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 .
DETAILED ACTION
Status of Claims
The following is a FINAL OFFICE ACTION in response to applicant’s amendments to and response for Application #17/948,488, filed on 07/29/2025.
Claims 1, 3-17, and 19-22 are now pending and have been examined.
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, 3-17, and 19-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The rationale for this finding is explained below.
Per Step 1 of the analysis, the claims are analyzed to determine if they are directed to statutory subject matter. Claim 1 claims a method, or process. A process is a statutory category for patentability. Claim 11 claims a device comprising a memory and processor. Therefore, the device is interpreted as an apparatus. An apparatus is a statutory category for patentability. Claim 17 claims a computer program product comprising a non-transitory computer-readable storage medium. Therefore, the claim is interpreted as an article of manufacture. An article of manufacture is a statutory category for patentability. The claim is also in conformity with the Kappos Memorandum of 2010 regarding medium claims, as it includes the phrase “non-transitory.”
Per Step 2A, Prong 1 of the analysis, the examiner must now determine if the claims are directed to an abstract idea or eligible subject matter. In the instant case, the independent claims are directed towards an abstract idea. Specifically, claims 1 and 17 are directed to “extracting the material names from the one or more material sources (that comprise different departments within an entity and with each of the material names identifying a material used during by the entity- claim 11 only), preprocessing the material names and removing extraneous data from one or more of the material names, matching the material names with one or more safety data sheet material names, for each of the material names the matching comprises determining one or more classification levels of the material name with the classifications comprising a number of fundamental words in the material name that are sequentially together, comparing the one or more classification levels to the safety data sheet material names, for each safety data sheet material name that matches one of the classification levels, assigning a score based on which classification level matches the safety data sheet material name, during the manufacturing of the product.” The claims are directed to an abstract idea, namely a mental process. A human operator with access to the material sources and safety data sheets could easily analyze the sources, extract the material names, remove extraneous data from the names, identify and compare the material name to names in a safety sheet, determine one or more classification levels of the material name with the classifications comprising a number of fundamental words being sequentially together, compare the classification levels to the safety data sheet material names, and determining a score could be done both as part of a mental process or using a specific mathematical formula. This process includes making a judgment or conclusion after analyzing and comparing the data sets and making calculations. Therefore, the claims are directed to an abstract idea, specifically a mental process. The processing circuitry and memory automate the abstract idea using a computer. Claim 11 adds “while manufacturing a product using the materials, determining one of the materials that is affected by the change in a governmental regulation. This is also considered part of the mental process since the time during which the mental process is performed being “during manufacturing” does not change the analysis since this is only descriptive of the time frame and what is occurring. There is no set of steps that describe an actual product being manufactured. This is no different than stating that a determining step is occurring “while other manufacturing is being conducted at the facility.” The determining step itself involves only analysis of the material names and comparison to current regulations to identify any changes that are applicable to the materials being used. Claims 11 and 17 add the calculating of a probability that the safety data sheet names match the material names. This calculation could also be done as part of the mental process either completely mentally or with the aid of such as pen and paper.
Per Step 2A, Prong 2 of the analysis, the examiner must now determine if the claims integrate the abstract idea into a practical application. The additional elements of the claims include the recitation of “processing circuitry,” “memory circuitry,” and a “computer program product.” However, these components are considered generic recitations of technical elements which are recited at a high level of generality. These components are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and do not integrate the abstract idea into a practical application. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The claims also recite the additional elements of “during the manufacturing of the product, receiving a request for information about one of the material names,” and “transmitting an output for display on a user device to display the material name that is requested, the matching safety data sheet material names, and the score…” in claim 1, and “generating a display comprising the material names…probability” in claims 11 and 17. While the claims do not specify that this would be electronically over a network, it is assumed as the steps are performed by a computer. Absent any further detail, these additional elements are considered “receiving and/or transmission of data over a network,” which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network” citing OIP Techs v Amazon.com, buySAFE v Google. Therefore, the transmittal and generate for display steps do not integrate the abstract idea into a practical application.
