DETAILED ACTION
This office action is in response to the communication filed on September 30, 2025. Claims 1-13 are currently pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments in Pages 7-12 of the Remarks with respect to the 101 rejection of amended claims 1-13 have been fully considered and are persuasive. The 101 rejection of claims 1-13 has been withdrawn.
Applicant's arguments in Pages 12-14 of the Remarks with respect to the 102 rejection of amended claims 1-13 have been fully considered but they are not persuasive for the following reasons:
Applicant argues that the cited prior art Boxler. does not teach or even suggest the features "accept, by user operation to the terminal device, selection of a statistical number candidate from the plurality of statistical number candidates” and “display, on the terminal device, by referring to master database, information related to an article assigned to the selected statistical number candidate by the user in the past, wherein the master database stores each of the plurality of statistical number candidates and information related to an article assigned to each of the plurality of statistical number candidates”, as recited in amended independent claim 1 and similarly recited in amended independent claims 12 and 13.
Examiner respectfully disagrees. The cited prior art Boxler discloses the argued features.
Boxler in [0072] discloses that user may select candidate codes and the GUI allows the user to view a relational database providing more information about each of the candidate codes.
Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification.
Therefore, Boxler discloses "accept, by user operation to the terminal device, selection of a statistical number candidate from the plurality of statistical number candidates”.
Boxler in [0037] and [0038] discloses server parsing resources to extract relevant information and organizing and storing it in a searchable relational database, database providing organized, searchable text resources of data sources to the user to help them during the classification process, the user views the database via a GUI on user devices, which is interpreted as a master database.
Boxler in [0072] discloses that user may select candidate codes and the GUI allows the user to view a relational database providing more information about each of the candidate codes, which is interpreted as by referring to a master database.
Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification.
Boxler in [0106] discloses GUI allowing a user to modify the classification by allowing the user to modify selections during the classification process, allowing the user to back track and review paths not originally pursued, user can select a classification previously completed to view the options he was previously presented with and may select a new option to classify, which is interpreted as displaying information related to an article assigned to the selected statistical number candidate by the user in the past.
Therefore, Boxler discloses “display, on the terminal device, by referring to master database, information related to an article assigned to the selected statistical number candidate by the user in the past, wherein the master database stores each of the plurality of statistical number candidates and information related to an article assigned to each of the plurality of statistical number candidates”.
For the above reasons, Examiner states that rejection of the current Office action is proper.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Boxler (US Pub 2024/0403340).
With respect to claim 1, Boxler discloses a search assistance device (Boxler in [0029] and [0030] discloses implementing a human-in-the-loop AI solution for classifying an object in a hierarchical classification system, user operating a device to transmit a query via an application, query including a description of an object the user wishes to classify, allowing users to quickly find a correct classification code for an object using a graphical user interface and assisted by AI) comprising:
at least one memory configured to store instructions (Boxler in [0097] discloses a computer device comprising one or more processors and computer program stored in a non-transitory computer readable medium, such as a memory, which is executed by the device to perform steps); and
at least one processor configured to execute the instructions (Boxler in [0097] discloses a computer device comprising one or more processors and computer program stored in a non-transitory computer readable medium, such as a memory, which is executed by the device to perform steps) to:
receive, from a terminal device of user, a first input related to an article as a search target (Boxler in [0029] and [0030] discloses user operating user device enters and transmits a query towards a server via a GUI, the query includes a description of an object the user wishes to classify, allowing users to quickly find a correct classification code for an object using a graphical user interface and assisted by AI; Boxler in [0042] discloses generating a query including object description and transmit the query towards server, after receiving the query server begins a classification process; [0058] discloses user indicating via the GUI to search specific sections of the classification system, server limiting the search to the relevant sections);
obtain a specification of a statistical number candidate into which the search target is classified based on the first input and classification information for each statistical number included in a statistical number group having a hierarchical structure (Boxler in [0004] and [0005] discloses harmonized system (HS) schedule being an internationally standardized system of names and numbers to classify traded products, HS schedule being used for customs tariffs and for collection of international trade statistics, HS numerical codes used for classification of goods, which is a statistical number; Boxler in [0045] discloses using object description provided by user to query AI based model embodied as a large language model (LLM) trained on very large corpora of text allowing it to recognize user’s object description to provide relevant information about the object; Boxler in [0074] discloses after viewing candidate codes a user deciding none of the codes represent the object, user providing a filter to focus search within specific chapters of the HS system; Boxler in [0075] discloses text associated with candidate codes presented to user generated by an LLM, code consist of its HS description in the schedule tree; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
display, on the terminal device, first information requesting a second input related to the search target to be additionally input in a case where a plurality of statistical number candidates is specified, and the statistical number candidate (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
accept, by user operation to the terminal device, selection of a statistical number candidate from the plurality of statistical number candidates (Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification); and
display, on the terminal device, by referring to master database, information related to an article assigned to the selected statistical number candidate by the user in the past, wherein the master database stores each of the plurality of statistical number candidates and information related to an article assigned to each of the plurality of statistical number candidates (Boxler in [0037] and [0038] discloses server parsing resources to extract relevant information and organizing and storing it in a searchable relational database, database providing organized, searchable text resources of data sources to the user to help them during the classification process, the user views the database via a GUI on user devices; Boxler in [0072] discloses that user may select candidate codes and the GUI allows the user to view a relational database providing more information about each of the candidate codes, which is by referring to a master database; Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification; Boxler in [0106] discloses GUI allowing a user to modify the classification by allowing the user to modify selections during the classification process, allowing the user to back track and review paths not originally pursued, user can select a classification previously completed to view the options he was previously presented with and may select a new option to classify, which is displaying information related to an article assigned to the selected statistical number candidate by the user in the past).
