DETAILED ACTION
Status of Claims
Claims 1-9 submitted on 05/15/2024 are pending and have been examined.
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 .
Priority
Acknowledgment is made of applicant’s provisional Application No. 63/466,797, filed on 05/16/2023.
Acknowledgment is made of applicant’s provisional Application No. 63/625,596, filed on 01/26/2024.
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. The claims recite an abstract idea. This judicial exception is not integrated into a practical application. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Step 1
Claims 1-9 are directed to a process (see MPEP 2106.03).
Step 2A, Prong 1
Claim 1, taken as representative, recites at least the following limitations that recite an abstract idea:
a method for providing service-related data to be implemented using a service system including a data storage, the service system including a merchant-end that executes, the method comprising steps of:
a) obtaining, by the merchant-end, header information associated with a merchant based on registration information associated with the merchant, the registration information at least including a location of the merchant;
b) obtaining, by the merchant-end and based on product data that is associated with the merchandise and that is provided by the merchant, merchandise-related data associated with a merchandise provided by the merchant;
c) obtaining, by the merchant-end, content information based on the product data and the merchandise-related data;
d) generating, by the merchant-end, the service-related data using the header information and the content information; and
e) transmitting, by the merchant-end, the service-related data as an entry of to-be-searched service-related data to enable to store the entry of to-be-searched service-related data in the data storage.
The above limitation, under its broadest reasonable interpretation, falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106.04(a)(2)(II), in that it recites a commercial interaction.
Thus, under Prong 1 of Step 2A, claim 1 recite an abstract idea.
Step 2A, Prong 2
Claim 1 includes the following additional elements that are bolded:
a method for providing service-related data to be implemented using a service system that is connected to a server via a network, the server including a data storage, the service system including a merchant-end device that executes a first artificial intelligence (AI) assistant software program, the method comprising steps of:
a) obtaining, by the merchant-end device executing the first AI assistant software program, header information associated with a merchant based on registration information associated with the merchant, the registration information at least including a location of the merchant;
b) obtaining, by the merchant-end device executing the first AI assistant software program and based on product data that is associated with the merchandise and that is provided by the merchant, merchandise-related data associated with a merchandise provided by the merchant;
c) obtaining, by the merchant-end device executing the first AI assistant software program, content information based on the product data and the merchandise-related data;
d) generating, by the merchant-end device executing the first AI assistant software program, the service-related data using the header information and the content information; and
e) transmitting, by the merchant-end device executing the first AI assistant software program, the service-related data to the server as an entry of to-be-searched service-related data to enable the server to store the entry of to-be-searched service-related data in the data storage.
The additional elements recited in claims 1 merely invoke such elements as a tool to perform the abstract idea and generally link the use of the abstract idea to a particular technological environment of AI assistant software programs and computers (see MPEP 2106.05(f) and MPEP 2106.05(h). These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration (see Fig. 1, ¶¶0016-0027).
As such, under Prong 2 of Step 2A, when considered both individually and as a whole, the additional elements do not integrate the judicial exception into a practical application and, thus, claims 1 are directed to an abstract idea.
Step 2B
As noted above, while the recitation of the additional elements in independent claims 1 are acknowledged, claims 1 merely invoke such additional elements as a tool to perform the abstract idea and generally link the use of the abstract idea to a particular technological environment (see MPEP 2106.05(f) and MPEP 2106.05(h)).
Even when considered as an ordered combination, the additional elements of claim 1 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1 are ineligible.
Dependent claims 2-4 and 8 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because they do not add “significantly more” to the abstract idea. More specifically, dependent claims 2-4 and 8 merely further define the abstract limitations of claims 1 or provide further embellishments of the limitations recited in independent claims 1. Claims 2-4 and 8 do not introduce any further additional elements. Thus, dependent claims 2-4 and 8 are ineligible.
Furthermore, it is noted that certain dependent claims recite additional elements supplemental to those recited in independent claims 1: a client-end device (Claims 5-7), a second AI assistant software program (5 and 6), a third party application (Claim 6), and a digital signature (claim 9). However, these elements do not integrate the abstract idea into a practical application because they merely amount to using a computer to apply the abstract idea to a particular technological environment or field of use and thus do not act to integrate the abstract idea into a practical application of the abstract idea. Additionally, the additional elements do not amount to significantly more because they merely amount to using a computer to apply the abstract idea and amount to no more than a general link of the use of the abstract idea to a particular technological environment.