Per Step 2B of the analysis, the examiner must now determine if the claims include limitations that are “significantly more” than the abstract idea by demonstrating an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The additional elements of the claims include the recitation of “processing circuitry,” “memory circuitry,” and a “computer program product.” However, these components are considered generic recitations of technical elements which are recited at a high level of generality. These components are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and are not considered significantly more than the abstract idea itself. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The claims also recite the additional elements of “during the manufacturing of the product, receiving a request for information about one of the material names,” and “transmitting an output for display on a user device to display the material name…” in claim 1, and “generating a display comprising the material names…probability” in claims 11 and 17. While the claims do not specify that this would be electronically over a network, it is assumed as the steps are performed by a computer. Absent any further detail, these additional elements are considered “receiving and/or transmission of data over a network,” which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network” citing OIP Techs v Amazon.com, buySAFE v Google. Therefore, the transmittal and generate for display steps are not considered significantly more.
When considered as an ordered combination, the claims still are considered to be directed to an abstract idea. The claims recite the logical set of steps for extracting material names from sources, removing extraneous data, selecting and comparing the name to the safety data sheet material names, identifying names that match and if needed calculating a probability. Therefore, the ordered combination does not lead to a determination of significantly more.
When considering the dependent claims, claim 3 is considered part of the abstract idea as calculating a probability and listing names in a ranked order could be done as a set of mental steps. Claim 4 is considered “receiving and/or transmission of data over a network,” which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network” citing OIP Techs v Amazon.com, buySAFE v Google, and not significantly more. Claim 5 is considered part of the abstract idea, and the “parsing” step is considered conventional computer functioning and the examiner takes Official Notice that it is old and well known in the computer arts at the time of the effective filing date of this application to parse data in a table for analysis. Claims 6-7 are considered part of the abstract idea as pattern matching and removing attributes can be done as a set of mental steps. Claim 8 is considered part of the abstract idea, and the “tokenization,” absent further detail, is considered conventional computer functioning and the examiner takes Official Notice that it is old and well known in the computer arts at the time of the effective filing date of this application to apply tokenization to data. Claim 9 is considered “receiving and/or transmission of data over a network,” which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network” citing OIP Techs v Amazon.com, buySAFE v Google, and not significantly more. Claim 10 is considered part of the abstract idea, as updating the data repository can be done as a mental process with manual actions if a paper data repository or with the aid of an input means if electronic. Claim 14 is considered part of the abstract idea, as the steps could be done as part of the mental process when analyzing the data and making a judgment. Claim 21 as amended is considered part of the abstract idea, as the specific details as to what type of score is awarded or when it is awarded does not change the analysis that determination of a score based on analysis, comparison, and calculations is considered part of the mental process. Claim 22 is considered part of the abstract idea, as gathering information from different areas is considered part of what could be done as a mental process, and if it was done over some kind of electronic network it would be considered “receiving and/or transmission of data over a network,” which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network” citing OIP Techs v Amazon.com, buySAFE v Google, and not significantly more. The other dependent claims mirror those already discussed above.
Therefore, claims 1, 3-17, and 19-22 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. Vs. CLS Bank International et al., 2014 (please reference link to updated publicly available Alice memo at http://www.uspto.gov/patents/announce/alice_pec_25jun2014.pdf as well as the USPTO January 2019 Updated Patent Eligibility Guidance.)
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(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 5-8, 10, 17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1.
