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 .
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. abstract idea) without anything significantly more.
Step 1: Claims 1-18 are directed to a method, claim 19 is directed to a system, and claim 20 is directed to a non-transitory computer-readable recording medium. Therefore, claims 1-20 are directed to patent eligible categories of invention.
Step 2A, Prong 1:
The claim(s) recite(s) (mathematical relationships/formulas, mental process or certain methods of organizing human activity). Specifically the independent claims recite:
mental process: as drafted, the claim recites the limitations of collecting, organizing, and presenting information about the status of a project, and responding to inquires based on the information which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “a computing system,” nothing in the claim precludes the determining step from practically being performed in the human mind. For example, but for the “a computing system” language, the claim encompasses the user manually receiving, manipulating, and outputting data related to a project. The mere nominal recitation of a generic computing devices does not take the claim limitation out of the mental processes grouping. This limitation is a mental process.
(c) certain methods of organizing human activity: The claim as a whole recites a method of organizing human activity. The claimed invention is a method that allows for users to report on the status of a project which is a method of managing interactions between people (the management of people, tasks, and fundamental business/commercial interaction). Thus, the claim recites an abstract idea.
Dependent claims 2, 9, 10, 16-18, further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Dependent claims 3-8, 11-15, will be evaluated under Step 2A, Prong 2 below.
Step 2A, Prong 2: Independent claims 1, 19, 20, do not integrate the judicial exception into a practical application. Claim 1 is a method comprising “a computing system… a storage.” Claim 19 is a computing system that comprises “one or more processors… a memory… a storage” or “using the at least one processor and one or more machine learning algorithms.” Claim 20 is a non-transitory computer-readable recording medium comprising “a processor… a storage.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, manipulate or store data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 2, 9, 10, 16-18, further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claims 3-6, 8, 14, introduce the additional element of “a first artificial intelligence (AI model)” and “a second AI model.” This limitation provides nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Therefore, this limitation is not sufficient to prove integration into a practical application.
Dependent claims 7, 11-13, introduces the additional element of “a user terminal.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Dependent claim 15 introduces the additional element of “an internal system and an external system.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not sufficient to prove integration into a practical application.
Step 2B: Independent claims 1, 19, 20 do not comprise anything significantly more than the judicial exception. As can be seen above with respect to Step 2A, Prong 2, claim 1 is a method comprising “a computing system… a storage.” Claim 19 is a computing system that comprises “one or more processors… a memory… a storage” or “using the at least one processor and one or more machine learning algorithms.” Claim 20 is a non-transitory computer-readable recording medium comprising “a processor… a storage.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, manipulate or store data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
The additional elements of the independent claims, when considered both individually and in combination, do not comprise anything significantly more than the judicial exception.
Dependent claims 2, 9, 10, 16-18, further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which is not anything significantly more than the judicial exception.
Dependent claims 3-6, 8, 14, introduce the additional element of “a first artificial intelligence (AI model)” and “a second AI model.” This limitation provides nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Therefore, this limitation is not anything significantly more than the judicial exception.
Dependent claims 7, 11-13, introduces the additional element of “a user terminal.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Dependent claim 15 introduces the additional element of “an internal system and an external system.” This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
The additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not anything significantly more than the judicial exception.
Therefore based on the above analysis as conducted based on MPEP 2106 from the United States Patent and Trademark Office the claims are viewed as a court recognized abstract idea, are viewed as a judicial exception, does not integrate the claims into a practical application, does not provide significantly more, and does not provide an inventive concept, therefore the claims are ineligible.
Accordingly, claims 1-20 are rejected under 35 USC 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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.
Claim(s) 1, 2, 7, 10, 11, 12, 16-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Breslin et al. (US 7827448 B1).
Regarding claim 1, Breslin teaches work support method performed by a computing system, the work support method comprising: acquiring a plurality of pieces of summary information for a specific project using a plurality of data stored in a storage, the plurality of pieces of summary information being associated with different categories (Fig. 1-3, col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
generating a plurality of pieces of card-type information associated with different categories, using the plurality of pieces of summary information (Fig. 1-3, col. 3, lines 30-51, discloses receiving information from various col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
and generating status information for the specific project including at least one of the plurality of pieces of card-type information (col. 3, line 52 – col. 4, line 11, col. 4, lines 32-64, col. 7, lines 20-62, discloses the status information of various projects).
Regarding claim 2, Breslin teaches wherein the plurality of pieces of summary information include first summary information associated with a first category and second summary information associated with a second is category, the first category is associated with a plurality of data generated through a first application, and the second category is associated with a plurality of data generated through a second application (Fig. 1-3, col. 3, lines 30-51, discloses receiving information from various col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55).
