DETAILED ACTION
This communication is in response to the Application filed on 11/02/2022. Claims 1-20 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 .
Information Disclosure Statement
The IDS dated 11/02/2022 has been considered and placed in the application file.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. All of the claims are method claims (1-15), apparatus/machine claims (16-20) or manufacture claim under (Step 1), but under Step 2A all of these claims recite abstract ideas and specifically mental processes. These mental processes are more particularly recited in claims 1, 16, and 20 as:
applying at least one artificial intelligence (AI) model to the downloaded digital compliance material…
determining, from the applying the at least one AI model, at least one compliance policy for conveyance of at least one benefit to the benefit recipient…
responding by indicating, for each identified benefit of at least one identified benefit, whether conveyance of the identified benefit complies with the relevant compliance policies for conveyance of benefits to the benefit recipient…
Under Step 2A Prong One, claims 1, 16, and 0 are directed to an abstract idea and specifically a mental process. As detailed above, the steps of applying, searching, determining, responding, etc. may be practically performed in the human mind with the use of a physical aid such as a pen and paper. For example, a human compliance agent could receive instructions from a client to review compliance documents with regard to a gift they would like to give to a recipient. The human agent could then search for relevant compliance material describing a company’s compliance policies, extract compliance policies relevant to the gift, and respond to the client with information regarding whether conveyance of the gift complies with the company’s compliance policies.
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because claims 1-20 do not recite additional elements that integrate the exception into a practical application. In particular, claims 1, 16, and 20 recite the additional elements of a processor (¶ [0021]), memory (¶ [0024]-[0025]), and artificial intelligence model (¶ [0071]). These additional elements are recited at a high level of generality and merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). Further, claims 1, 16, and 20 recite the additional elements of “searching…”, “downloading…”, and “receiving…”, all of which amount to insignificant extra-solution activities which are not indicative of integration into a practical application as per MPEP 2106.05(g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Under Step 2B, the claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of using a computer is noted as a general computer {processor (¶ [0021]); memory (¶ [0024]-[0025]); artificial intelligence model (¶ [0071])}. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, the additional limitations in the claims noted above are directed towards insignificant extra-solution activities. The claims are not patent eligible.
With respect to claims 2-4, the claim relates to specifying sender context, recipient context, and conveyance mechanisms related to complying with both send and recipient context. This relates to a human compliance agent retrieving compliance documents from both the sender’s company and the recipient’s company, and determining whether conveyance of the sender’s gift would violate compliance policies from either company’s compliance documents. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 5, the claim relates to limiting digital compliance material to either digital news information or government regulations. This relates to a human compliance agent retrieving compliance documents from public government regulation documents. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 6, the claim relates to extracting text passages from compliance material using an AI model. This relates to a human compliance agent circling entire sections in a compliance document that are relevant to the sender’s gift. The additional limitation of an “AI model” is recited at a high level of generality (¶ [0071]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 7 and 14, the claim relates to extracting text snippets from extracted text passages and specifying extracted answer text snippets to include compliance information. This relates to a human compliance agent using their understanding of language to highlight relevant text snippets within the circled sections of a compliance document. The additional limitation of an “AI model” is recited at a high level of generality (¶ [0071]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 8, the claim relates to the NLU model receiving queries, extracting text snippets, and responding with those text snippets. This relates to a human compliance agent receiving a client request, analyzing compliance documents to find relevant text snippets, and then responding to the client using the relevant snippets . The additional limitation of a “model” is recited at a high level of generality (¶ [0071]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 9, the claim relates to classifying text snippets into a single class selected from a group of classes that each represent a different level of compliance. This relates to a human compliance agent receiving a client request, discovering that the request violates a compliance policy, and labelling the request to indicate the violation. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 10, the claim relates to generating summary statements. This relates to a human compliance agent responding to a non-compliant client request by citing the text snippet that the request violated. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 11, the claim relates to the prompt identifying the recipient, and the searching performed in response to the prompt. This relates to a human compliance agent receiving a client request that identifies the recipient of a gift and searching for compliance documents in response to receiving the request. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 12, the claim relates to the prompt specifying a benefit, and the responding including a compliance check. This relates to a human compliance agent receiving a client request that specifies a gift to a recipient and responding with a statement that informs the client that their gift is non-compliant. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 13 and 18, the claim relates to identifying a plurality of benefits whose conveyance is determined to comply with relevant compliance policies. This relates to a human compliance agent receiving a client request that specifies a gift to a recipient and identifying a category of gifts relevant to the client’s gift that is compliant with compliance policies. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 14, the claim relates to the client’s request including multiple recipients. This relates to a human compliance agent checking the compliance policies of each recipient in a client’s request and informing the client which gifts were compliant and which gifts were non-compliant for each of the client’s recipients. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 15 and 19, the claim relates to building a request data record based on a sender selecting a benefit. This relates to a human compliance agent keeping records of their client’s requests, each record including a client’s gift and relevant compliance policies. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
For all of the above reasons, taken alone or in combination, claims 1-20 recite a non-statutory mental process.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 20200387911 A1 (Yoon et al.) in view of "Automated Question Answering for Improved Understanding of Compliance Requirements: A Multi-Document Study" (Abualhaija et al.).