Regarding Claim 1, Miller teaches:
A computer-implemented method) for matching material names from one or more material sources with data sheet material names from one or more data sheet sources, the method comprising:
extracting, using processing circuitry, the material names from the one or more material sources (see at least [0061] and [0172] in which product names are extracted from sources; see also [0121], [0182], [0203], [0353], [0418], [0431], and [0502] which clearly show that the products can be a raw material or other material)
preprocessing, using the processing circuitry, the material names and removing extraneous data from one or more of the material names (see [0172] in which redundant, incomplete, incorrect, inaccurate, irrelevant, and duplicate data is removed or corrected)
matching the material names with one or more safety data sheet material names (see [0064] in which the query term is compared to the PIDC data set and the terms in the data set with sufficient similarity are matched)
determining, using the processing circuitry, a probability that the material name matches the safety data sheet material names (see [0064] in which only matching terms with sufficient similarity are identified, and therefore there would need to be some kind of standard of probability in order to determine the similarity is sufficient)
receiving a request for information about one of the material names (see at least [0064] in which the computer system receives and evaluation submission from an end user)
in response to receiving the request, transmitting, using processing circuitry, an output for display on a user device to display the material name that is requested, and the matching data sheet material names (see at least [0301] in which the reporting of results is done via transmittal and display on a GUI of a user device)
Miller, however, does not appear to specify:
safety data sheet material names, safety sheet data sources
Stoettinger teaches:
safety data sheet material names, safety sheet data sources (see Abstract, Figure 2A which shows product attributes to include safety, [0024]-[0029] which teach a datastore, and at least [0031]-[0036] in which the name input query is compared to stored lists of dangerous materials and products; the examiner notes that a database with lists of dangerous materials would also inherently indicate which materials are safe by virtue of them not being indicated as dangerous)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Stoettinger with Miller because Miller already teaches other product attributes in the material name comparison and matching, and further mentions in [0216] the safe use of the materials, and a safety data sheet for matching would allow for the materials used by the inquiring party to be verified as safe for use.
Miller andStoettinger, however, does not appear to specify:
determining one or more classification levels of the material name with the classifications comprising a number of fundamental words in the material name that are sequentially together
comparing the one or more classification levels to the safety data sheet material names, for each safety data sheet material name that matches one of the classification levels, assigning a score based on which classification level matches the safety data sheet material name
Zhou teaches:
determining one or more classification levels of the material name with the classifications comprising a number of fundamental words in the material name that are sequentially together and comparing the one or more classification levels to the safety data sheet material names, for each safety data sheet material name that matches one of the classification levels, assigning a score based on which classification level matches the safety data sheet material name (see [0020]-[0022] and especially [0026]-[0030], [0048]-[0051], and [0055]-[0056] in which number of words that match in sequential order between phrases is used to determine a probability score for the matching of the phrases)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Zhou with Miller and Stoettinger because Miller already teach using similarity matching between material name terms in order to determine that the right materials are used and teaches a probability of match, and using scores based on similar words in sequential order would provide a higher likelihood that the matching material names are indeed associated with the same material, leading to a safer and higher quality product.
**The examiner notes that while the cited reference does not include the term “classification level,” the claim itself describes the classifications as comprising “a number of fundamental words in the material name that are sequentially together.” Therefore, it is not clear what the classification and classification level actually is other than “a number of fundamental words in the material name that are sequentially together.” Since Zhou uses threshold levels and number of words in a phrase in sequential order, Zhou is determined to read on “classification levels” as currently written and described in the claims.**
Miller, Stoettinger, and Zhou, however, does not appear to specify:
during the manufacturing of the product receiving a request for information about one of the material names
Miller does however teach receiving of a request for information on one or more material names in [0064]. Further, Miller teaches in such as [0502] the materials to include raw materials and concerns over regulatory compliance. And, Stoettinger clearly teaches in at least [0031]-[0036] a name input query that is compared to lists of dangerous materials and products. Further, the claim steps do not include any active set of steps that describe manufacturing of a product, and the comparison and scoring using the material name is only described in the end as being reported or transmitted. There is no active manufacturing that is then altered or changed upon any kind of dynamic determination that a material name may or may not be able to be or should not be used based on various factors. The fact that the request is being received “during the manufacturing of a product” absent further detail, is given little patentable weight and considered non-functional descriptive language. Manufacturing of a product can occur even continuously for weeks and months in manufacturing facilities.