Thus, dependent claims 5-7 and 9 are ineligible.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silveira et al. (US 2015/0006333 A1) in view of Batina et al. (US 2024/0289361 A1).
Regarding Claim 1, Silveira et al., hereinafter, Silveira, discloses a method for providing service-related data to be implemented using a service system that is connected to a server via a network, the server including a data storage, the service system including a merchant-end device that executes, the method comprising steps of (Figs. 1, 12A-C; Abstract[A method for generating a website includes obtaining a seed input associated with an entity. The seed input may include one or more keywords, such as a business name. Obtaining the seed input may include receiving the seed input from the user, or the seed input may be obtained without input from the user. The method further includes retrieving, using at least one of the seed input and the identification of the entity, content relevant to the entity from one or more data stores. The method may include generating an online store from product information within the retrieved content.] in view of ¶0003[a server computer system, referred to herein as a web server, may connect through the Internet to a remote client computer system and may send, to the remote client computer system upon request]):
a) obtaining, by the merchant-end device executing, header information associated with a merchant based on registration information associated with the merchant, the registration information at least including a location of the merchant (Fig. 2; ¶0051[The web server 100 may use the seed input to perform the information retrieval and website generation algorithms described below. The seed input may be a data element that partially or fully identifies the user's business (that is, the entity requesting the creation of the website). The seed input may be one or more keywords including one or a combination of the following, for example and without limitation: part or all of the business name; part or all of the business address; the type of business, at a desired degree of specificity (i.e. "restaurant," "Indian restaurant," "North Indian restaurant," "vegan North Indian restaurant," etc.); part or all of the name of a person associated with the business, such as the owner or executive chef; part or all of the name of a relevant product produced or sold by the business; and any other text that may be used to identify the business.]);
b) obtaining, by the merchant-end device executing and based on product data that is associated with the merchandise and that is provided by the merchant, merchandise-related data associated with a merchandise provided by the merchant (Fig. 2; ¶0051[The seed input may be a data element that partially or fully identifies the user's business... The seed input may be… a relevant product produced or sold by the business; and any other text that may be used to identify the business… one or more of the user's products or works of art; a person associated with the business, such as the owner or executive chef; and any other images that may be used to identify the business.]);
c) obtaining, by the merchant-end device executing, content information based on the product data and the merchandise-related data (Fig. 2; ¶0051[The seed input may be a data element that partially or fully identifies the user's business... The seed input may be… a relevant product produced or sold by the business; and any other text that may be used to identify the business… one or more of the user's products or works of art; a person associated with the business, such as the owner or executive chef; and any other images that may be used to identify the business.]);
d) generating, by the merchant-end device executing, the service-related data using the header information and the content information (¶¶0107-0108[the seed input may be used to generate an online store for the user… the online store generation may be performed in conjunction with an overall website generation process, such as the processes illustrated in FIGS. 4, 9, and 10. Referring to FIG. 17, at step 1700 the web server 100 may receive the seed input from the user or another entity, or obtain the seed input automatically using any of the methods described above. Accordingly, the seed input may be stored in a data store in advance of generating the online store, or the web server may obtain the seed input and immediately begin creating the online store]); and
e) transmitting, by the merchant-end device executing, the service-related data to the server as an entry of to-be-searched service-related data to enable the server to store the entry of to-be-searched service-related data in the data storage (Fig. 4; ¶0129[The templates may be stored on the web server 100 or in a remote database accessible by the web server 100.]; Examiner notes that a generated website is comparable to a “to-be-searched service-related data”).
Although Silveira discloses executing a method, Silveira does not explicitly disclose executing a first artificial intelligence (AI) assistant software program.
Although Silveira discloses obtaining header information, Silveira does not explicitly disclose obtaining by a device executing the first AI assistant software program.
