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 .
Response to Arguments
Applicant's arguments filed 06/24/26 have been fully considered but they are not persuasive.
The applicant’s 06/24/26 amendments have overcome the previous 35 U.S.C. 112 rejection.
With respect to the 35 U.S.C. 101 rejection, the applicant argues:
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This argument is not persuasive because the claims, in their current form, do not positively recite the user’s act of selecting a module.
The amended claims merely recite, “receive a user selection of one or more selectable modules.”
There is a difference between processing data that is received from a user selection and positively reciting the user and the user’s actions in the claims. Here, the claims are still entirely directed to data processing. The data is received, processed, and then stays on a computer. It does not come off the computer to apply the judicial exception with, or by use of, a machine (see MPEP 2106.05(b)) or effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)).
The applicant is also reminded that claims are evaluated on a case-by-case basis. For step 2A, prong two considerations, the claims are weighed against the criteria for limitations that are indicative of integration into a practical application (see MPEP 2106.05(a), (b), (c), (e), and Vanda) versus the criteria for limitations that are not indicative of integration into a practical application (see MPEP 2106.05(f), (g), (h)).
Even if the claims did positively recite a user selecting a module, the examiner must consider the specificity and manner in which such an element is claimed and whether it more closely aligns with the criteria for limitations that are indicative of integration into a practical application, as opposed to limitations that are not indicative of integration into a practical application.
One suggestion that the examiner will offer is for the applicant to carefully consider what the “solution” of the invention is and whether any added elements serve as a core part of that solution or are merely “extra-solution,” such as routine data gathering or generic display of output data.
The applicant also mentions the “two-computing-system architecture” introduced by the claim amendments. However, the first and second computing systems are generally and generically claimed. When considering whether the limitations were indicative of integration into a practical application, the examiner determined that the general and generic disclosure of the computing systems more closely resembled merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) than it did applying the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)), or improving the functioning of a computer or to any other technology or technical field (see MPEP 2106.05(a)).
Next, the applicant argues:
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This argument is not persuasive because the applicant mentions the details in the specification but has not claimed them. For example, the specification discusses “the construction of cargo ships …” However, there does not appear to be any mention of cargo ships in the claims, which are broadly recited.
One further consideration that the examiner takes into account is the question of monopolization and whether the claim, as a whole, is more than a drafting effort designed to monopolize the exception. Currently, the independent claims would apply to any number of industries that deal with defect data objects, and they could arguably be interpreted to monopolize the exception across all such industries. The claims do not match the narrow scope of some of the examples cited in the applicant’s specification.
Next, the applicant argues:
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This argument is not persuasive because the examiner’s 101 rejection has specified which limitations are considered abstract under step 2A, prong one, as well as which limitations are considered to not be indicative of integration into a practical application, under step 2A, prong two.
For the limitations considered to recite abstract ideas under step 2A, prong one, the examiner has clarified the interpretation based on the current claims. In some cases, the math may not be explicitly claimed, but the claims recite a broad, “determine …” structure that could be performed in the human mind. If the more narrow teachings of the specification are applied, then some of these “determine” limitations may not be able to be performed in the human mind due to their complex mathematics, but then those mathematics represent an abstract mathematical concept.
The applicant can certainly make an “as a whole” argument that even if certain limitations apply math and/or mental process, the claims, as a whole, are not directed to a judicial exception.
However, for such an argument, the examiner considers the overall “solution” of the claims, and here, the solution appeared to be directed to data processing, as opposed to some sort of transformation of a real-world structure or a concrete improvement to the functioning of a computer itself.
Next, the applicant argues:
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This argument is not persuasive because, as discussed above, the claims, in their current form, do not appear to positively recite the nexus between these three elements, in a way that demonstrates that the “solution” of the claimed invention is more than collecting data and processing it. As stated above, the claims have been amended to state, “receive a user selection of one of the one or more selectable modules,” but do not positively recite the user engaging with the modules themselves. The claims also are broad, in the sense of not specifying a specific endeavor, such as work with cargo ships. The current independent claims also do not appear to be entirely clear on how the feature weights are adjusted based on user-confirmed additions and removals of defect data objects.
The examiner would suggest not only claiming the “what” but also the “how”, in order to create a “nexus” between the different elements that the applicant highlighted above.
