DETAILED ACTION
Claims 1 – 20 have been presented for examination. Claims 1 – 20 are currently amended. Claim 21 is cancelled.
This office action is in response to submission of the application on 09/14/2023.
The instant Office Action relies on Qian et al. “Introducing self-organized maps (SOM) as a visualization tool for materials research and education” which is cited on the IDS.
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 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Independent claim 1 recites at Step 1 a statutory category (i.e. a machine) singular material detection apparatus to: generate, by using the physical property information, a self-organizing map on which each node is assigned a position in a map space and a physical property vector indicating a value related to a physical property quantity for each of a plurality of types of the physical properties of the product; assign each material specification information to one of the nodes based on the physical property information corresponding to that material specification information; and detect a singular node located at a singular position in the map space out of the nodes that are assigned the material specification information. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “generate” and “assign” and “detect” amounts to modeling actions recited at a high-level of generality which are not reasonably precluded from being performed mentally. Accordingly, the claim recites an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: at least one memory that is configured to store instructions; and at least one processor that is configured to execute the instructions to: acquire, for each of a plurality of patterns of a material that can be used in a target process, material specification information representing a material specification of the material and physical property information indicating a physical property quantity for each of a plurality of physical properties of a product that can be generated in the target process by using the material. The “memory” and “processor” are recited at a high-level of generality such that they amount to no more than mere application of the judicial exception using generic computer components which does not amount to an improvement in computer functionality (see MPEP 2106.04(a)(I)). The “acquire” amounts to insignificant data gathering since it is recited at a high-level of generality, and since the “generate” step relies on the received elements in a generic manner (see MPEP 2106.04(d) referencing MPEP 2106.05(g)). The claim is directed to an abstract idea.
At Step 2B the claim does not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the recited “memory” and “processor” amount to no more than mere instructions to apply the judicial exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The recited “acquire” covers well-understood, routine, and conventional activity since it is generic with regard to how the data is obtained and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). Considering the additional elements in combination does not add anything more than when considering them individually since the “acquire” requires no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Dependent claim 2 – 7 recite(s) at Step 1 the same statutory category as the parent claim(s), and further recite(s): Claim 2 wherein the assignment of the material specification information further includes, for each of a plurality of pieces of the material specification information, assigning the material specification information to the node to which the physical property vector that is most similar to the physical property vector obtained from the physical property information corresponding to that material specification information is assigned; Claim 3 wherein the detection of the singular node further includes detecting, out of the nodes that are assigned the material specification information, the node whose distance from a reference position in the map space is larger than a threshold as a singular node; Claim 4 wherein the detection of the singular node further includes computing a center of mass or a geometric center of the plurality of nodes that are assigned the material specification information as the reference position; and computing, as the threshold, a statistic value representing a magnitude of a distribution of positions of the plurality of nodes that are assigned the material specification information are assigned or a value obtained by multiplying the statistic value by a predetermined positive real number; Claim 5 wherein the detection of the singular node further includes: dividing the plurality of the nodes that are assigned the material specification information into a plurality of clusters based on the material specification information; and detecting, for each of the plurality of the clusters, the singular node out of the nodes belonging to the cluster based on a distribution of positions of the nodes in the map space included in the cluster. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “assigning” and “detecting” and “dividing” and “calculating” amounts to modeling and predicting actions recited at a high-level of generality which are not reasonably precluded from being performed mentally. Alternatively, the recited limitations in part, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover mathematical calculations(see MPEP 2106.04(a)(2)(I)). The “calculating” recites specific mathematical relationships and/or calculations. Accordingly, the claim(s) recite(s) an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: Claim 6 wherein the at least one processor is configured to further to generate a map image showing each of the nodes arranged in the map space, wherein the map image includes an indication indicating the singular node; Claim 7 wherein the indication indicating the singular node indicates the material specification represented by the material specification information assigned to the singular node, the physical properties represented by the physical property vector assigned to the singular node, or both. For example, the “generate a map image” and “indicates” amounts to insignificant data outputting since it generates and displays (i.e., showing) desired data (see MPEP 2106.04(d)). The claim is directed to an abstract idea.