Regarding claim 7, Breslin teaches after the generating the status information, receiving an inquiry related to the specific project from a user terminal (col. 4, line 50 - col. 5, line 15, disclose clicking an indicator to receive status information. Col. 5, lines 25-35, col. 6, lines 56-67, Fig. 3); generating a response to the inquiry based on the plurality of pieces of card-type information included in the status information (col. 6, lines 56- col. 7, line 10, disclose col. 4, line 50 - col. 5, line 15, disclose clicking an indicator to receive status information. Col. 5, lines 25-35, Fig. 3); and transmitting the generated response to the user terminal (col. 6, lines 56- col. 7, line 10, disclose col. 4, line 50 - col. 5, line 15, disclose clicking an indicator to receive status information. Col. 5, lines 25- col. 6, line 12, col. 9, lines 8-26, Fig. 3).
Regarding claim 10, Breslin teaches receiving user input selecting at least one piece of card-type information for generating a response from among the plurality of pieces of card-type information included in the is status information; and generating the response based on the at least one piece of card-type information selected by a user (col. 4, line 11-60, disclose selecting information and generating a response (report). Col. 4, line 61- col. 5, line 56).
Regarding claim 11, Breslin teaches after the generating the status information, receiving a request for information regarding the specific project from a user terminal; and transmitting the status information to the user terminal, wherein a portion of first card-type information included in the status information is displayed in a first output area of the user terminal, and a portion of second card-type information included in the status information is displayed in a second output area of the user terminal (Fig. 1-3, col. 3, lines 30-51, discloses receiving information from various col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 9, lines 9-25, discloses transmitting information. Col. 5, lines 2-55, col. 6, lines 38-55).
Regarding claim 12, Breslin teaches after the generating the status information, receiving a request for information regarding the specific project from a user terminal (col. 6, lines 45-55, discloses status summaries in the reporting data store when a website is refreshed. Col. 6, lines 56- col. 7, line 7, discloses requesting information); extracting periodic status information for the specific project (col. 6, lines 45-55, discloses status summaries in the reporting data store when a website is refreshed. Col. 6, lines 56- col. 7, line 7, discloses requesting status information); and transmitting the periodic status information to the user terminal (col. 9, lines 8-26, disclose transmitting information, col. 6, lines 45-55, discloses status summaries in the reporting data store when a website is refreshed. Col. 6, lines 56- col. 7, line 7, discloses requesting status information).
Regarding claim 16, Breslin teaches after the generating the status information, when a scheduled time for updating the status information arrives, additionally acquiring a plurality of pieces of summary information for io the specific project based on the plurality of data stored in the storage (col. 6, line 37- col. 7, line 7, discloses generating a status report at a specific time); and updating the status information for the specific project based on the additionally acquired summary information (col. 6, line 37- col. 7, line 7, discloses updating a status report at a specific time.).
Regarding claim 17, Breslin teaches wherein when an inquiry regarding the is specific project is received, it is determined that the scheduled time for updating the status information has arrived (col. 6, line 37- col. 7, line 7, discloses updating a status report at a specific time., col. 5, lines 4-55, discloses updating status information).
Regarding claim 18, Breslin teaches wherein when additional data related to the specific project is detected as being stored in the storage with a size exceeding a threshold, it is determined that the scheduled time for updating the status information has arrived (col. 6, line 37- col. 7, line 7, discloses updating a status report at a specific time., col. 5, lines 4-55, discloses updating status information).
Regarding claim 19, Breslin teaches one or more processors; and a memory storing a computer program executed by the one or more processors (col. 8, lines 40-57, col. 9, lines 26-31);
wherein the computer program includes instructions for operations of: acquiring a plurality of pieces of summary information for a specific project using a plurality of data stored in a storage, the plurality of pieces of summary information being associated with different categories (Fig. 1-3, col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
generating a plurality of pieces of card-type information associated with different categories using the plurality of pieces of summary information (Fig. 1-3, col. 3, lines 30-51, discloses receiving information from various col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
and generating status information for the specific project including at least one of the plurality of pieces of card-type information (col. 3, line 52 – col. 4, line 11, col. 4, lines 32-64, col. 7, lines 20-62, discloses the status information of various projects).