Although Silveira discloses obtaining merchandise-related data, Silveira does not explicitly disclose obtaining by a device executing the first AI assistant software program.
Although Silveira discloses obtaining content information, Silveira does not explicitly disclose obtaining by a device executing the first AI assistant software program.
Although Silveira discloses generating service-related data using the header, Silveira does not explicitly disclose generating by a device executing the first AI assistant software program.
Although Silveira discloses transmitting service-related data to a server, Silveira does not explicitly disclose transmitting by a device executing the first AI assistant software program.
However, Batina et al., hereinafter, Batina, teaches an AI assistant software program on a device (Fig. 1[The system 100 may be implemented using one or more computing devices]; ¶¶0080-0085[The system 100 may provide user interfaces for accessing one or more of: the generative AI model 112, the media database 130, or search results produced by the search engine 114. In some implementations, the generative AI model 112 may be accessed via a user interface, such as a chatbot (e.g., ChatGPT), which facilitates text-based conversation. The generative AI model 112 may provide chat-like outputs responsive to user-inputted prompts. For example, upon receiving input of an initial prompt from a user, the generative AI model 112 may generate one or more follow-up questions, formatted as chat-outputs, to present to the user. The user can provide responses to the questions as chat-inputs to the generative AI model 112. In this way, information may be exchanged between the user and the generative AI model 112 in a dialogue format… The search engine 114 receives the output produced by the generative AI model 112. The generative AI model 112 may thus be used to effectively process a user-inputted search query and provide relevant query data, i.e., output of the model, to the search engine 114. The search engine 114 may then perform a search of the relevant search space using the query data.]).
The method of Batina is applicable to the method of Silveira as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by Silveira to include an AI assistant software program as taught by Batina. One of ordinary skill in the art would have been motivated to expand the method of Silveira in order to discern a user's needs based on user interactions (¶0003).
Regarding Claim 2, Silveira in view of Batina teaches the method as claimed in Claim 1, Silveira further discloses wherein step b) includes performing a search for domain knowledge associated with the merchandise based on the product data so as to obtain the merchandise-related data (¶0108[The steps immediately subsequent to collecting the seed input may include identifying the entity (step 305), collecting data pertaining to the entity from the internet and data stores (step 310), and categorizing the entity (step 315), each as described above. The data stores from which data is collected at step 310 may in particular include data stores where product information is likely to be found, including the entity's previous website, business listing data stores 140, point-of-sale transaction data stores 150, and offline crawling data stores 155.]; Examiner notes that collecting data from the internet and data stores is comparable to performing a search for domain knowledge associated with the product).
Regarding Claim 3, Silveira in view of Batina teaches the method as claimed in Claim 1, Silveira further discloses wherein:
step a) includes transforming the registration information into a serialization format so as to obtain the header information (Fig. 12A-C; ¶0090[the POS device 905 may be configured to provide formatted transaction data, such as in an XML file or spreadsheet, to the web server 100.] in view of ¶0032[Obtaining the seed input may include receiving, from a point-of-sale device in electronic communication with the server computer, transaction data for a transaction performed by the entity, and extracting the seed input from the transaction data.] and ¶0087[The transaction data may include information that the presently-described systems may be configured to use as seed input. For example, the transaction data may include the business name, physical or electronic address, or phone number, account numbers that may be associated with the business if authorization to use them is obtained]; Examiner notes that instant specification ¶0033 states that a serialization format is a “JavaScript Object Notation (JSON), Extensible Markup Language (XML), etc.”); and
step c) includes transforming the product data and the merchandise-related data into the serialization format so as to obtain the content information (Fig. 12A-C; ¶0090[the POS device 905 may be configured to provide formatted transaction data, such as in an XML file or spreadsheet, to the web server 100.] in view of ¶0032[Obtaining the seed input may include receiving, from a point-of-sale device in electronic communication with the server computer, transaction data for a transaction performed by the entity, and extracting the seed input from the transaction data.]; Examiner notes that instant specification ¶0033 states that a serialization format is a “JavaScript Object Notation (JSON), Extensible Markup Language (XML), etc.”).
Although Silveira discloses transforming registration information into a serialization format, Silveira does not explicitly disclose using the first AI assistant software program.