Claim 1
Regarding claim 1, Yoon et al. disclose a computer-implemented method comprising:
automatically searching for, and downloading digital compliance material, the digital compliance material describing relevant compliance policies for conveyance of benefits to a benefit recipient (Yoon et al. ¶ [0037], "The host platform may retrieve compliance information from either the sender's compliance policy (senders domain), the recipient's compliance policy (recipient's domain), related compliance policies (other domains in the same industry), default rules specified by the host platform, and the like.");
[applying at least one artificial intelligence (AI) model to the downloaded digital compliance material, and] determining [, from the applying the at least one AI model,] at least one compliance policy for conveyance of at least one benefit to the benefit recipient (Yoon et al. ¶ [0037], "In the example of FIG. 4A, the host platform access company data 420 that is linked to the domain name 412 of the sender and retrieve company-specific compliance policy rules 422 which may include files, documents, web text, PDFs, etc."); and
based on receiving a prompt from a sender desiring to convey a benefit (Yoon et al. ¶ [0035], "the user may generate unstructured messages in which the content is added by the user without using drop-down menus, or predefined gifts."), responding by indicating, for each identified benefit of at least one identified benefit, whether conveyance of the identified benefit complies with the relevant compliance policies for conveyance of benefits to the benefit recipient (Yoon et al. ¶ [0035], "In this example, the host platform identifies a domain name 412 of a sender of the gift and performs a compliance check based thereon.").
Yoon et al. do not explicitly disclose all of applying an AI model.
However, Abualhaija et al. disclose [automatically searching for, and] downloading[,] digital compliance material, the digital compliance material describing relevant compliance policies (Abualhaija et al. pg. 42, Section 3, Paragraph 1, "The input to the approach is a regulatory document (RegD)") [for conveyance of benefits to a benefit recipient];
applying at least one artificial intelligence (AI) model to the downloaded digital compliance material (Abualhaija et al. pg. 41, Section 2, Paragraph 7, "A large-scale pre-trained LM can be fine-tuned to solve different downstream NLP tasks, e.g., QA and computing text similarity [22]. The models we employ in this work based on BERT and its variants are fine-tuned to address machine reading comprehension (MRC)."), and determining , from the applying the at least one AI model, at least one compliance policy (Abualhaija et al. pg. 42, Section 3A, Paragraph 2-3, "we further partition RegD into a list of context spans, denoted as
C
=
{
c
1
,
c
2
,
.
.
.
,
c
n
}
... We automatically generate
C
in two steps. The first step applies regular expressions over the annotations produced by the NLP pipeline in order to identify the articles in RegD based on its formatting structure. ... We are mainly interested in splitting RegD into articles, since each article often discusses a coherent topic in a regulation." Separating a regulatory document into distinct regulation topics is considered analogous to determining at least one compliance policy) [for conveyance of at least one benefit to the benefit recipient]; and
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Yoon et al.’s compliance check to incorporate Abualhaija et al.’s AI front-end.
The suggestion/motivation for doing so would have been that, “[Extracting compliance requirements from regulations] is time consuming and error-prone since regulations often contain complicated natural language (NL) structures, are composed of long chapters, and contain many references to external articles. Second, requirements engineers do not necessarily have sufficient legal expertise to efficiently navigate through the regulations and find information related to compliance requirements,” as noted by Abualhaija et al. in pg. 1, Section 1, Paragraph 2.