With respect to claim 2, Boxler discloses the search assistance device according to claim 1, wherein
the first information represents a question used to specify whether the search target is classified into the statistical number candidate (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification), and
the second input is an answer to the question (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification).
With respect to claim 3, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
display, on the terminal device, second information indicating a reason why the second input requested by the first information is necessary (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification).
With respect to claim 4, Boxler discloses the search assistance device according to claim 3, wherein
the second information includes at least one of the statistical number candidate related to the first information, an article name in the statistical number candidate, and an explanation for a heading of the statistical number candidate related to the first information (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification).
With respect to claim 5, Boxler discloses the search assistance device according to claim 3, wherein the at least one processor is further configured to execute the instructions to:
display, on the terminal device, the second information according to an operation on the first information (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification).
With respect to claim 6, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
display a first region capable of receiving the first input and a second region capable of receiving the second input, the second region being different from the first region (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
receive information input in the second region as the second input (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification); and
obtain a new specification of a statistical number candidate based on the second input and classification information for the statistical number candidate related to the first information requesting the second input (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification; Boxler in [0007], [0081], and [0106] discloses AI models use training data comprising history of correct classifications for similar, if not the same, products, user may change one of the assumptions or choices and server may produce a new set of candidate codes, GUI allows user to modify selection during classification process, modification allows user to back track and review paths user did not originally pursue, user can view options he was previously presented with and may select a new option).
With respect to claim 7, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
obtain the statistical number candidate into which the search target is classified based on information related to statistical numbers assigned to articles by a user in the past (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification; Boxler in [0007], [0081], and [0106] discloses AI models use training data comprising history of correct classifications for similar, if not the same, products, user may change one of the assumptions or choices and server may produce a new set of candidate codes, GUI allows user to modify selection during classification process, modification allows user to back track and review paths user did not originally pursue, user can view options he was previously presented with and may select a new option).
With respect to claim 8, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
display the statistical number candidate and the first information on a same screen (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification; Boxler in [0007], [0081], and [0106] discloses AI models use training data comprising history of correct classifications for similar, if not the same, products, user may change one of the assumptions or choices and server may produce a new set of candidate codes, GUI allows user to modify selection during classification process, modification allows user to back track and review paths user did not originally pursue, user can view options he was previously presented with and may select a new option).
With respect to claim 9, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
display, on the terminal device, in a case where a plurality of statistical number candidates is specified from among statistical numbers included in a heading hierarchy in the statistical number group having the hierarchical structure, output the first information and the statistical number candidate (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0036] discloses server obtains multiple sources of text for classification including schedule and legal notes, explanatory and legal nodes, cross rulings, and additional resources; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0073] and [0140] discloses server may update a set of candidate codes to include one or more of the headings under a particular chapter, user can select a chapter or a heading included under the chapter; Boxler in [0077] discloses candidate codes displayed to the user accompanied with and explainable AI illustrating to the user the reasoning as to why particular candidate codes were recommended; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification; Boxler in [0007], [0081], and [0106] discloses AI models use training data comprising history of correct classifications for similar, if not the same, products, user may change one of the assumptions or choices and server may produce a new set of candidate codes, GUI allows user to modify selection during classification process, modification allows user to back track and review paths user did not originally pursue, user can view options he was previously presented with and may select a new option).