At Step 2B the claim(s) do not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. The “generate a map image” and “indicates” covers well-understood, routine, and conventional activity since it is generic with regard to how the data is obtained and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). Considering the additional elements in combination does not add anything more than when considering them individually since the “generate a map image” and “indicates” requires no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Independent claim 8 recites at Step 1 a statutory category (i.e. a process) control method performed by a computer, comprising: generating, by using the physical property information, a self-organizing map on which each node is assigned a position in a map space and a physical property vector indicating a value related to a physical property quantity for each of a plurality of types of the physical properties of the product; assigning each material specification information to one of the nodes based on the physical property information corresponding to that material specification information; and detecting a singular node located at a singular position in the map space out of the nodes that are assigned the material specification information. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “generating” and “assigning” and “detecting” amounts to modeling actions recited at a high-level of generality which are not reasonably precluded from being performed mentally. Accordingly, the claim recites an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: acquiring, for each of a plurality of patterns of a material that can be used in a target process, material specification information representing a material specification of the material and physical property information indicating a physical property quantity for each of a plurality of physical properties of a product that can be generated in the target process by using the material. The “acquiring” amounts to insignificant data gathering since it is recited at a high-level of generality, and since the “generating” step relies on the received elements in a generic manner (see MPEP 2106.04(d) referencing MPEP 2106.05(g)). The claim is directed to an abstract idea.
At Step 2B the claim does not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. The recited “acquiring” covers well-understood, routine, and conventional activity since it is generic with regard to how the data is obtained and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). Considering the additional elements in combination does not add anything more than when considering them individually since the “acquiring” requires no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Dependent claim 9 – 14 recite(s) at Step 1 the same statutory category as the parent claim(s), and further recite(s) limitations substantially the same as claims 1 – 7 which may be compared. Accordingly, the claim(s) recite(s) an abstract idea for the same reasons.
At Step 2A, Prong II this judicial exception is not integrated into a practical application for the same reasons as claims 1- 7. The claim is directed to an abstract idea.
At Step 2B the claim(s) do not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. For at least the same reasons as claims 1 - 7, the claim is not patent eligible.
Independent claim 15 recites at Step 1 a statutory category (i.e. a machine)
non-transitory computer readable medium storing a program that causes a computer to perform: generating, by using the physical property information, a self-organizing map on which each node is assigned a position in a map space and a physical property vector indicating a value related to a physical property quantity for each of a plurality of types of the physical properties of the product; assigning each material specification information to one of the nodes based on the physical property information corresponding to that material specification information; and detecting a singular node located at a singular position in the map space out of the nodes that are assigned the material specification information. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “generating” and “assigning” and “detecting” amounts to modeling actions recited at a high-level of generality which are not reasonably precluded from being performed mentally. Accordingly, the claim recites an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: acquiring, for each of a plurality of patterns of a material that can be used in a target process, material specification information representing a material specification of the material and physical property information indicating a physical property quantity for each of a plurality of physical properties of a product that can be generated in the target process by using the material. The “acquiring” amounts to insignificant data gathering since it is recited at a high-level of generality, and since the “generating” step relies on the received elements in a generic manner (see MPEP 2106.04(d) referencing MPEP 2106.05(g)). The claim is directed to an abstract idea.
At Step 2B the claim does not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. The recited “acquiring” covers well-understood, routine, and conventional activity since it is generic with regard to how the data is obtained and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). Considering the additional elements in combination does not add anything more than when considering them individually since the “acquiring” requires no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Dependent claim 16 – 20 recite(s) at Step 1 the same statutory category as the parent claim(s), and further recite(s) limitations substantially the same as claims 1 – 6 which may be compared. Accordingly, the claim(s) recite(s) an abstract idea for the same reasons.
At Step 2A, Prong II this judicial exception is not integrated into a practical application for the same reasons as claims 1- 6. The claim is directed to an abstract idea.
At Step 2B the claim(s) do not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. For at least the same reasons as claims 1 - 6, the claim is not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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.