Therefore, it would be obvious to one of ordinary skill in the art to combine during the manufacturing of the product receiving a request for information about one of the material names with Miller, Stoettinger, and Zhou because Miller does however teach receiving of a request for information on one or more material names in [0064] and teaches in such as [0502] the materials to include raw materials and concerns over regulatory compliance, and Stoettinger clearly teaches in at least [0031]-[0036] a name input query that is compared to lists of dangerous materials and products, and receiving a request while a product is being manufactured would provide some relevance to the result as the report could potentially be applied to the manufacturing of the product at some point.
Regarding Claim 5, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller further teaches:
wherein extracting the material names from the one or more material sources comprises analyzing the one or more material sources for data in extensible markup language (XML) and parsing the xml data for the material names that are in tables (see [0054] in which the processing of the data when analyzing the sources includes XML data and data tables; the examiner notes that analysis of the XML data and data tables would inherently include parsing)
Regarding Claim 6, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller further teaches:
wherein extracting the material names from the one or more material sources comprises applying pattern matching to sections of text of the one or more material sources and identifying the material names (see [0218] which specifically teaches pattern matching when comparing the terms to the database terms)
Regarding Claim 7, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller further teaches:
wherein preprocessing the material names comprises removing attributes from the material names including colors, types, and classes (see [0134], [0172], [0267], and [0272]-[0274] in which data cleansing techniques and attribute removal from data is discussed. The citations do not specifically teach the removal of colors, types, and classes. However, the examiner takes Official Notice that it is old and well known in the computer arts for data cleansing and removal techniques to include removal of almost any aspect of data that the programmer desires. Companies such as Google, Microsoft, and IBM have used such techniques for at least a decade prior to the effective filing date of this application. Therefore, it would be obvious to one of ordinary skill in the art to combine removing attributes…including colors, types, and classes with Miller and Stoettinger because Miller already teaches data cleansing techniques and attribute removal from data and in such as [0134] includes the removal of specified terms and categories, and removing colors, types, and classes would allow for a better ability to match the material names by minimizing extraneous differences in the data.
Regarding Claim 8, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller further teaches:
wherein preprocessing the material names comprises applying tokenization (see at least [0061]-[0063] in which tokenization is taught) and removing punctuation from the material names (see [0271] in which data cleansing and preprocessing can include punctuation removal)
Regarding Claim 10, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller further teaches:
updating the data repository by linking a selected one of the matching safety data sheet material names with the material name (see [0117], [0124], [0160], [0194], [0197], and [0396])
Regarding Claim 17, Miller teaches:
A computer program product…comprising:
extracting the material names from the one or more material sources (see at least [0061] and [0172] in which product names are extracted from sources; see also [0121], [0182], [0203], [0353], [0418], [0431], and [0502] which clearly show that the products can be a raw material or other material)
preprocessing the material names and removing extraneous data from one or more of the material names (see [0172] in which redundant, incomplete, incorrect, inaccurate, irrelevant, and duplicate data is removed or corrected)
selecting one of the material names and determining a classification based on fundamental words in the material name (see at least [0008], [0056], [0159], and [0434] in which classification of the material is also determined based on the semantic analysis)
comparing the material name that is selected with the data sheet material names, identifying the data sheet material names that match the classification of the material name (see [0064] in which the query term is compared to the PIDC data set and the terms in the data set with sufficient similarity are matched)
calculating a probability that the material name matches the safety data sheet material names (see [0064] in which only matching terms with sufficient similarity are identified, and therefore there would need to be some kind of standard of probability in order to determine the similarity is sufficient)
generating an output for display on a user device, the display comprises the material name, the matching data sheet material names (see at least [0301] in which the reporting of results is done via transmittal and display on a GUI of a user device)
Miller, however, does not appear to specify:
safety data sheet material names, safety sheet data sources
Stoettinger teaches:
safety data sheet material names, safety sheet data sources (see Abstract, Figure 2A which shows product attributes to include safety, [0024]-[0029] which teach a datastore, and at least [0031]-[0036] in which the name input query is compared to stored lists of dangerous materials and products; the examiner notes that a database with lists of dangerous materials would also inherently indicate which materials are safe by virtue of them not being indicated as dangerous)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Stoettinger with Miller because Miller already teaches other product attributes in the material name comparison and matching, and further mentions in [0216] the safe use of the materials, and a safety data sheet for matching would allow for the materials used by the inquiring party to be verified as safe for use.