Next, the applicant argues:
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This argument is not persuasive because, as discussed above, the claims are broadly recited and do not capture the solution put forth by the applicant. The applicant argues for an unconventional two-computing system, but the claims merely recite a general and generic first and second computing system. Also, as seen in the art rejection below, the art teaches a two-computing system. This can simply be a user’s computer communicating with a remote computer or mobile phone. That is well-understood, routine, and conventional.
The applicant draws parallels to Example 39, but Example 39 lacked a judicial exception. There is a judicial exception in these claims, as seen in the rejection below.
Next, the applicant argues:
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This argument is not persuasive because the applicant is again referring to details in the specification that are not claimed. Claim 21 merely gives a generic list of operations, without any details of how the operations are performed and/or related to the core solution.
With respect to the 35 U.S.C. 103 rejection, the applicant’s arguments are moot because the examiner has cited a new section of Marum that rebuts the applicant’s arguments about Marum not teaching a two-computing-system architecture. Paragraph 0012 of Marum explicitly states, “The program code may execute entirely on the user’s computer, partly on the user’s computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server.” This shows a two-computing-system architecture.
For the above reasons, the rejection is upheld.
Drawings
As stated previously, the drawings filed on 06/19/23 are approved.
Claim Objections
Upon comparing the currently amended claims (as filed on 06/24/26) with the previous claims (as filed on 11/07/25), the examiner found the following discrepancies:
Claims 19-20 were cancelled in the previous claims, but there are claims listed as “(Original)” in the most recent set of claims. This will be interpreted as an inadvertent inclusion and that claims 19-20 should be cancelled. They will not be considered in the below rejection.
Claim 8, lines 14-15, of the currently amended claims includes the limitation, “store the comparison metric within the database, wherein subsequent feature extraction from the database is based on the stored comparison metric ..” This limitation does not appear to be in claim 8 of the 11/07/25 claims. It will be construed that this is a newly amended limitation that was added and that should have been underlined.
Claim 8, line 16, of the currently amended claims includes the struck through language of “
Claim 15, line 15, of the currently amended claims includes the struck through language of “
In addition, claim 7 has been amended to state, “generating or providing training data for [[the]] machine learning model based on the generated issue data object …” such that the claim now reads as, “generating or providing training data for machine learning model based on the generated issue data object …” This is a grammatical informality. It will be construed that the claim should state, “generating or providing training data for a machine learning model based on the generated issue data object …”
Examiner’s Note - 35 USC § 112
The applicant’s 06/24/26 claim amendments have overcome the previous 35 U.S.C. 112 rejection.
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 1-18 and 21-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
With respect to step 1 of the patent subject matter eligibility analysis, the claims are directed to a process, machine, manufacture, or composition of matter. Independent claim 1 is directed to a system, which is a machine. Independent claim 9 is directed to a computer-implemented method, which is a process. Independent claim 16 is directed to a non-transitory computer readable medium, which is a manufacture. All other claims depend on independent claims 1, 9, and 16. As such, claims 1-19 are directed to a statutory category.
With respect to step 2A, prong one, the claims recite an abstract idea, law of nature, or natural phenomenon. Specifically, the following limitations recite mathematical concepts and/or mental processes.
Claim 1
determine a defect similarity between the first defect data object and the second defect data object, wherein the defect similarity is determined based on a comparison metric with which to determine the defect similarity, wherein the comparison metric is based on a feature weight (A general determination of a defect similarity, based on a general, undefined, comparison metric, is an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. However, the applicant’s disclosure appears to define the determination by specific equations, such in paragraphs 0038 and 0046 of the original specification. The claimed limitation therefore recites an abstract mental process and/or an abstract mathematical concept.)
determine that the first defect data object and the second defect data object are related based on the comparison metric (A general determination of two data objects being related, based on a general comparison metric, is an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. However, the applicant’s disclosure appears to define the determination by specific equations, such in paragraphs 0038 and 0046 of the original specification. The claimed limitation therefore recites an abstract mental process and/or an abstract mathematical concept.)
Independent claims 8 and 15 recite similar abstract limitations.
All other claims depend on independent claims 1, 8, and 15 and also recite abstract concepts, as a result of their dependency.