Although Silveira disclose transforming product data, Silveira does not explicitly disclose using the first AI assistant software program.
However, Batina teaches an AI assistant software program on a device (Fig. 1[The system 100 may be implemented using one or more computing devices]; ¶¶0080-0085[The system 100 may provide user interfaces for accessing one or more of: the generative AI model 112, the media database 130, or search results produced by the search engine 114. In some implementations, the generative AI model 112 may be accessed via a user interface, such as a chatbot (e.g., ChatGPT), which facilitates text-based conversation. The generative AI model 112 may provide chat-like outputs responsive to user-inputted prompts. For example, upon receiving input of an initial prompt from a user, the generative AI model 112 may generate one or more follow-up questions, formatted as chat-outputs, to present to the user. The user can provide responses to the questions as chat-inputs to the generative AI model 112. In this way, information may be exchanged between the user and the generative AI model 112 in a dialogue format… The search engine 114 receives the output produced by the generative AI model 112. The generative AI model 112 may thus be used to effectively process a user-inputted search query and provide relevant query data, i.e., output of the model, to the search engine 114. The search engine 114 may then perform a search of the relevant search space using the query data.]).
The method of Batina is applicable to the method of Silveira as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by Silveira to include an AI assistant software program as taught by Batina. One of ordinary skill in the art would have been motivated to expand the method of Silveira in order to discern a user's needs based on user interactions (¶0003).
Regarding Claim 4, Silveira in view of Batina teaches the method as claimed in Claim 1, Silveira discloses the service system further being connected via the network to a map-service device that provides a map service, the method further comprising, after step e) (Fig. 1; ¶0066[Similarly, if a portion of the potential content is identified by the content framework as a business address, that information can then be used to display a map on the website that depicts the location of the address.] in view of ¶0045 which discloses a map-service device that provides a map service):
in response to receipt of an access link to the entry of to-be-searched service-related data from the server, transmitting, by the merchant-end device executing, a landmark adding request that includes the access link and the location of the merchant included in the registration information to the map-service device as a request for display of the merchant on the map service, so that the map-service device adds a landmark on the map service based on the location of the merchant, and associate the access link with the landmark (Figs. 1 and 7; ¶0066[Similarly, if a portion of the potential content is identified by the content framework as a business address, that information can then be used to display a map on the website that depicts the location of the address.]; Examiner notes that a map that displays the location of the address is comparable to a landmark in view of ¶0045[Referring to FIG. 1, a web server 100 may be configured to communicate over the Internet with one or more requesting device 110 in order to serve requested website content to the requesting device 110. The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet. Examples include, respectively and without limitation: a wired connection, WiFi or other wireless network, cellular network, or satellite network; Transmission Control Protocol and Internet Protocol ("TCP/IP"), Global System for mobile Communications ("GSM") protocols, code division multiple access ("CDMA") protocols, and Long Term Evolution ("LTE") mobile phone protocols; and web browsers such as MICROSOFT INTERNET EXPLORER, MOZILLA FIREFOX, and APPLE SAFARI.]; Examiner notes that accessing the website by requesters is comparable to an access link).
Although Silveira disclose transmitting by a device, Silveira does not explicitly disclose transmitting by a device executing the first AI assistant software program.
However, Batina teaches an AI assistant software program on a device (Fig. 1[The system 100 may be implemented using one or more computing devices]; ¶¶0080-0085[The system 100 may provide user interfaces for accessing one or more of: the generative AI model 112, the media database 130, or search results produced by the search engine 114. In some implementations, the generative AI model 112 may be accessed via a user interface, such as a chatbot (e.g., ChatGPT), which facilitates text-based conversation. The generative AI model 112 may provide chat-like outputs responsive to user-inputted prompts. For example, upon receiving input of an initial prompt from a user, the generative AI model 112 may generate one or more follow-up questions, formatted as chat-outputs, to present to the user. The user can provide responses to the questions as chat-inputs to the generative AI model 112. In this way, information may be exchanged between the user and the generative AI model 112 in a dialogue format… The search engine 114 receives the output produced by the generative AI model 112. The generative AI model 112 may thus be used to effectively process a user-inputted search query and provide relevant query data, i.e., output of the model, to the search engine 114. The search engine 114 may then perform a search of the relevant search space using the query data.]).