Miller andStoettinger, however, does not appear to specify:
assigning a highest score to a complete match of the classification, assign a lower score to a partial match of the classification
the probability based on the number of words that are sequentially matched
Zhou teaches:
assigning a highest score to a complete match of the classification, assign a lower score to a partial match of the classification (see [0026]-[0030], [0048]-[0051], and [0055]-[0056] in which the match reaching a first threshold of match is assigned a first probability score, and when a higher match threshold is reached a higher match score is assigned)
the probability based on the number of words that are sequentially matched (see [0020]-[0022] and especially [0026]-[0030], [0048]-[0051], and [0055]-[0056] in which number of words that match in sequential order between phrases is used to determine a probability score for the matching of the phrases)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Zhou with Miller and Stoettinger because Miller already teach using similarity matching between material name terms in order to determine that the right materials are used and teaches a probability of match, and using scores based on similar words in sequential order would provide a higher likelihood that the matching material names are indeed associated with the same material, leading to a safer and higher quality product.
Regarding Claim 19, the combination of Miller, Stoettinger, and Zhou teaches:
the computer program product of claim 17
Miller further teaches:
wherein preprocessing the material names comprises removing attributes from the material names including colors, types, and classes (see [0134], [0172], [0267], and [0272]-[0274] in which data cleansing techniques and attribute removal from data is discussed. The citations do not specifically teach the removal of colors, types, and classes. However, the examiner takes Official Notice that it is old and well known in the computer arts for data cleansing and removal techniques to include removal of almost any aspect of data that the programmer desires. Companies such as Google, Microsoft, and IBM have used such techniques for at least a decade prior to the effective filing date of this application. Therefore, it would be obvious to one of ordinary skill in the art to combine removing attributes…including colors, types, and classes with Miller and Stoettinger because Miller already teaches data cleansing techniques and attribute removal from data and in such as [0134] includes the removal of specified terms and categories, and removing colors, types, and classes would allow for a better ability to match the material names by minimizing extraneous differences in the data.
Regarding Claim 20, the combination of Miller, Stoettinger, and Zhou teaches:
the computer program product of claim 17
Miller further teaches:
wherein preprocessing the material names comprises applying tokenization (see at least [0061]-[0063] in which tokenization is taught) and removing punctuation from the material names (see [0271] in which data cleansing and preprocessing can include punctuation removal)
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1 and in further view of Biro, et al., Pre-Grant Publication No. 2019/0205833 A1.
Regarding Claim 3, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller, Stoettinger, and Zhou, however, does not appear to specify:
listing the safety data sheet material names that match the material name in a ranked order based on the probability
Biro teaches:
listing the safety data sheet material names that match the material name in a ranked order based on the probability (see Figure 3 and [0032] in which the matching products are listed in a ranked order based on probability of BOM match)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Biro with Miller and Stoettinger because Miller already teaches identifying and reporting material name comparison and matching and displaying on a GUI, and listing results by ranked probability of match would lead to ease of use and interaction by the viewer and ability to identify and view the likely best results first.
**The examiner notes that Miller and Stoettinger have already been shown to teach material names and safety sheet names, and therefore Biro is being used to teach the other aspects of claim 3.**
Regarding Claim 4, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller, Stoettinger, and Zhou, however, does not appear to specify:
displaying the safety data material names that have a probability above a predetermined amount
Biro teaches:
displaying the safety data material names that have a probability above a predetermined amount (see Figure 3 and [0032] in which the matching products are listed in a ranked order based on probability of BOM match, and only those above a threshold BOM match score are displayed)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Biro with Miller and Stoettinger because Miller already teaches identifying and reporting material name comparison and matching and displaying on a GUI, and listing results by ranked probability of match for those with scores above a threshold would lead to ease of use and interaction by the viewer and ability to identify and view the likely best results first.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1 and in further view of Ohashi, et al., Pre-Grant Publication No. 2007/0043980 A1.