Claims 5 and 12 further discloses determination that can be performed in the human mind. They also disclose a comparison between different attributes, where one attribute has a higher feature weight than another attribute, which is an abstract mathematical relationship.
With respect to step 2A, prong two, the claims do not recite additional elements that integrate the judicial exception into a practical application. The following limitations are considered “additional elements” and explanation will be given as to why these “additional elements” do not integrate the judicial exception into a practical application.
Claim 1
A system comprising: a first computing system comprising: at least one processor; and at least one memory storing machine-readable instructions, wherein the at least one processor is configured to access the at least one memory and execute the machine-readable instructions to cause the first computing system to: (These are generic computer components. Merely using a computer as a tool to perform an abstract idea is not indicative of integration into a practical application. See MPEP 2106.05(f))
obtain a first defect data object and a second defect data object from a database (Obtaining data from a database to be processed is part of the data gathering for the data processing solution. It merely adds insignificant extra-solution activity to the judicial exception and is not indicative of integration into a practical application. See MPEP 2106.05(g)).)
perform feature extraction from one or more unstructured fields corresponding to the first defect data object and the second defect data object (This limitation appears to merely be data processing that uses a computer as a tool to perform an abstract idea (Paragraph 0033 of the applicant’s original specification states, “Defect feature extraction module 118 may include programming instruction that cause computer system 110 … to extract feature information.”). It is not indicative of integration into a practical application. (see MPEP 2106.05(f)). Furthermore, the feature extraction appears to simply be part of the data gathering, which merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g).))
based on the performed feature extraction (As discussed in the preceding limitation, the feature extraction appears to be computer processing that merely uses a computer as a tool to perform an abstract idea. (see MPEP 2106.05(f)). It also appears to merely execute part of the data gathering, which merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g).))
related to an attribute of a manufacturing or an industrial process (This limitation merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). It is not indicative of integration into a practical application.)
store the comparison metric within the database, wherein subsequent feature extraction from the database is based on the stored comparison metric (Storing data in a database merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). Also, storing data in a database is a computer operation, and merely using a computer as a tool to perform an abstract idea is not indicative of integration into a practical application (see MPEP 2106.05(f)).)
generate and store an issue data object comprising the first defect data object and the second defect data object in the database, the issue data object indicative of a diagnosis of a defect common to the first defect data object and the second defect data object (This limitation is not indicative of integration into a practical application, as it merely uses a computer as a tool to perform an abstract idea. Also, storing data in a database adds insignificant extra-solution activity to the judicial exception.)
transmit the generated issue data object to a second computing system (Transmitting data merely uses a computer as a tool to perform the abstract idea (see MPEP 2106.05(f)). Furthermore, this limitation is broad and general. No details are given as to the structural nature of the second computing system, nor are any details given as to how the transmission is done. It appears that the transmission is merely general and generic computer processing.)
cause the second computing system to display a first display interface identifying the issue data object and requesting additional defect information associated with the issue data object (Using a generic computing system merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Displaying data processing results, on a generic display interface, merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)).)
obtain, from the second computing system, one or more additional defect data objects in which respective comparison value scores indicative of a degree to which the additional defect data objects correspond to or are related to the issue data object satisfy a criterion, or remove one or more existing defect data objects in which respective comparison value scores indicative of a degree to which the existing defect data objects correspond to or are related to the issue data object or other existing defect data objects within the issue data objects fail to satisfy the criterion (This limitation is not indicative of integration into a practical application, as it merely uses a computer as a tool to perform an abstract idea. The limitation is directed to computer processing. Fetching/removing/ignoring data based on a computation result is also considered a form of “output” of the data processing solution and merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). There mere mention of the second computing system merely uses a computer as a tool to perform an abstract idea.)
generate a second display interface, wherein the second display interface comprises one or more selectable modules that are configured to launch details associated with the comparison metric or the comparison value scores corresponding to any two selected from a group consisting of: the first defect data object, the second defect data object, and the additional defect data objects (This limitation is not indicative of integration into a practical application because the display interface is a computerized form of outputting the processed information, and merely using a computer as a tool to perform an abstract idea is not indicative of integration into a practical application (see MPEP 2106.05(f)). It should be noted that although the claim states that the display interface comprises one or more selectable modules, the limitation does not positively recite the user actually interacting with the selectable modules. The limitation is directed to generating a display interface, which is akin to outputting processed data in visual form. As mentioned, it merely uses a computer as a tool to perform an abstract idea. Furthermore, a mere display of processed data in visual form merely adds insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). The “solution” of the claimed invention is represented by the data processing.)