The method of Batina is applicable to the method of Silveira as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by Silveira to include an AI assistant software program as taught by Batina. One of ordinary skill in the art would have been motivated to expand the method of Silveira in order to discern a user's needs based on user interactions (¶0003).
Claim(s) 5, 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silveira in view of Batina in view of Qin et al. (US 2024/0346256 A1).
Regarding Claim 5, Silveira in view of Batina teaches the method as claimed in Claim 1, Silveira discloses the service system further including a client-end device that executes, the method further comprising, after step e), steps of (Fig. 1[showing devices]; ¶0045[Referring to FIG. 1, a web server 100 may be configured to communicate over the Internet with one or more requesting device 110 in order to serve requested website content to the requesting device 110. The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet]; Examiner notes that requesting devices are comparable to client-end devices):
f) in response to receipt of a search command indicating a request for a desired service, by the client-end device executing, generating a service data request that includes the search command, and transmitting the service data request to the server, so that the server is enabled to, based on the service data request, retrieve at least one selected entry of service-related data from among entries of to-be-searched service-related data stored therein, and transmit the at least one selected entry of service-related data to the client-end device (Fig. 1[showing communication between devices and servers]; ¶0045[Referring to FIG. 1, a web server 100 may be configured to communicate over the Internet with one or more requesting device 110 in order to serve requested website content to the requesting device 110. The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet.] in view of ¶0129[The templates may be stored on the web server 100 or in a remote database accessible by the web server 100.]; Examiner notes that a generated website is comparable to a “to-be-searched service-related data”);
g) in response to receipt of the at least one selected entry of service-related data, adding, by the client-end device executing, the at least one selected entry of service-related data (Fig. 1[showing communication between devices and servers]; ¶0045[Referring to FIG. 1, a web server 100 may be configured to communicate over the Internet with one or more requesting device 110 in order to serve requested website content to the requesting device 110. The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet.]); and
h) by the client-end device executing, obtaining a qualified entry of service-related data from among the at least one selected entry of service-related data based on the search command (Fig. 1[showing communication between devices and servers]; ¶0045[Referring to FIG. 1, a web server 100 may be configured to communicate over the Internet with one or more requesting device 110 in order to serve requested website content to the requesting device 110. The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet. Examples include, respectively and without limitation: a wired connection, WiFi or other wireless network, cellular network, or satellite network; Transmission Control Protocol and Internet Protocol ("TCP/IP"), Global System for mobile Communications ("GSM") protocols, code division multiple access ("CDMA") protocols, and Long Term Evolution ("LTE") mobile phone protocols; and web browsers such as MICROSOFT INTERNET EXPLORER, MOZILLA FIREFOX, and APPLE SAFARI.]).
Although Silveira discloses a client-end device, Silveira does not explicitly disclose a second AI assistant software program.
Although Silveira discloses executing and obtaining information, Silveira does not explicitly disclose executing the second AI assistant software program.
However, Batina teaches a second AI assistant software program on a device (Fig. 1[The system 100 may be implemented using one or more computing devices]; ¶¶0080-0085[The system 100 may provide user interfaces for accessing one or more of: the generative AI model 112, the media database 130, or search results produced by the search engine 114. In some implementations, the generative AI model 112 may be accessed via a user interface, such as a chatbot (e.g., ChatGPT), which facilitates text-based conversation. The generative AI model 112 may provide chat-like outputs responsive to user-inputted prompts. For example, upon receiving input of an initial prompt from a user, the generative AI model 112 may generate one or more follow-up questions, formatted as chat-outputs, to present to the user. The user can provide responses to the questions as chat-inputs to the generative AI model 112. In this way, information may be exchanged between the user and the generative AI model 112 in a dialogue format… The search engine 114 receives the output produced by the generative AI model 112. The generative AI model 112 may thus be used to effectively process a user-inputted search query and provide relevant query data, i.e., output of the model, to the search engine 114. The search engine 114 may then perform a search of the relevant search space using the query data.] in view of ¶0114[The server may provide an interface to other devices including, without limitation, clients, other servers, printers, database servers, print servers, file servers, communication servers, distributed servers and the like]).