Claim 2
Regarding claim 2, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the benefit recipient comprises at least one selected from the group consisting of: a target company, an employee of a target company (Yoon et al. ¶ [0019], "One of the objectives of the system is to support platform users/customers to be compliant with both their sending policy (company they work at) as well as the recipient policy (recipient's company)."), and an associate of a target company, and wherein the digital compliance material comprises benefit recipient compliance material having polices directed to receiving benefits (Yoon et al. ¶ [0023], "the host platform 120 may identify a domain name of ... the recipient 130. The host platform 120 may identify compliance rules that are associated with the domain of ... the recipient. For example, organizations may provide web-based endpoints with compliance information that are accessible to the host platform 120." ¶ [0015], "the system may identify and notify... recipients of relevant compliance information associated with a gift request message" Compliance information associated with a gift is considered analogous to recipient compliance material having policies directed to receiving benefits), the benefit recipient compliance material comprising at least one selected from the group consisting of: a code of ethics, a code of conduct, a gifting policy (Yoon et al. ¶ [0037], "In the example of FIG. 4A, the host platform access company data 420... company data 420 may include mappings between categories of gifts and specific policies. For example, a gift card may be mapped to policy A, while a restaurant meal may be mapped to policy B, or the like." Data that maps gifts to policies is considered analogous to a gifting policy), and a hospitality policy of the benefit recipient.
Claim 3
Regarding claim 3, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the sender comprises at least one selected from the group consisting of: a sending company, an employee of a sending company (Yoon et al. ¶ [0019], "One of the objectives of the system is to support platform users/customers to be compliant with both their sending policy (company they work at) as well as the recipient policy (recipient's company)."), and an associate of a sending company, and wherein the digital compliance material comprises sender compliance material having polices directed to conveying benefits, the sender compliance material comprising at least one selected from the group consisting of: a code of ethics, a code of conduct, a gifting policy (Yoon et al. ¶ [0037]-[0038], " In the example of FIG. 4A, the host platform access company data 420 that is linked to the domain name 412 of the sender and retrieve company-specific compliance policy rules 422 which may include files, documents, web text, PDFs, etc. ... The company data 420 may include mappings between categories of gifts and specific policies. For example, a gift card may be mapped to policy A, while a restaurant meal may be mapped to policy B, or the like."), and a hospitality policy of the sender.
Claim 4
Regarding claim 4, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein whether conveyance of the identified benefit complies with the relevant compliance policies is based at least in part on compliance with both (i) the benefit recipient compliance material and (ii) the sender compliance material (Yoon et al. ¶ [0019], "One of the objectives of the system is to support platform users/customers to be compliant with both their sending policy (company they work at) as well as the recipient policy (recipient's company).").
The remaining limitations of claim 4 are similar in scope to that of claims 2 and 3 and therefore are rejected for similar reasons as described above.
Claim 5
Regarding claim 5, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the digital compliance material comprises at least one selected from the group consisting of:
digital news information informing of a category of recipients to which the benefit recipient belongs, and which category of recipients is subject to at least some of the relevant compliance policies; and
governmental regulations setting forth at least some of the relevant compliance policies (Yoon et al. ¶ [0019], "The industry data sources 170 may include other company data sources or generic data sources that are published and accessible on the web. For example,... government regulations... may include general compliance information which can be used to supplement or stand in the place of company-specific compliance information.").
Claim 6
Regarding claim 6, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the applying the at least one AI model comprises:
analyzing the digital compliance material [with at least one pre-trained model configured] to extract text passages, from the digital compliance material, that are relevant to the conveyance of benefits to the benefit recipient (Yoon et al. ¶ [0040]-[0041], "The compliance policy data 422 and 432 is further shown in FIG. 4B and includes unstructured data such as the text of the gifting policies of the company and of the industry in general. ... The host platform can translate the unstructured data into structured data. This allows business rules to be applied to the data. In this step, the system extracts or analyzes keywords/attributes within the gift/email itself and then finds compliance information (rules) of the recipient that is associated therewith."); and
extracting from the digital compliance material the text passages that are relevant to the conveyance of benefits to the benefit recipient (Yoon et al. ¶ [0041], "the system extracts or analyzes keywords/attributes within the gift/email itself and then finds compliance information (rules) of the recipient that is associated therewith. For example, a compliancy policy may specify no alcohol, no gifts over $100, etc.").