With respect to claim 10, Boxler discloses the search assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to:
obtain the statistical number candidate and the first information by using a large-scale language model (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0027] discloses using large language models (LLMs) to improve classification, using LLMs to create human in the loop AI solutions that bring together the expertise of human classifiers and the computer power of AI, using LLMs to improve contextual understanding of technical terms and language used in the HS classification system, training an LLM on a large corpus of technical documents to develop models that have deep understanding of the specific language used in the HS classification system; Boxler in [0028] discloses human classifiers identifying correct classification codes and training an LLM on a large corpus of annotated data to develop models that can identify and correct errors in the classification of products).
With respect to claim 11, Boxler discloses the search assistance device according to claim 10, wherein the at least one processor is further configured to execute the instructions to:
input a prompt to the large-scale language model, the prompt including the first input, the classification information for each statistical number included in the statistical number group having the hierarchical structure, and question information as to whether the search target is classified into the statistical number, and acquire the statistical number candidate and the first information from the large-scale language model (Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0027] discloses using large language models (LLMs) to improve classification, using LLMs to create human in the loop AI solutions that bring together the expertise of human classifiers and the computer power of AI, using LLMs to improve contextual understanding of technical terms and language used in the HS classification system, training an LLM on a large corpus of technical documents to develop models that have deep understanding of the specific language used in the HS classification system; Boxler in [0028] discloses human classifiers identifying correct classification codes and training an LLM on a large corpus of annotated data to develop models that can identify and correct errors in the classification of products).
With respect to claim 12, Boxler discloses a search assistance method performed by a computer (Boxler in [0097] discloses a computer device comprising one or more processors and computer program stored in a non-transitory computer readable medium, such as a memory, which is executed by the device to perform steps), the search assistance method comprising the steps of:
receiving, from a terminal device of user, a first input related to an article as a search target (Boxler in [0029] and [0030] discloses user operating user device enters and transmits a query towards a server via a GUI, the query includes a description of an object the user wishes to classify, allowing users to quickly find a correct classification code for an object using a graphical user interface and assisted by AI; Boxler in [0042] discloses generating a query including object description and transmit the query towards server, after receiving the query server begins a classification process; [0058] discloses user indicating via the GUI to search specific sections of the classification system, server limiting the search to the relevant sections);
obtaining a specification of a statistical number candidate into which the search target is classified based on the first input and classification information for each statistical number included in a statistical number group having a hierarchical structure (Boxler in [0004] and [0005] discloses harmonized system (HS) schedule being an internationally standardized system of names and numbers to classify traded products, HS schedule being used for customs tariffs and for collection of international trade statistics, HS numerical codes used for classification of goods, which is a statistical number; Boxler in [0045] discloses using object description provided by user to query AI based model embodied as a large language model (LLM) trained on very large corpora of text allowing it to recognize user’s object description to provide relevant information about the object; Boxler in [0074] discloses after viewing candidate codes a user deciding none of the codes represent the object, user providing a filter to focus search within specific chapters of the HS system; Boxler in [0075] discloses text associated with candidate codes presented to user generated by an LLM, code consist of its HS description in the schedule tree; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
display, on the terminal device, first information requesting a second input related to the search target to be additionally input in a case where a plurality of statistical number candidates is specified, and the statistical number candidate (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
accepting, by user operation to the terminal device, selection of a statistical number candidate from the plurality of statistical number candidates (Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification); and
displaying, on the terminal device, by referring to master database, information related to an article assigned to the selected statistical number candidate by the user in the past, wherein the master database stores each of the plurality of statistical number candidates and information related to an article assigned to each of the plurality of statistical number candidates (Boxler in [0037] and [0038] discloses server parsing resources to extract relevant information and organizing and storing it in a searchable relational database, database providing organized, searchable text resources of data sources to the user to help them during the classification process, the user views the database via a GUI on user devices; Boxler in [0072] discloses that user may select candidate codes and the GUI allows the user to view a relational database providing more information about each of the candidate codes, which is by referring to a master database; Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification; Boxler in [0106] discloses GUI allowing a user to modify the classification by allowing the user to modify selections during the classification process, allowing the user to back track and review paths not originally pursued, user can select a classification previously completed to view the options he was previously presented with and may select a new option to classify, which is displaying information related to an article assigned to the selected statistical number candidate by the user in the past).