The method of Batina is applicable to the method of Silveira as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by Silveira to include an AI assistant software program as taught by Batina. One of ordinary skill in the art would have been motivated to expand the method of Silveira in order to discern a user's needs based on user interactions (¶0003).
Although Silveira discloses generating a service data request with a search command, Silveira in view of Batina does not explicitly teach executing the second AI assistant software program and a location of the client-end device.
Although Silveira discloses adding selected entry of service-related data, Silveira in view of Batina does not explicitly teach executing the second AI assistant software program and adding to an external data source that is retrievable during retrieval-augmented generation (RAG).
However, Qin et al., hereinafter, Qin teaches an AI assistant program, a location of the client device and an external data source that is retrievable during RAG (Figs. 1-3 and 8; ¶0018[A retrieval augmented generation (RAG) approach is disclosed herein that adds an information retrieval component to create augmented prompts to feed into the generative language model for generating the final answer/prediction. RAG is a general-purpose fine-tuning which combines pre-trained parametric and non-parametric memory for language generation.] in view of ¶0080[LI receiver 884 may be used for location determination of computing device 802 and may include a satellite navigation receiver such as a Global Positioning System (GPS) receiver or may include other type of location determiner configured to determine location of computing device 802 based on received information (e.g., using cell tower triangulation, etc.). Accelerometer 886 may be present to determine an orientation of computing device 802.]).
The method of Qin is applicable to the method of Silveira in view of Batina as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as taught by Silveira in view of Batina to include an AI assistant software program, a retrieval augmented generation (RAG) approach, and a location of the client as taught by Qin. One of ordinary skill in the art would have been motivated to expand the method of Silveira in view of Batina in order to generate human-like text for a wide range of applications, including chatbots, language translation, and content creation (¶0001).
Regarding Claim 6, Silveira in view of Batina in view of Qin teaches the method as claimed in Claim 5, Silveira discloses further comprising executing, by the client-end device executing, a third party application that is associated with a merchandise of the qualified entry of service-related data (¶0111[At step 1715, the web server 100 may generate the online store in the form of one or more web pages laid out according to an online store template… The online store template may include API or function calls, software modules, and other web applications as needed to implement secure purchasing of products listed in the online store]; Examiner notes that other web applications are comparable to third party applications associated with the merchandise).
Although Silveira discloses executing by a device, Silveira does not explicitly disclose executing by a device executing the second AI assistant software program.
However, Batina teaches a second AI assistant software program on a device (Fig. 1[The system 100 may be implemented using one or more computing devices]; ¶¶0080-0085[The system 100 may provide user interfaces for accessing one or more of: the generative AI model 112, the media database 130, or search results produced by the search engine 114. In some implementations, the generative AI model 112 may be accessed via a user interface, such as a chatbot (e.g., ChatGPT), which facilitates text-based conversation. The generative AI model 112 may provide chat-like outputs responsive to user-inputted prompts. For example, upon receiving input of an initial prompt from a user, the generative AI model 112 may generate one or more follow-up questions, formatted as chat-outputs, to present to the user. The user can provide responses to the questions as chat-inputs to the generative AI model 112. In this way, information may be exchanged between the user and the generative AI model 112 in a dialogue format… The search engine 114 receives the output produced by the generative AI model 112. The generative AI model 112 may thus be used to effectively process a user-inputted search query and provide relevant query data, i.e., output of the model, to the search engine 114. The search engine 114 may then perform a search of the relevant search space using the query data.] in view of ¶0114[The server may provide an interface to other devices including, without limitation, clients, other servers, printers, database servers, print servers, file servers, communication servers, distributed servers and the like]).
The method of Batina is applicable to the method of Silveira as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by Silveira to include an AI assistant software program as taught by Batina. One of ordinary skill in the art would have been motivated to expand the method of Silveira in order to discern a user's needs based on user interactions (¶0003).
Claim(s) 7 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silveira in view of Batina in view of Qin in view of Crepps et al. (US 2020/0160427 A1).