Claims 8 – 9 and 13 – 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Qian et al. “Introducing self-organized maps (SOM) as a visualization tool for materials research and education” (henceforth “Qian”).
With regard to claim 8, Qian teaches a control method performed by a computer, comprising: (Qian Page 5, Left “When running on a local computer with a 2.3 GHz two-core processor, the training process of our SOM with a map size of 60 x 60 on our dataset with 398 materials and 21 properties takes 221.513 s.”)
acquiring, for each of a plurality of patterns of a material that can be used in a target process, material specification information representing a material specification of the material and physical property information indicating a physical property quantity for each of a plurality of physical properties of a product that can be generated in the target process by using the material; (Qian Page 4, Right data is extracted from Granta including type of materials (material specification information) and functional properties of the materials (physical property information indicating), where the materials are desirable used for any purpose (in a target process) “By using the data extraction tool in Granta, a total of 421 materials with their various properties were produced. The training data consists of 196 ceramic materials and 225 metallic materials. … Some of the properties are numerical data, e.g. Young’s modulus, and some of the properties are categorical data, e.g. magnetic or non-magnetic”)
generating, by using the physical property information, a self-organizing map on which each node is assigned a position in a map space and a physical property vector indicating a value related to a physical property quantity for each of a plurality of types of the physical properties of the product; (Qian Page 5, Left an SOM is trained from the material properties (by using the physical property information), and where each node matches a training material with associated material properties (each node is assigned a position and vector)
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assigning each material specification information to one of the nodes based on the physical property information corresponding to that material specification information; and (Qian Figure 9 the nodes are assigned their base material (material specification information to nodes) on the SOM (based on the physical property information corresponding to)
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detecting a singular node located at a singular position in the map space out of the nodes that are assigned the material specification information. (Qian Page 13, Left and Figure 9 materials which same base material can show large difference in functional properties (a singular node located at a singular position) “We have identified these ‘outlier’ materials to be: two Beryllium metals and diamond. These materials are unique due to their processing method and base material composition, supporting SOM as an effective tool for identifying material similarities and dissimilarities”)
With regard to claim 9, Qian teaches all the elements of the parent claim 8, and further teaches
wherein the assignment of the material specification information further includes, for each of a plurality of pieces of the material specification information, assigning the material specification information to the node to which the physical property vector that is most similar to the physical property vector obtained from the physical property information corresponding to that material specification information is assigned. (Qian Page 5, Right the base material used for the specific SOM node is shown (assigning to the node in which vector is most similar), where the SOM represents functional properties derived from the material composition (physical property vector obtained from the physical property information corresponding to that material specification information))
With regard to claim 13, Qian teaches all the elements of the parent claim 8, and further teaches:
generating a map image showing each of the nodes arranged in the map space, wherein the map image includes an indication indicating the singular node. (Qian Figure 9 outliers are indicated
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With regard to claim 14, Qian teaches all the elements of the parent claim 13, and further teaches:
wherein the indication indicating the singular node indicates the material specification represented by the material specification information assigned to the singular node, the physical properties represented by the physical property vector assigned to the singular node, or both. (Qian Figure 9 outliers are indicated along with the base material (the material specification information assigned)
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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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 7, 10 – 12 and 15 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Qian, and further in view of Guan et al. “K-means+: An Autonomous Clustering Algorithm” (henceforth “Guan”). Qian and Guan are analogous art because they solve the same problem of providing information related to product development, and because they are from the same field of endeavor of product development.