With respect to claim 13, Boxler discloses a non-transitory computer-readable recording medium recording a program for causing a computer to execute the processes (Boxler in [0097] discloses a computer device comprising one or more processors and computer program stored in a non-transitory computer readable medium, such as a memory, which is executed by the device to perform steps) of:
receiving, from a terminal device of a user, a first input related to an article as a search target (Boxler in [0029] and [0030] discloses user operating user device enters and transmits a query towards a server via a GUI, the query includes a description of an object the user wishes to classify, allowing users to quickly find a correct classification code for an object using a graphical user interface and assisted by AI; Boxler in [0042] discloses generating a query including object description and transmit the query towards server, after receiving the query server begins a classification process; [0058] discloses user indicating via the GUI to search specific sections of the classification system, server limiting the search to the relevant sections);
obtaining a specification of a statistical number candidate into which the search target is classified based on the first input and classification information for each statistical number included in a statistical number group having a hierarchical structure (Boxler in [0004] and [0005] discloses harmonized system (HS) schedule being an internationally standardized system of names and numbers to classify traded products, HS schedule being used for customs tariffs and for collection of international trade statistics, HS numerical codes used for classification of goods, which is a statistical number; Boxler in [0045] discloses using object description provided by user to query AI based model embodied as a large language model (LLM) trained on very large corpora of text allowing it to recognize user’s object description to provide relevant information about the object; Boxler in [0074] discloses after viewing candidate codes a user deciding none of the codes represent the object, user providing a filter to focus search within specific chapters of the HS system; Boxler in [0075] discloses text associated with candidate codes presented to user generated by an LLM, code consist of its HS description in the schedule tree; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
displaying, on the terminal device, first information requesting a second input related to the search target to be additionally input in a case where a plurality of statistical number candidates is specified, and the statistical number candidate (Boxler in [0015] discloses submitting a query with a graphical user interface (GUI), the query comprising a text describing an object, obtaining a response to the query comprising a set of one or more candidate locations in a hierarchy classification system, displaying a first candidate locations section in the GUI identifying the one or more candidate locations, displaying an additional description section identifying an additional description of the object based on the first set of one or more candidate locations, obtaining an indication of a selection of the additional description, displaying a second candidate location section identifying a second set of one or more candidate locations in the hierarchy classification system based on the selection of the additional description; Boxler in [0007] and [0046]-[0050] discloses server using prompts to elicit additional descriptions in the form of questions asking for user answers as inputs, server generating and transmitting an output with one or more descriptions generated by AI based model, descriptions presented to user via GUI, user can select any one of the one or more descriptions that accurately describes the object, the selected description used by server for generating enhanced description for the object; Boxler in [0051] and [0053] discloses using user provided object description and/or enhanced description to search for classification codes in the hierarchical classification system; Boxler in [0078] discloses server may identify multiple candidate codes, GUI presents choices to the user in relevancy order, allowing user to identify correct known choices, GUI guides the user to the most likely choice when user is unsure, users narrow down candidate codes until they arrive at a single complete code which is the correct classification);
accepting, by user operation to the terminal device, selection of a statistical number candidate from the plurality of statistical number candidates (Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification); and
displaying, on the terminal device, by referring to master database, information related to an article assigned to the selected statistical number candidate by the user in the past, wherein the master database stores each of the plurality of statistical number candidates and information related to an article assigned to each of the plurality of statistical number candidates (Boxler in [0037] and [0038] discloses server parsing resources to extract relevant information and organizing and storing it in a searchable relational database, database providing organized, searchable text resources of data sources to the user to help them during the classification process, the user views the database via a GUI on user devices; Boxler in [0072] discloses that user may select candidate codes and the GUI allows the user to view a relational database providing more information about each of the candidate codes, which is by referring to a master database; Boxler in [0105] and in Figure 6 discloses a user selecting a classification for an item or article, GUI presenting the user information associated with the classification, such as the proposed classification, a link to view references, or data sources associated with the classification, and a tariff associated with the classification, user can make a selection and complete the classification; Boxler in [0106] discloses GUI allowing a user to modify the classification by allowing the user to modify selections during the classification process, allowing the user to back track and review paths not originally pursued, user can select a classification previously completed to view the options he was previously presented with and may select a new option to classify, which is displaying information related to an article assigned to the selected statistical number candidate by the user in the past).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/R.M/Examiner, Art Unit 2159
/ANN J LO/Supervisory Patent Examiner, Art Unit 2159