Regarding Claim 7, Silveira in view of Batina in view of Qin teaches the method as claimed in Claim 5, Silveira further discloses wherein:
in step a), the header information thus obtained includes the location of the merchant (Fig. 2; ¶0051[The seed input may be one or more keywords including one or a combination of the following, for example… part or all of the business address; the type of business, at a desired degree of specificity]; Examiner notes that business address is comparable to a location of the merchant); and
in step f), the location of the merchant included in the header information of the at least one selected entry of service-related data (Fig. 2; ¶0051[The seed input may be one or more keywords including one or a combination of the following, for example… part or all of the business address; the type of business, at a desired degree of specificity]; Examiner notes that business address is comparable to a location of the merchant).
Although Silveira discloses a location of the merchant, Silveira in view of Batina in view of Qin does not explicitly teach location of merchant is within a predetermined distance from the location of the client-end device.
However, Crepps et al., hereinafter, Crepps, teaches a merchant being within a distance of a user device location (¶0029[When performing the look up, the DA computing device may use filters. In some embodiments, the filters are included in the product request message received from the user computing device. In other embodiments, the DA computing device retrieves the filters from the central database. The filters may include, but are not limited to, merchant data, such as a merchant identifier, a merchant location identifier, metadata associated with each requested product identifier (e.g., price, name of each product, product category, associated keywords with each product, among other metadata associated with each product), and metadata associated with each merchant location (e.g., hours of operation, applicable sales taxes, merchant-imposed fees, among other metadata associated with each merchant location). Other filters may be calculated filters. In some embodiments, the DA computing device is configured to generate the calculated filters. In other embodiments, the DA computing device is configured to receive the calculated filters which may be included within the product request message. The calculated filters may include, but are not limited to, product price range, a distance range between the merchant location and the location of the user computing device, a distance range between the merchant location and a location specified by the user computing device, and/or any other suitable filters that the DA computing device may utilize to perform the look up. The distance between locations may be calculated using a global positioning system (GPS) and/or other any suitable geolocation technology that enables the DA system to function as described herein.]).
The method of Crepps is applicable to the method of Silveira in view of Batina in view of Qin as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as taught by Silveira in view of Batina in view of Qin to include a merchant being within a predetermined distance of a user as taught by Crepps. One of ordinary skill in the art would have been motivated to expand the method of Silveira in view of Batina in view of Qin in order to display the matched data in the form of a list in order of relevance based on the number of matched data between the data within the product request message and the data stored within the central database (¶0033).
Regarding Claim 8, Silveira in view of Batina in view of Qin teaches the method as claimed in Claim 5, Silveira further discloses wherein step h) includes, with respect to each of the at least one selected entry of service-related data retrieved from the server (Fig. 1[showing communication between devices and servers]; ¶0045):
the merchandise-related data included in the selected entry of service-related data and search criteria included in the search command, so as to determine whether the selected entry of service-related data fits the search criteria (Fig. 1[showing communication between devices and servers]; ¶0045[The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet. Examples include, respectively and without limitation: a wired connection, WiFi or other wireless network, cellular network, or satellite network; Transmission Control Protocol and Internet Protocol ("TCP/IP"), Global System for mobile Communications ("GSM") protocols, code division multiple access ("CDMA") protocols, and Long Term Evolution ("LTE") mobile phone protocols; and web browsers such as MICROSOFT INTERNET EXPLORER, MOZILLA FIREFOX, and APPLE SAFARI.] in view of ¶0129[The templates may be stored on the web server 100 or in a remote database accessible by the web server 100.]); and
the selected entry of service-related data in a case where the selected entry of service-related data fit the search criteria (Fig. 1[showing communication between devices and servers]; ¶0045[The requesting devices 110 may request the website content using any electronic communication medium, communication protocol, and computer software suitable for transmission of data over the Internet. Examples include, respectively and without limitation: a wired connection, WiFi or other wireless network, cellular network, or satellite network; Transmission Control Protocol and Internet Protocol ("TCP/IP"), Global System for mobile Communications ("GSM") protocols, code division multiple access ("CDMA") protocols, and Long Term Evolution ("LTE") mobile phone protocols; and web browsers such as MICROSOFT INTERNET EXPLORER, MOZILLA FIREFOX, and APPLE SAFARI.]).