Regarding Claim 9, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller, Stoettinger, and Zhou, however, does not appear to specify:
displaying a predetermined number of the safety data sheet material names that match the material name
Ohashi teaches:
displaying a predetermined number of the safety data sheet material names that match the material name (see Figure 6 and [0054] in which a predetermined number of results are displayed on the GUI in response to the query matching)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Ohashi with Miller, Stoettinger, and Zhou because Miller already teaches identifying and reporting material name comparison and matching and displaying on a GUI, and listing a predetermined number of results would lead to better user experience by not being overwhelmed by potentially a large number of results and allowing the user to focus on the highest quality results.
**The examiner notes that Miller and Stoettinger have already been shown to teach material names and safety sheet names, and therefore Ohashi is being used to teach the other aspects of the claim.**
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1 and in further view of Official Notice.
Regarding Claim 22, the combination of Miller, Stoettinger, and Zhou teaches:
the method of claim 1
Miller, Stoettinger, and Zhou, however, does not appear to specify:
wherein extracting the material names from the one or more material sources comprises gathering the information from different areas within a business that manufactures the product
The examiner, however, takes Official Notice that it is old and well known in the commerce arts to use information and data from different areas within a business in order to conduct further analysis and make decisions regarding the business, its products, ordering of supplies, safety and compliance determinations, and dozens of other such possibilities. Companies and businesses of all areas would use their own data inherently both because it is available and because it is relevant to their business! Such businesses have done so for at least a decade or two prior to the effective filing date of the application.
Therefore, it would be obvious to one of ordinary skill in the art to combine wherein extracting the material names from the one or more material sources comprises gathering the information from different areas within a business that manufactures the product with Miller, Stoettinger, and Zhou because Miller and Stoettinger already teach a company that manufactures materials, and using data from their own business to make further determinations would use available and proprietary data which would also be the most relevant and accurate for that same business.
Claims 11-13 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Clark, et al., Pre-Grant Publication No. 2020/0050620 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1.
Regarding Claim 11, Miller teaches:
A computing device comprising:
extracting material names from a plurality of material sources (see at least [0061] and [0172] in which product names are extracted from sources; see also [0121], [0182], [0203], [0353], [0418], [0431], and [0502] which clearly show that the products can be a raw material or other material)
comparing the material names with data sheet material names from a plurality of data sheet sources (see [0064] in which the query term is compared to the PIDC data set and the terms in the data set with sufficient similarity are matched)
identifying the data sheet material names that match at least one word of the material name (see [0064] in which the query term is compared to the PIDC data set and the terms in the data set with sufficient similarity are matched)
calculating a probability that the matching safety data sheet material names match the material name (see [0064] in which only matching terms with sufficient similarity are identified, and therefore there would need to be some kind of standard of probability in order to determine the similarity is sufficient)
generating a display comprising material names and the matching data sheet material names (see at least [0301] in which the reporting of results is done via transmittal and display on a GUI of a user device)
Miller, however, does not appear to specify:
safety data sheet material names, safety sheet data sources
Stoettinger teaches:
safety data sheet material names, safety sheet data sources (see Abstract, Figure 2A which shows product attributes to include safety, [0024]-[0029] which teach a datastore, and at least [0031]-[0036] in which the name input query is compared to stored lists of dangerous materials and products; the examiner notes that a database with lists of dangerous materials would also inherently indicate which materials are safe by virtue of them not being indicated as dangerous)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Stoettinger with Miller because Miller already teaches other product attributes in the material name comparison and matching, and further mentions in [0216] the safe use of the materials, and a safety data sheet for matching would allow for the materials used by the inquiring party to be verified as safe for use.