receive a user selection of one of the one or more selectable modules (This limitation is directed to receiving data, which merely adds insignificant extra-solution activity to the judicial exception.)
in response to the received user selection, launch the details associated with the comparison metric or the comparison value scores (The claimed launching appears to simply be a computer processing response to receiving data. It merely uses a computer as a tool to perform an abstract idea. The data appears to stay on the computer, as opposed to being used to effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)).)
Independent claims 8 and 15 recite similar limitations that are not indicative of integration into a practical application.
All other claims depend on independent claims 1, 8, and 15 and also recite limitations that are not indicative of integration into a practical application, as a result of their dependency.
The dependent claims are further directed to the abstract machine learning operations, and they are also not indicative of integration into a practical application because they merely use a computer as a tool to perform an abstract idea; add insignificant extra-solution activity to the judicial exception; and/or generally link the use of the judicial exception to a particular technological environment or field of use.
Claims 21-22 are further directed to data processing that merely uses a computer as a tool to perform an abstract idea. Also, the image analysis, speech recognition, and textual analysis merely serve to generally link the judicial exception to a particular technological environment or field of use. No detail is given as to how the image analysis, speech recognition, or textual analysis are performed. Also, the claim is written as the processor and memory executing the machine-readable instructions to cause to system to perform … The focus of the claim is on the data processing and not on a specific approach to image data, speech recognition, or textual analysis that would be considered a “solution”.
With respect to step 2B, the claims do not recite additional elements that amount to significantly more than the judicial exception. The claimed invention does not add significantly more because, as discussed above in step 2A, prong two, the claims do nothing more than merely use a computer as a tool to perform an abstract idea; add insignificant extra-solution activity to the judicial exception; and/or generally link the use of the judicial exception to a particular technological environment or field of use. The claims are directed to receiving and processing data. This is well-understood, routine, and conventional. Simply appending well-understood, routine, and conventional activities previously known to the industry, and specified at a high level of generality, to the judicial exception is not indicative of an inventive concept (aka “significantly more”) (see MPEP 2106.05(d) and Berkheimer Memo).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, 7-11, 14-18, and 21-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marum et al (US PgPub 20110321007) in view of Ognev et al (US PgPub 20070074149).
With respect to claim 1, Marum et al discloses:
A system (paragraph 0002 state, “Defect tracking systems …”)
a first computing system (figure 3, reference 210)
at least one processor (paragraph 0013)
at least one memory storing machine-readable instructions, wherein the at least one processor is configured to access the at least one memory and execute the machine-readable instructions (paragraph 0011) to cause the first computing system to:
obtain a first defect data object and a second defect data object from a database (abstract states, “a subset of the different code segments can be predicted utilizing information contained within a database of previously reported defects.”)
determine a defect similarity between the first defect data object and the second defect data object (see defect similarity engine 334; paragraphs 0027 and 0033), wherein the defect similarity is determined based on a comparison metric with which to determine the defect similarity, wherein the comparison metric is based on a feature weight related to an attribute of a manufacturing or an industrial process (paragraph 0022 states, “Any of a variety of statistical analysis methods can be utilized when determining relevancy. For instance, a greater weight can be attributed to segments of similar defects having strong commonalities with the unresolved defects compared to those similar defects with lesser commonalities (as determined by matching defect characteristics, for example).”)
store the comparison metric within the database (paragraph 0050 states, “information can be stored within a database structure …”)
determine that the first defect data object and the second defect data object are related based on the comparison metric (paragraph 0022)
generate and store an issue data object comprising the first defect data object and the second defect data object in the database, the issue data object indicative of a diagnosis of a defect common to the first defect data object and the second defect data object (abstract states, “An unresolved defect can be identified in a computer program product.” The identification of defects is analogous to the claimed generation of an issue data object. Paragraph 0011 discloses various memory to store data.)
transmit the generated issue data object to a second computing system (suggested by paragraph 0012, which states, “The program code may execute entirely on the user’s computer, partly on the user’s computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server.”)