Regarding claim 20, Breslin teaches a non-transitory computer-readable recording medium comprising instructions (col. 8, lines 30-57, col. 9, lines 26-31);
wherein when executed by a processor, the instructions enable the processor to io perform operations of: acquiring a plurality of pieces of summary information for a specific project using a plurality of data stored in a storage, the plurality of pieces of summary information being associated with different categories (Fig. 1-3, col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
generating a plurality of pieces of card-type information associated with different categories using the plurality of pieces of summary information (Fig. 1-3, col. 3, lines 30-51, discloses receiving information from various col. 4, lines 10-60, discloses status summaries and five different categories that the information could be summed up into. col. 7, line 54- col. 8, line 8, discloses combining status summaries. Col. 5, lines 2-25, col. 6, lines 38-55);
and generating status information for the specific project including at least one of the plurality of pieces is of card-type information (col. 3, line 52 – col. 4, line 11, col. 4, lines 32-64, col. 7, lines 20-62, discloses the status information of various projects).
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) 3, 4, 8, is/are rejected under 35 U.S.C. 103 as being unpatentable over Breslin et al. (US 7827448 B1) in view of Page et al. (US 20240232752 A1).
Regarding claim 3, Breslin teaches reporting business rules to generate status summaries.
Breslin does not specifically teach an AI model.
However, Page teaches inputting text requesting information related to the specific project into a first artificial intelligence (Al) model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. ¶ 67); and acquiring the plurality of pieces of summary information through the first Al model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. ¶ 67).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using AI modeling, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Regarding claim 4, Breslin teaches reporting business rules to generate status summaries. Breslin also teaches status indicators (col. 6, lines 5-25). Breslin does not specifically teach an AI model.
However, Page teaches wherein the generating the plurality of pieces of card-type information comprises: inputting the plurality of pieces of summary information into a second Al model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. Including training another (second) model. ¶ 67); and acquiring the plurality of pieces of card-type information through the second Al model, and the second Al model is configured to output the plurality of pieces of card-type information based on the plurality of pieces of summary information (¶ 37-38, discloses inputting text to an AI model to receive specific project information. Including training another model. ¶ 67).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using AI modeling, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Regarding claim 8, the combination of Breslin and Page teach the limitations of claim 7. Breslin does not teach AI modeling. Page further teaches, wherein the generating the response to the inquiry comprises: inputting text instructing a first AI model to generate a response to the inquiry by referring to the plurality of pieces of card-type information included in the status information into the first AI model; and acquiring the response from the first AI model (¶ 66-70, discloses proving instructions to AI models and specifying the input data to be processed. ¶ 38.)
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using AI modeling, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Claim(s) 5, 6, 9, is/are rejected under 35 U.S.C. 103 as being unpatentable over Breslin et al. (US 7827448 B1) in view of Page et al. (US 20240232752 A1) in further view of Newland et al. (US 20250307775 A1).
Regarding claim 5, Breslin teaches output the plurality of pieces of card-type information using the selected at least one piece of summary information (col. 3, line 10 – col. 4, line 25, disclose
Breslin does not teach an AI model. However, Page teaches an AI model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. ¶ 67, 75).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using an AI model, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Breslin does not specifically teach calculating confidence scores. However, Newland teaches calculate confidence scores for the plurality of pieces of summary information, select at least one of the plurality of pieces of summary information based on the calculated confidence scores, and output the plurality of pieces of card-type information using the selected at least one piece of summary information, output the plurality of pieces of card-type information using the selected at least one piece of summary information (¶ 57-58, discloses calculating AI confidence scores. ¶ 80, 96-97, 116-118, 128, 332).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform confidence scores, as taught/suggested by Newland. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status. One of ordinary skill in the art would have recognized that applying the known technique of Newland would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Newland to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such confidence score features into similar systems. Further, applying a confidence score would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to have a quantitative measure of uncertainty.
Regarding claim 6, Breslin teaches status indicators and summary information (col. 2, lines 40-55, col. 4, lines 56-65, col. 5, line 20-40).
Breslin does not teach an AI model. However, Page teaches an AI model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. ¶ 67, 75).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using an AI model, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Breslin does not specifically teach a confidence score. However, Newland teaches wherein the second Al model is further configured to calculate the confidence scores for the plurality of pieces of summary information based on a frequency of overlapping keywords or words included in each of the plurality of pieces of card-type information (¶ 57-58, discloses calculating AI confidence scores. ¶ 196-197, 239-240, discloses determining the confidence level and predicting the work based on the number of times the information related to the work is applied. ¶ 80, 96-97, 116-118, 128, 332).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform confidence scores, as taught/suggested by Newland. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status. One of ordinary skill in the art would have recognized that applying the known technique of Newland would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Newland to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such confidence score features into similar systems. Further, applying a confidence score would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to have a quantitative measure of uncertainty.