Abualhaija et al. further disclose analyzing the digital compliance material with at least one pre-trained model configured to extract text passages, from the digital compliance material (Abualhaija et al. pg. 43, Section 3C, Paragraph 1, "In the last step, we iteratively feed
q
and each
c
i
∈
C
r
to a QA model to extract a likely answer to
q
from
c
i
. The final output of our approach consists of, for each posed
q
, a set of relevant context spans
C
r
, where in each
c
i
∈
C
r
a likely answer to
q
is highlighted. As we discuss in Section IV, we experiment with four alternative QA models, namely BERT, ALBERT, RoBERTa and ELECTRA")[, that are relevant to the conveyance of benefits to the benefit recipient]; and
extracting from the digital compliance material the text passages that are relevant (Abualhaija et al. pg. 40, Section 1, Paragraph 6, "Phase I employs IR-based methods to retrieve the top-
k
context spans which are relevant to the input question") [to the conveyance of benefits to the benefit recipient].
Claim 7
Regarding claim 7, the rejection of claim 6 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the applying [the at least one AI model] further comprises using at least one selected from the group consisting of natural language understanding (NLU) and natural language processing (NLP) (Yoon et al. ¶ [0048], "Compliance starts at the company level. For example, company policy may say that gifts (business, meals and travel) may be accepted only in the best interests of the client, etc. For translating, the system uses heuristics, expert rules (algorithm) and the application of word analysis leverages machine learning. Could be natural language processing") to reduce the extracted text passages to extracted answer text snippets (Yoon et al. ¶ [0047], "Translating the unstructured data into structured data allows the sender to read the compliance requirements that are relevant to the gift. The translation into structured data may be converted into rules. (e.g., no gift in the amount of over $100, no alcohol, etc.) This extends to things like cascade of compliance rules that fit into industries." Structured data such as rules (e.g., no gift in the amount of over $100, no alcohol, etc.) is considered analogous to extracted answer text snippets), each extracted answer text snippet indicating, for a respective one selected from the group consisting of a specific benefit and a specific benefit type, whether conveyance of the selected specific benefit or selected benefit type complies with the relevant compliance policies (Yoon et al. ¶ [0023]-[0024], "The host platform 120 may identify compliance rules that are associated with the domain of the sender 110 and/or the recipient. ... The host platform 120 may identify a gift category or type associated with the gratitude-based message 102 and map the category to a compliance rule that is associated with the sender 110 and/or the recipient 130. The host platform 120 may compare the content of the gift with the content of the mapped compliance rule(s) to determine whether the gift maps to the compliance rule." Mapping the gift category to a compliance rule to check for policy compliance is considered analogous to indicating whether conveyance of a selected benefit type complies with relevant compliance policies).
Abualhaija et al. further disclose wherein the applying the at least one AI model further comprises using at least one selected from the group consisting of natural language understanding (NLU) and natural language processing (NLP) to reduce the extracted text passages to extracted answer text snippets (Abualhaija et al. pg. 40, Section 1, Paragraph 5, "Our approach builds on recent advances in natural language processing (NLP) technologies. QA in NLP is the task of automatically finding the most likely answer to a question posed in NL in a given text passage. In our work, we refer to a single text passage as a context span.").
Claim 8
Regarding claim 8, the rejection of claim 7 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Abualhaija et al. further disclose wherein the using the selected at least one of NLU and NLP comprises providing to an NLU model (Abualhaija et al. pg. 41, Section 2, Paragraph 7, "The models we employ in this work based on BERT and its variants are fine-tuned to address machine reading comprehension (MRC)." BERT is considered analogous to an NLU model) queries (Abualhaija et al. pg. 42, Section 3, Paragraph 1, "The input to the approach is a regulatory document (RegD) and a question (
q
) posed in NL.") [tailored to specific benefits and specific benefit types], the NLU model extracting the answer text snippets based on the queries (Abualhaija et al. pg. 43, Section 3C, Paragraph 1, "In the last step, we iteratively feed
q
and each
c
i
∈
C
r
to a QA model to extract a likely answer to
q
from
c
i
."), and receiving from the NLU model, as responses to the queries, the extracted answer text snippets (Abualhaija et al. pg. 43, Section 3C, Paragraph 1, "The final output of our approach consists of, for each posed
q
, a set of relevant context spans
C
r
, where in each
c
i
∈
C
r
a likely answer to
q
is highlighted.").