cause the second computing system to display a first display interface identifying the issue data object and requesting additional defect information associated with the issue data object (suggested by the disclosure that any of the operations of the present invention (which includes display capabilities (see figure 3, reference 340), can be performed on either the user’s computer or a remote computer (paragraph 0012).)
obtain, from the second computing system, one or more additional defect data objects in which respective comparison value scores indicative of a degree to which the additional defect data objects correspond to or are related to the issue data object satisfy a criterion, or remove one or more existing defect data objects in which respective comparison value scores indicative of a degree to which the existing defect data objects correspond to or are related to the issue data object or other existing defect data objects within the issue data objects fail to satisfy the criterion (figure 1, reference 135 and figure 2; paragraph 0019 states, “the unresolved defect can be specified along with additional defect information.”; paragraph 0025 states, “When additional defects are detected, the method 100 can repeat …”)
generate a second display interface (paragraph 0012 suggested remote computer; paragraph 0048 states, “The user interface 340 can be an interface through which human to machine interactions occur. The user interface 340 can be a graphical user interface (GUI), a voice user interface (VUI), a multi-modal interface, a text user interface, and the like.”), wherein the second display interface comprises one or more selectable modules that are configured to launch details associated with the comparison metric or the comparison value scores corresponding to any two selected from a group consisting of: the first defect data object, the second defect data object, and the additional defect data objects (suggested by figure 3 and paragraphs 0043-0044, which state, “User interface 340 permits a user of device 310 to interact with the defect prediction engine 332 and its functions. For example, window 342 represents a screen of user interface 340 showing an unresolved defect 343 and its specifics (e.g., details 344). Window 342 includes an option 345 to help find the problem causing the defect. Selection of option 345 can bring up window 439 … window 349 can include specific recommendations, which may be derived from specifics of the past defects that were previously reported and that have already been repaired or corrected.” Please also note claim 3, which states, “responsive to a user selection of one of the subset of the different code segments, navigating to the corresponding navigational aid …”)
receive a user selection of one of the one or more selectable modules (see user interface in figure 3; The user makes selections from the presented menus and options.)
in response to the received user selection, launch the details associated with the comparison metric or the comparison value scores (suggested by paragraphs 0040- 043. Paragraph 0040 discloses comparison metrics/scores. Paragraph 0043 states, “User interface 340 permits a user of device 310 to interact with the defect prediction engine 332 and its functions … Selection of option 345 can bring up window 349.”)
With respect to claim 1, Marum et al differs from the claimed invention in that it does not explicitly disclose:
perform feature extraction from one or more unstructured fields corresponding to the first defect data object and the second defect data object
based on the performed feature extraction
wherein subsequent feature extraction from the database is based on the stored comparison metric
With respect to claim 1, Ognev et al discloses:
perform feature extraction from one or more unstructured fields corresponding to the first defect data object and the second defect data object (Paragraph 0060 of Ognev states, “when data is located (e.g., stored) in multiple defect data stores, a process for determining which data store or group of data stores, to search can be effected via a machine learning technique.” Paragraph 0063 of Ognev states, “SVM’s are configured via a learning or training phase within a classifier constructor and feature selection module.”)
based on the performed feature extraction (paragraphs 0060 and 0063)
wherein subsequent feature extraction from the database is based on the stored comparison metric (obvious in view of combination; Marum teaches comparison (paragraph 0040) and Ognev teaches feature extraction.)
With respect to claim 1, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Ognev et al into the invention of Marum et al. The motivation for the skilled artisan in doing so is to gain the benefit of automating the processes of Marum.
Independent claims 8 and 15 represent variations of claim 1 and are rejected for similar reasons.
With respect to claims 2, 9, and 16, Marum et al, as modified, discloses:
adjust the feature weight or a different feature weight based on the generated issue data object, the additional defect data objects, or the removed existing defect data objects (obvious in view of paragraph 0022 of Marum; it would be obvious to one of ordinary skill in the art to adjust weight based on the defect data.)