With regard to claim 1, Qian teaches a singular material detection apparatus comprising: at least one processor that is configured to execute the instructions to: (Qian Page 5, Left “When running on a local computer with a 2.3 GHz two-core processor, the training process of our SOM”)
acquire, for each of a plurality of patterns of a material that can be used in a target process, material specification information representing a material specification of the material and physical property information indicating a physical property quantity for each of a plurality of physical properties of a product that can be generated in the target process by using the material; (Qian Page 4, Right data is extracted from Granta including type of materials (material specification information) and functional properties of the materials (physical property information indicating), where the materials are desirable used for any purpose (in a target process) “By using the data extraction tool in Granta, a total of 421 materials with their various properties were produced. The training data consists of 196 ceramic materials and 225 metallic materials. … Some of the properties are numerical data, e.g. Young’s modulus, and some of the properties are categorical data, e.g. magnetic or non-magnetic”)
generate, by using the physical property information, a self-organizing map on which each node is assigned a position in a map space and a physical property vector indicating a value related to a physical property quantity for each of a plurality of types of the physical properties of the product; (Qian Page 5, Left an SOM is trained from the material properties (by using the physical property information), and where each node matches a training material with associated material properties (each node is assigned a position and vector)
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assign each material specification information to one of the nodes based on the physical property information corresponding to that material specification information; and (Qian Figure 9 the nodes are assigned their base material (material specification information to nodes) on the SOM (based on the physical property information corresponding to)
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detect a singular node located at a singular position in the map space out of the nodes that are assigned the material specification information. (Qian Page 13, Left and Figure 9 materials which same base material can show large difference in functional properties (a singular node located at a singular position) “We have identified these ‘outlier’ materials to be: two Beryllium metals and diamond. These materials are unique due to their processing method and base material composition, supporting SOM as an effective tool for identifying material similarities and dissimilarities”)
Qian does not appear to explicitly disclose: at least one memory that is configured to store instructions.
However, Guan teaches:
at least one memory that is configured to store instructions to execute an algorithm (Guan Page 19, Middle “The K-means+ algorithm, which is implemented in Java, is run on a personal computer of Dell Dimension 2300 with a Celeron CUP 1.80 GHz and a RAM of 256MB.”)
It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 15, it recites the same steps as claim 1, which is taught by Qian in view Guan. Claim 15 further recites: a non-transitory computer readable medium storing a program that causes a computer to perform the steps.
Guan teaches:
a non-transitory computer readable medium storing a program that causes a computer to perform steps. (Guan Page 19, Middle “The K-means+ algorithm, which is implemented in Java, is run on a personal computer of Dell Dimension 2300 with a Celeron CUP 1.80 GHz and a RAM of 256MB.”)
It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 2 and 16, Qian in view of Guan teaches all the elements of the parent claim 1 and 15, and further teaches
wherein the assignment of the material specification information further includes, for each of a plurality of pieces of the material specification information, assigning the material specification information to the node to which the physical property vector that is most similar to the physical property vector obtained from the physical property information corresponding to that material specification information is assigned. (Qian Page 5, Right the base material used for the specific SOM node is shown (assigning to the node in which vector is most similar), where the SOM represents functional properties derived from the material composition (physical property vector obtained from the physical property information corresponding to that material specification information))
With regard to claim 3 and 17, Qian in view of Guan teaches all the elements of the parent claim 1 and 15, and further teaches:
wherein the detection of the singular node further includes detecting, out of the nodes that are assigned the material specification information, the node whose distance from a reference position in the map space is larger than a threshold as a singular node. (Guan Page 8, Top outliers are based on threshold distance from centroid (a reference position)
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It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 4 and 11 and 18, Qian in view of Guan teaches all the elements of the parent claim 3 and 10 and 17, and further teaches:
wherein the detection of the singular node further includes:
computing a center of mass or a geometric center of the plurality of nodes that are assigned the material specification information as the reference position; and (Guan Page 8, Top outliers are based on threshold distance from centroid (center of mass)
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computing, as the threshold, a statistic value representing a magnitude of a distribution of positions of the plurality of nodes that are assigned the material specification information are assigned or a value obtained by multiplying the statistic value by a predetermined positive real number. (Guan Page 8, Top magnitude of distance (statistic value representing a magnitude) from centroid (of a distribution of positions) used as threshold
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It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 5 and 19, Qian in view of Guan teaches all the elements of the parent claim 1 and 15, and further teaches wherein the detection of the singular node further includes:
dividing the plurality of the nodes that are assigned the material specification information into a plurality of clusters based on the material specification information; and (Qian Page 9, Left the base material itself can also be grouped on the SOM (dividing nodes assigned the material specification into clusters), including identifying a material that is far away from its grouping “It is important to note that although this point is located in a separate cluster from the other surrounding points, it actually belongs to the same light blue cluster as the other carbide-based materials in the lower right in Fig. 9.”, and Page 7, Right similar materials themselves are a grouping, and distance from other similar materials are readily identified “Upon further visual analysis of the location of similar materials in the cluster maps, several interesting materials stand out that are located farther away from other similar materials.”)