Claim 9
Regarding claim 9, the rejection of claim 7 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose classifying an extracted answer text snippet into one class selected from the group consisting of:
a class indicating that the respective selected specific benefit or specific benefit type for that extracted answer text snippet is compliant with the relevant compliance policies;
a class indicating that the respective selected specific benefit or specific benefit type for that extracted answer text snippet is compliant with the relevant compliance policies provided additional conditions are satisfied; and
a class indicating that the respective selected specific benefit or specific benefit type for that extracted answer text snippet is non-compliant with the relevant compliance policies (Yoon et al. ¶ [0050]-[0051], "one or more corporate compliance requirements of the sender and/or the recipient may be detected based on the type of transfer of value. ... the method may automatically detect whether the gift violates compliance requirements, and in response, prevent the message from being transmitted to the recipient." The ability to perform different actions based on the output of a compliance check implies classifying a specific gift and associated compliance rule into either a compliant class or non-compliant class).
Claim 10
Regarding claim 10, the rejection of claim 7 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Abualhaija et al. further disclose generating summary statements for display to a user, each of the summary statements providing a respective one-sentence distillation of one or more extracted answer text snippets in a user-understandable form (Abualhaija et al. pg. 43, Section 3C, Paragraph 1, "The final output of our approach consists of, for each posed
q
, a set of relevant context spans
C
r
, where in each
c
i
∈
C
r
a likely answer to
q
is highlighted. ... the extracted answer is always a short text span in
c
i
(e.g., a part of a sentence)." A short text span is considered analogous to a summary statement. Highlighting likely answers is considered analogous to distilling extracted answer text snippets in a user-understandable form).
Claim 11
Regarding claim 11, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose receiving the prompt from the sender, the prompt identifying the benefit recipient (Yoon et al. ¶ [0021], "the host platform 120 may provide a user interface which allows the sender 110 to select a gift, one or more recipients, add message content, select a transmission means (e.g., email, text, etc.) and send the gratitude-based message 102 to the recipient 130."), wherein the automatically searching for, and downloading, the digital compliance material, the analyzing, and the responding are performed in response to the receiving the prompt (Yoon et al. ¶ [0023], "When the user selects the gift, a compliance detection and notification process may be performed to determine a compliance policy (e.g., an internal policy of an organization, a general policy of an industry, a default policy provided by the host platform 120, or the like) that is associated with the gift.").
Claim 12
Regarding claim 12, the rejection of claim 11 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the at least one identified benefit is a specific benefit indicated by the prompt (Yoon et al. ¶ [0023], "When the user selects the gift, a compliance detection and notification process may be performed to determine a compliance policy... that is associated with the gift."), and wherein the responding indicates whether conveyance of that specific benefit to the identified benefit recipient complies with the relevant compliance policies for conveyance of benefits to that identified benefit recipient (Yoon et al. ¶ [0024], "The host platform 120 may compare the content of the gift with the content of the mapped compliance rule(s) to determine whether the gift maps to the compliance rule. As a non-limiting example, the gift may include tickets to a sporting event. The host platform 120 may detect that a cost of the tickets are $400. In this example, the host platform 120 may detect a compliance rule of the sender 110 or the recipient 130 that prevents gifts of over $150. In this case, the host platform 120 may notify the sender of the compliance rule.").
Claim 15
Regarding claim 15, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose, based on the sender selecting a benefit for conveyance to the benefit recipient (Yoon et al. ¶ [0023], "When the user selects the gift, a compliance detection and notification process may be performed"), the benefit confidently determined to comply with the relevant compliance policies for conveyance of benefits to the benefit recipient (Yoon et al. ¶ [0024], "The host platform 120 may identify a gift category or type associated with the gratitude-based message 102 and map the category to a compliance rule that is associated with the sender 110 and/or the recipient 130. The host platform 120 may compare the content of the gift with the content of the mapped compliance rule(s) to determine whether the gift maps to the compliance rule."), building a request data record that includes a context of sender selection, the context [including results of the applying the at least one AI model,] including the determined at least one compliance policy (Yoon et al. ¶ [0037], "In the example of FIG. 4A, the host platform access company data 420 that is linked to the domain name 412 of the sender and retrieve company-specific compliance policy rules 422 which may include files, documents, web text, PDFs, etc." ¶ [0026], "The database 124 may store the compliance rules and also mappings of gift categories to compliance rules as further explained in the description of FIG. 4A. The database 124 may acquire compliance rules from endpoints such as company-specific data sources 160 and/or industry-related data sources 170.").