Regarding claim 9, Breslin teaches status indicators and summary information. Breslin does not teach an AI model. However, Page teaches an AI model (¶ 37-38, discloses inputting text to an AI model to receive specific project information. ¶ 67, 75).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform using an AI model, as taught/suggested by Page. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Page would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Page to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such AI modeling features into similar systems. Further, applying AI modeling would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to analyze a various data sets quicker then by a human.
Breslin does not specifically teach a confidence score. However, Newland teaches wherein the first AI model is configured to generate the response to the inquiry by referring to the plurality of pieces of card-type information in descending order of confidence scores (¶ 57-58, discloses calculating AI confidence scores in ranked form or the like. ¶ 196-197, 239-240, discloses determining the confidence level and predicting the work based on the number of times the information related to the work is applied. ¶ 80, 96-97, 116-118, 128, 332).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform confidence scores, as taught/suggested by Newland. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project status. One of ordinary skill in the art would have recognized that applying the known technique of Newland would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Newland to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such confidence score features into similar systems. Further, applying a confidence score would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to have a quantitative measure of uncertainty.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Breslin et al. (US 7827448 B1) in view of Jonnalagadda (US 20240354704 A1).
Regarding claim 13, Breslin teaches status indicators and summary information. Breslin does not teach a history request. However, Jonnalagadda teaches after the generating the status information, receiving a response history request from a user terminal; extracting inquiries and responses to the inquiries; and transmitting the extracted inquiries and responses to the user terminal (¶ 3, discloses historical action, reaction, and interaction in a project management setting. ¶ 34-35, discloses receiving a search request, pulling together data, and outputting historical project data. ¶ 11, 41, 85-87).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform a history request as taught/suggested by Jonnalagadda. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project management status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Jonnalagadda would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Jonnalagadda to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such a history request features into similar systems. Further, applying a history request would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user access to pertinent data that could save time for the project.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Breslin et al. (US 7827448 B1) in view of Jonnalagadda (US 20240354704 A1) in further view of Doyle (US 20240119416 A1).
Regarding claim 14, Breslin teaches status indicators and summary information. Breslin does not teach feedback. However, Doyle teaches receiving positive or negative feedback on the responses from the user terminal; and generating training data including the positive or negative feedback, the inquiries, and the responses, wherein the training data is used to additionally train a first AI model (¶ 61-63, discloses using received feedback to train ML models. ¶ 57, 63).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform feedback as taught/suggested by Doyle. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to project management status and data reporting. One of ordinary skill in the art would have recognized that applying the known technique of Doyle would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Doyle to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such feedback features into similar systems. Further, applying feedback would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow the user the ability to use up to date thoughts to train the data.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Breslin et al. (US 7827448 B1) in view of Spector et al. (US 10331402 B1).
Regarding claim 15, Breslin teaches status indicators and summary information. Breslin does not teach searching and finding additional information under a threshold. However, Spector teaches after the generating the status information, determining whether a number of pieces of card-type information included in the status information is greater than or equal to a threshold (col. 12, line 50- col. 13, line 10, col. 14, line 60-col. 15, line 12, Col. 15, line 60 – col. 16, line 7, disclose whether a score is above a threshold.); when the number of pieces of card-type information included in the status information is less than the threshold, searching for and finding data related to the specific project in at least one of an internal system and an external system (col. 12, lines 17-50, Fig. 5A-5B, disclose the search based approach uses a search engine that searches an external internet. The knowledge base is the internal system. Col. 13, lines 10-45); additionally generating card-type information based on the found data (col. 12, lines 17-50, Fig. 5A-5B, disclose the search based approach uses a search engine to generate an answer for output. Col. 13, lines 10-45); and including the additionally generated card-type information in the status information (col. 12, lines 17-50, Fig. 5A-5B, disclose that the system relies on a search-based question answering approach. Col. 13, lines 10-45).
It would have been obvious to one of ordinary skill in the art at the time of filing to modify Breslin to include/perform the threshold limitations as taught/suggested by Spector. This known technique is applicable to the system of Breslin as they both share characteristics and capabilities, namely, they are directed to systems that have knowledge databases. One of ordinary skill in the art would have recognized that applying the known technique of Spector would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Spector to the teachings of Breslin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such threshold limitations features into similar systems. Further, applying the not met threshold limitations have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for the system to seek additional information.
Other pertinent prior art includes Sakamoto et al. (US 20250356279 A1) which discloses optimal work support according to the degree of concentration for each user engaged in work. Mori et al. (US 20200074380 A1) which discloses objectively evaluating the skill level of a target operator with respect to a work step and for allowing said target operator to learn the work efficiently.
Conclusion
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JAMIE H. AUSTIN
Examiner
Art Unit 3625
/JAMIE H AUSTIN/Primary Examiner, Art Unit 3625
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