
calculating continuous attribute statistics comprising: (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
updating a minimum value with a received attribute value if the minimum value is less than a predetermined minimum; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
updating a maximum value with the received attribute value if the maximum value is greater than a predetermined maximum; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
updating an expectation value; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
updating an expectation of squares value by; and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
computing a standard deviation. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 10 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
writing key value pairs for each partition of records to temporary files and extracting, key values comprising; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
... writing the decision attribute index and a decision attribute value pair to a temporary file; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
writing the continuous attribute index and continuous attribute value pair to a temporary file; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
Claim 10 does not reflect an improvement to computer technology or any other technology.
Claim 11 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein said discretization of continuous attributes further comprises: (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
making row based partitions of dataset of records computing a range of an attribute as a maximum value minus a minimum value, and equally dividing the range into a number of discrete classes for uniform scaling discretization; (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
converting an attribute to a discrete value by using the difference of attribute value from an attribute minimum value in proportion to class width; and (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process.)
Claim 11 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
writing the converted attribute set to a discretized table. (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, storing/retrieving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example iv. Storing and retrieving information.)
Claim 11 does not reflect an improvement to computer technology or any other technology.
Claim Rejections - 35 USC § 102
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim1 is rejected under 35 U.S.C. 102(a)(2) as being anticipated by “Saadat” (US 2012/0143873 A1).
Regarding claim 1, Saadat teaches
A computer implemented method for searching for patterns in datasets in a system having multiple computer processors comprising: (Saadat, Abstract and Figure 1A describes a method performed in a system having multiple computer processors.)
generating pattern key-value pairs from each discretized record of a dataset by taking an attribute and attribute value combination as a key and record identification (id) and decision value from computing buckets of said system; writing key value pairs for each partition of records to temporary files via a computing bucket; and (Saadat, [0043-0046], [0089-0094]. In particular, [0044] describes generating an index comprising at least a key field (i.e., the choice of field and the value of that field is the key). The hash values of the key correspond to the partition/bucket to which the items are assigned. [0054] indicates that each record may also include a unique identifier. [0135] indicates that the memory of each device may be used to store temporary values, which would include the keys value pairs generated during execution of the algorithm. Note that the instant specification indicates that a “computing bucket” encompasses at least a processing unit (see, e.g., published instant specification at [0075].)
sending key value pairs to different computing buckets in a sorted key order so that pairs with the same pattern key will be sent to the same computing bucket; (Saadat, [0031, 0035, 0056] indicates that the values for the records are stored in their respective partitions. [0089] indicates that the master index may be sorted on key values. The recitation of “so that...” in the claim is a recitation of an intended result. Nevertheless, [0044] indicates that the keys are hashed to determine the partition, so that records with the same keys will end up in the same partition.)
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.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 11 of U.S. Patent No. 10,733,156. Although the claims at issue are not identical, they are not patentably distinct from each other as indicated below. Instant claim language is shown in bold and claim language from the patent is shown in italics. Patented claim 11 teaches: A computer implemented method for searching for patterns in datasets in a system having multiple computer processors comprising: (A computer implemented method to obtain discrete partitions of continuous attributes in large quantities of classified data set with one or more continuous attributes and a decision attribute using multiple processors comprising:)
generating pattern key-value pairs from each discretized record of a dataset by taking an attribute and attribute value combination as a key and record identification (id) and decision value from computing buckets of said system; (...forming a key value pair where a key of the key value pair is based on a continuous attribute index and attribute value and a value of the key value pair is based on decision attribute value;)
writing key value pairs for each partition of records to temporary files via a computing bucket; and (sorting keys in ascending order on attribute index followed by attribute value; Note that sorting the keys necessarily requires at least temporarily storing them. The steps are performed by a computer (i.e., computing bucket) as indicated in the preamble of patented claim 11.)
sending key value pairs to different computing buckets in a sorted key order so that pairs with the same pattern key will be sent to the same computing bucket; (sending sorted keys having same attribute index into same processor to create a partition set of that attribute;)
Examiner Remarks
Claims 2-11 are not rejected under 35 USC 102 or 103.
Regarding claim 2, Saadat teaches claim 1 as indicated above.