detecting, for each of the plurality of the clusters, the singular node out of the nodes belonging to the cluster based on a distribution of positions of the nodes in the map space included in the cluster. (Guan Page 8, Top outliers are based on threshold distance from centroid (a reference position)
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It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 6 and 20, Qian in view of Guan teaches all the elements of the parent claim 1 and 15, and further teaches:
wherein the at least one processor is configured to further to generate a map image showing each of the nodes arranged in the map space,
wherein the map image includes an indication indicating the singular node. (Qian Figure 9 outliers are indicated
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With regard to claim 7, Qian in view of Guan teaches all the elements of the parent claim 6, and further teaches:
wherein the indication indicating the singular node indicates the material specification represented by the material specification information assigned to the singular node, the physical properties represented by the physical property vector assigned to the singular node, or both. (Qian Figure 9 outliers are indicated along with the base material (the material specification information assigned)
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With regard to claim 10, Qian teaches all the elements of the parent claim 8, and does not appear to explicitly disclose: wherein the detection of the singular node further includes detecting, out of the nodes that are assigned the material specification information, the node whose distance from a reference position in the map space is larger than a threshold as a singular node.
However, Guan teaches:
wherein the detection of the singular node further includes detecting, out of the nodes that are assigned the material specification information, the node whose distance from a reference position in the map space is larger than a threshold as a singular node. (Guan Page 8, Top outliers are based on threshold distance from centroid (a reference position)
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It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
With regard to claim 12, Qian teaches all the elements of the parent claim 8, and does not appear to explicitly disclose: wherein the detection of the singular node further includes: dividing the plurality of the nodes that are assigned the material specification information into a plurality of clusters based on the material specification information; and detecting, for each of the plurality of the clusters, the singular node out of the nodes belonging to the cluster based on a distribution of positions of the nodes in the map space included in the cluster.
However, Guan teaches:
dividing the plurality of the nodes that are assigned the material specification information into a plurality of clusters based on the material specification information; and (Qian Page 9, Left the base material itself can also be grouped on the SOM (dividing nodes assigned the material specification into clusters), including identifying a material that is far away from its grouping “It is important to note that although this point is located in a separate cluster from the other surrounding points, it actually belongs to the same light blue cluster as the other carbide-based materials in the lower right in Fig. 9.”, and Page 7, Right similar materials themselves are a grouping, and distance from other similar materials are readily identified “Upon further visual analysis of the location of similar materials in the cluster maps, several interesting materials stand out that are located farther away from other similar materials.”)
detecting, for each of the plurality of the clusters, the singular node out of the nodes belonging to the cluster based on a distribution of positions of the nodes in the map space included in the cluster. (Guan Page 8, Top outliers are based on threshold distance from centroid (a reference position)
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It would have been obvious to one of ordinary skill in the art to combine the method of analyzing materials using SOM disclosed using a local computer by Qian with the execution of mathematical algorithm with a memory disclosed by Guan. One of ordinary skill in the art would have been motivated to make this modification in order analyze data for product design (Guan Page 21 “For medical application, K-means+ can be used to group diseases by their symptoms, this could help to find effective treatments”).
Examiner General Comments
With regard to the prior art rejection(s), any cited portion of the relied upon reference(s), either by pointing to specific sections or as quotations, is intended to be interpreted in the context of the reference(s) as a whole as would be understood by one of ordinary skill in the art. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention since the entire reference is considered to provide disclosure relating to the cited portions. Further, the claims and only the claims form the metes and bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner’s notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent and spirit of compact prosecution.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALFRED H. WECHSELBERGER whose telephone number is (571)272-8988. The examiner can normally be reached M - F, 10am to 6pm.
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/ALFRED H. WECHSELBERGER/ExaminerArt Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
Prosecution Insights