Miller and Stoettinger, however, does not appear to specify:
while manufacturing a product using materials, determining one of the materials that is affected by a change in a governmental regulation
generating a display indicating compliance with the change in the governmental regulation
Clark teaches:
while manufacturing a product using materials, determining one of the materials that is affected by a change in a governmental regulation and generating a display indicating compliance with the change in the governmental regulation (see Figures 8-9 and 17 and [0084]-[0087] and [0111]-[0115] in which changes and new regulatory compliances associated with the manufacture of a product are detected, and they can apply to the materials, procedures, and other aspects of manufacture, and in response a notification of the existence of the new regulation and compliance or non-compliance is transmitted and displayed to the user; see also [0111]-[0115] in which the detection of a change in government regulation is done in regards to current dynamic business operations of the manufacturer or business, and is not simply an analysis of historical data)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Clark with Miller and Stoettinger because Stoettinger already teaches safety determination based on comparison to a stored list of dangerous materials that are regulated, and being aware of new changes would ensure that the analysis of the materials is up to date and any resulting non-compliance that was previously allowed is brought to attention right away before non-compliant product is actually manufactured.
**The examiner notes that Miller and Stoettinger already teach material names in the manufacture of a product, so Clark is being used to meet the other limitations including the governmental regulation change being detected during an actual current business operation.**
Miller, Stoettinger, and Clark, however, does not appear to specify:
determining a score for each of the safety data sheet material names that match with the size of the score based on the number of words in sequence that match with the score comprising a highest score for a full match with the material name, a lower score for a partial match with the material name
Zhou teaches:
determining a score for each of the safety data sheet material names that match with the size of the score based on the number of words in sequence that match with the score comprising a highest score for a full match with the material name, a lower score for a partial match with the material name (see [0020]-[0022], [0026]-[0030], [0048]-[0051], and [0055]-[0056] in which number of words that match in sequential order between phrases is used to determine a probability score for the matching of the phrases and in which the match reaching a first threshold of match is assigned a first probability score, and when a higher match threshold is reached a higher match score is assigned)
It would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine Zhou with Miller, Stoettinger, and Clark because Miller already teach using similarity matching between material name terms in order to determine that the right materials are used, and using scores based on similar words in sequential order would provide a higher likelihood that the matching material names are indeed associated with the same material, leading to a safer and higher quality product.
Miller, Stoettinger, Clark, and Zhou, however, does not appear to specify:
generating a display, the display comprising…the score of the corresponding probability
Miller does already teach a display of matching material name data in such as [0301]. Zhou already teaches the score of the probability of match. Therefore, it would be obvious to one of ordinary skill in the art before the effective date of filing of the application to combine with generating a display, the display comprising…the score of the corresponding probability with
Miller, Stoettinger, Clark, and Zhou because Miller already teach using similarity matching between material name terms in order to determine that the right materials are used, and Zhou already teaches using scores based on similar words in sequential order would provide a higher likelihood that the matching material names are indeed associated, and displaying the scores would allow the user to be well aware of the goodness of match and give more certainty to the user of the right materials being used.
Miller, Stoettinger, Clark, and Zhou, however, does not appear to specify:
material sources that comprise different departments within an entity and with each of the material names identifying a material used during by the entity)
However these differences are only found in the nonfunctional descriptive data that is not functionally involved in the steps recited in claim 11. In fact, different departments within the entity are never mentioned again in the claims, and any findings regarding a change in government regulation are not then in any way disseminated to, applied to, or in any way used on a department level. The “departments” are simply described as a material name source. Thus, this descriptive material will not distinguish the claimed invention from the prior art in terms of patentability, see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994).