Although Silveira discloses the merchandise data, Silveira in view of Batina in view of Qin does not explicitly teach comparing the data and filtering out the data that does not fit the search criteria.
However, Crepps teaches comparing merchant and user data in order filter out data that does not fit a search criteria (¶0029[When performing the look up, the DA computing device may use filters. In some embodiments, the filters are included in the product request message received from the user computing device. In other embodiments, the DA computing device retrieves the filters from the central database. The filters may include, but are not limited to, merchant data, such as a merchant identifier, a merchant location identifier, metadata associated with each requested product identifier (e.g., price, name of each product, product category, associated keywords with each product, among other metadata associated with each product), and metadata associated with each merchant location (e.g., hours of operation, applicable sales taxes, merchant-imposed fees, among other metadata associated with each merchant location). Other filters may be calculated filters. In some embodiments, the DA computing device is configured to generate the calculated filters. In other embodiments, the DA computing device is configured to receive the calculated filters which may be included within the product request message. The calculated filters may include, but are not limited to, product price range, a distance range between the merchant location and the location of the user computing device, a distance range between the merchant location and a location specified by the user computing device, and/or any other suitable filters that the DA computing device may utilize to perform the look up. The distance between locations may be calculated using a global positioning system (GPS) and/or other any suitable geolocation technology that enables the DA system to function as described herein.]).
The method of Crepps is applicable to the method of Silveira in view of Batina in view of Qin as they share characteristics and capabilities, namely, they are both targeted to improving search for services. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device as taught by Silveira in view of Batina in view of Qin to include filtering out data as taught by Crepps. One of ordinary skill in the art would have been motivated to expand the method of Silveira in view of Batina in view of Qin in order to display the matched data in the form of a list in order of relevance based on the number of matched data between the data within the product request message and the data stored within the central database (¶0033).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silveira in view of Batina in view of Diorio et al. (US 9,607,286 B1).
Regarding Claim 9, Silveira in view of Batina teaches the method as claimed in Claim 1, Silveira discloses further comprising, between steps d) and e): performing operation by executing algorithm to generate a secret key, and attaching to the service-related data (¶0086[The present systems and methods may implement encryption, secured-account access, and other safeguards, and further may cooperate with one or more external security measures, to protect the confidentiality of such information. The entity may have a secured account on or accessible by the web server 100, or may be prompted to create such an account when the transaction data is first transmitted to or received by the web server 100.])
Although Silveira discloses performing an operation by executing an algorithm to generate a key, Silveira in view of Batina does not explicitly disclose performing a signature operation executing an asymmetric cryptography algorithm to generate a digital signature using a key and attaching the digital signature.
However, Diorio et al., hereinafter, Diorio, teaches a digital signature and asymmetric cryptography (Fig. 8; Col. 14, line 58 to Col. 15, line 30[Electronic signatures may be generated using symmetric and asymmetric cryptographic techniques. An electronic signature generated using symmetric cryptography may be known as a “message authentication code” (MAC). To generate a MAC for a message, a signatory (also referred to as a sender) uses a secret key and the message to generate the MAC. The sender may then send the message and the associated MAC to a recipient. The recipient in turn can use the same secret key to authenticate that the MAC corresponds to the message and that the sender knows the secret key. In some embodiments, the sender may instead only send the MAC to the recipient, and the recipient may recover the associated message from the MAC using the secret key. An electronic signature generated using asymmetric cryptography may be known as a “digital signature” (DS). To generate a DS for a message, a signatory or sender uses the message and the private key from a private/public key pair to generate the DS. The private key and public key in the key pair are mathematically related to each other, and the signatory keeps the private key secret while making the public key available to others. The sender may then send both the message and the associated DS (referred to as a “digital signature with appendix”) to a recipient. The recipient can then in turn use the public key to authenticate that the DS corresponds to the message and that the sender possesses the private key. An authenticated MAC or DS gives the recipient reason to believe that the message was created by a known sender, and that it was not altered in transit. In s