With respect to claims 3, 10, and 17, Marum et al, as modified, discloses:
generate or provide training data for a machine learning model based on the generated issue data object, the additional defect data objects, or the removed existing defect data objects (obvious in view of applying machine learning teachings of Ognev to data of Marum)
With respect to claims 4, 11, and 18, Marum et al, as modified, discloses:
obtain an approval of the issue data object (note “Approvals” in figure 3, reference 342)
generate or provide training data for a machine learning model based on the approval of the issue data object (obvious in view of combination; Marum teaches approvals and Ognev teaches machine learning)
With respect to claims 7 and 14, Marum et al, as modified, discloses:
train a machine learning model based on the generated issue data object, the additional defect data objects, or the removed existing defect data objects (obvious in view of combination; Ognev teaches machine learning and training (see paragraphs 0062-0063 of Ognev))
With respect to claim 21, Marum et al, as modified, discloses:
wherein the at least one processor is configured to access the at least one memory and execute the machine-readable instructions to cause the first computing system to perform image analysis on image data, speech recognition on audio data, and textual analysis on textual data within the one or more unstructured fields (Marum paragraph 0017 states, “Computer code products can consist of millions of lines of code, which can be organized in different interactive structural units … applications.” Ognev paragraph 0008 states, “It is to be understood and appreciated that this open and extensible framework can be applied to a wide range of applications where such analysis is needed and/or desired.” In view of Marum and Ognev explicitly disclosing that its principles could be applied to a wide variety of different application contexts, it would be obvious to one of ordinary skill in the art to configure the processor and memory to cause the system to perform each of the claimed applications, which are generic and common applications.)
With respect to claim 22, Marum et al, as modified, discloses:
wherein the at least one processor is configured to access the at least one memory and execute the machine-readable instructions to cause the first computing system to perform feature extraction from one or more corresponding fields or structured features of the first defect data object and the second defect data object (obvious in view of combination; figure 11 of Ognev shows processing unit and access to memory. Ognev discloses feature extraction, and Marum discloses defect data objects. Ognev also discloses defect analysis (abstract).)
Claim(s) 5-6 and 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marum et al (US PgPub 20110321007) in view of Ognev et al (US PgPub 20070074149), as applied to claims 1-4, 7-11, 14-18, and 21-22 above, and further in view of Caldwell et al (US PgPub 20100174691).
With respect to claims 5 and 12, Marum et al, as modified, discloses:
A system (as applied to claims 1 and 8 above)
With respect to claims 5 and 12, Marum et al, as modified, differs from the claimed invention in that it does not explicitly disclose:
wherein the determining of the defect similarity is based on the feature weight and an other feature weight corresponding to an other attribute, wherein the attribute has a higher feature weight compared to the other attribute and the feature weight is evaluated prior to the other feature weight
With respect to claims 5 and 12, Caldwell et al discloses:
wherein the determining of the defect similarity is based on the feature weight and an other feature weight corresponding to an other attribute, wherein the attribute has a higher feature weight compared to the other attribute and the feature weight is evaluated prior to the other feature weight (paragraph 0054 states, “the method or the system for automatically classifying a defect into a category determines whether the first defect is to be categorized into the first category in some embodiments. In some embodiments, the method or the system for automatically classifying a defect into a category may identify a threshold weight or a threshold score for a keyword …”; The threshold weight is construed to anticipate “an other feature weight”. This would appear to align with paragraph 0044 of the applicant’s specification, which states, “a predetermined threshold comparison value score may be used …” Please note that the examiner could not find any recitation of “an other feature weight” in the specification; it was only mentioned in the claims. The examiner is interpreting the threshold comparison value score of paragraph 0044 to serve as support for this limitation. If this is not the case, the examiner requests the applicant show where this limitation is supported in the specification.)
With respect to claims 5 and 12, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Caldwell et al into the invention of modified Marum et al. The motivation for the skilled artisan in doing so is to gain the benefit of providing a standard for automatic defect categorization.
With respect to claims 6 and 13, Marum et al, as modified, discloses:
halt an evaluation of the other feature weight if the evaluation of the feature weight fails to satisfy the criterion or a different criterion (paragraph 0075 of Caldwell states, “where the method or the system for automatically classifying a defect into a category determines that the result score or resultant weight causes the defect … the method or system stops the current iteration …”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mann et al (US PgPub 20190132191) discloses machine-learning and deep-learning techniques for predictive ticketing in information technology systems.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/LEONARD S LIANG/Examiner, Art Unit 2857 09/05/26