Regarding Claim 12, the combination of Miller, Stoettinger, Clark, and Zhou teaches:
the computing device of claim 11
Miller further teaches:
prior to identifying the material names that match, removing one or more attributes and punctuation from the material names (see [0271] in which data cleansing and preprocessing can include punctuation removal) with the attributes comprising color, type, and class see [0134], [0172], [0267], and [0272]-[0274] in which data cleansing techniques and attribute removal from data is discussed. The citations do not specifically teach the removal of colors, types, and classes. However, the examiner takes Official Notice that it is old and well known in the computer arts for data cleansing and removal techniques to include removal of almost any aspect of data that the programmer desires. Companies such as Google, Microsoft, and IBM have used such techniques for at least a decade prior to the effective filing date of this application. Therefore, it would be obvious to one of ordinary skill in the art to combine removing attributes…including colors, types, and classes with Miller and Stoettinger because Miller already teaches data cleansing techniques and attribute removal from data and in such as [0134] includes the removal of specified terms and categories, and removing colors, types, and classes would allow for a better ability to match the material names by minimizing extraneous differences in the data.
Regarding Claim 13, the combination of Miller, Stoettinger, Clark, and Zhou teaches:
the computing device of claim 11
Miller further teaches:
wherein extracting the material names from the one or more material sources comprises identifying the one or more material sources for tables that comprise extensible markup language (XML) and parsing the material names from the tables (see [0054] in which the processing of the data when analyzing the sources includes XML data and data tables; the examiner notes that analysis of the XML data and data tables would inherently include parsing)
Regarding Claim 15, the combination of Miller, Stoettinger, Clark, and Zhou teaches:
the computing device of claim 11
Miller further teaches:
wherein extracting the material names from the one or more material sources comprises applying pattern matching to sections of text of the one or more material sources and identifying the material names (see [0218] which specifically teaches pattern matching when comparing the terms to the database terms)
Regarding Claim 16, the combination of Miller, Stoettinger, Clark, and Zhou teaches:
the computing device of claim 11
Miller further teaches:
updating a data repository by linking a selected one of the matching safety data sheet material names with the material name (see [0117], [0124], [0160], [0194], [0197], and [0396])
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Miller, et al., Pre-Grant Publication No. 2022/0253871 A1 in view of Stoettinger, et al., Pre-Grant Publication No. 2020/0364495 A1 and in further view of Clark, et al., Pre-Grant Publication No. 2020/0050620 A1 and in further view of Zhou, Pre-Grant Publication No. 2020/0273447 A1 and in further view of Official Notice.
Regarding Claim 14, the combination of Miller, Stoettinger, Clark, and Zhou teaches:
the computing device of claim 11
Miller, Stoettinger, Clark, and Zhou, however, does not appear to specify:
identifying a combination of words that are sequentially listed in the material name
determining if there is a match between the combination and the safety data sheet material names
when there is no match, dividing the combination into a smaller combination of the words that are sequentially listed in the material name
determining if there is a match between the smaller combination and the safety data sheet material names
The examiner, however, takes Official Notice that it is old and well known in the advertising arts to use different combinations and/or sizes of words and phrases in order to match a query or term to a database. Companies such as IBM, SAP, Microsoft, and Google have done so for at least a decade prior to the effective filing date of the application.
Therefore, it would be obvious to one of ordinary skill in the art to combine identifying a combination of words that are sequentially listed in the material name, determining if there is a match between the combination and the safety data sheet material names, when there is no match, dividing the combination into a smaller combination of the words that are sequentially listed in the material name, and determining if there is a match between the smaller combination and the safety data sheet material names with Miller, Stoettinger, Clark, and Zhou because Miller and Stoettinger already teach matching of word combinations in a material name to a repository of material names as in Figure 6 and [0355]-[0359] of Miller and Figure 2B and [0032]-[0033] of Stoettinger, and making the combination of words smaller would allow for a broader search and possibly more or some results, leading to better outcomes for the user.
**The examiner notes that Miller and Stoettinger have already been shown to teach material names and safety sheet names, and therefore Official Notice is being used to teach the other aspects of the claim.**
**The examiner notes that claim 21 as amended was not given a prior art rejection, but there is a standing 101 rejection on the claim.**
Response to Arguments