Abualhaija et al. further disclose applying at least one AI model (Abualhaija et al. pg. 41, Section 2, Paragraph 7, "A large-scale pre-trained LM can be fine-tuned to solve different downstream NLP tasks, e.g., QA and computing text similarity [22]. The models we employ in this work based on BERT and its variants are fine-tuned to address machine reading comprehension (MRC).").
Claim 16
Regarding claim 16, Yoon et al. disclose a computer system comprising:
a memory (Yoon et al. ¶ [0105], "At least some of the steps in method 1400 may be performed by a computer having a processor executing commands stored in a memory of the computer (e.g., processors 212 and memories 220)."); and
a processor in communication with the memory (Yoon et al. ¶ [0105], "At least some of the steps in method 1400 may be performed by a computer having a processor executing commands stored in a memory of the computer (e.g., processors 212 and memories 220).").
The remaining limitations of claim 16 are similar in scope to that of claim 1 and therefore are rejected for similar reasons as described above.
Claim 17
Regarding claim 17, the rejection of claim 16 is incorporated. The limitations of claim 17 are similar in scope to that of claims 6 and 7 and therefore are rejected for similar reasons as described above.
Claim 20
Regarding claim 20, Yoon et al. disclose a computer program product comprising:
a computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method (Yoon et al. ¶ [0157], " The instructions may be stored in the memory 2204 and implemented in one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer-readable medium").
The remaining limitations of claim 20 are similar in scope to that of claim 1 and therefore are rejected for similar reasons as described above.
Claims 13-14 and 18-19 are rejected under 35 U.S.C. 103 as obvious over Yoon et al. in view of Abualhaija et al. as applied to claim 1 above, and further in view of US Patent Publication 20220198385 A1 (Rudeegraap et al.).
Claim 13
Regarding claim 13, the rejection of claim 11 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the at least one identified benefit comprises a plurality of identified benefits for which conveyance is confidently determined to comply with the relevant compliance policies (Yoon et al. ¶ [0023]-[0024], "When the user selects the gift, a compliance detection and notification process may be performed to determine a compliance policy ... that is associated with the gift. ... The host platform 120 may identify a gift category or type associated with the gratitude-based message 102 and map the category to a compliance rule that is associated with the sender 110 and/or the recipient 130." A category of gifts is considered analogous to a plurality of identified benefits (gifts). Therefore, mapping a category of gifts to a compliance rule is considered analogous to determining that a plurality of benefit complies with relevant compliance policies), and wherein the responding comprises generating and presenting an interface having a list of distinctive benefits from which the sender can select (Yoon et al. ¶ [0029]-[0030], "In 231, the sender 210 may request a list of available gifts from the host platform (e.g., via a gift category API 220). ... In 234, the host platform returns a list of available gifts in the selected category. Here, the user may compose a message 235 which includes a gift selected from the list and send the message in 236 to the host platform via a gift request API 222."), the list of distinctive benefits presented [together] with tags categorizing the benefits by a plurality of unique classes (Yoon et al. ¶ [0029], "In 231, the sender 210 may request a list of available gifts from the host platform (e.g., via a gift category API 220). In 232, the host platform may return a list of gift categories to the sender 210." Gift categories are considered analogous to a plurality of unique classes), the unique classes comprising at least one selected from the group consisting of: benefit type (Yoon et al. ¶ [0029], "In 232, the host platform may return a list of gift categories to the sender 210. For example, gift categories may include beverages, food, tickets, alcohol, gift cards, restaurant vouchers, and the like."), level of compliance with the relevant compliance policies, and location.
Yoon et al. in view of Abualhaija et al. do not disclose all of displaying distinctive benefits together with category tags.
However, Rudeegraap et al. disclose a list of distinctive benefits presented together with tags categorizing the benefits by a plurality of unique classes (Rudeegraap et al. ¶ [0068], "FIG. 5B illustrates screenshot 500B, which includes gift items or “Touches” that the user may choose to include in a gift package. Accordingly, application 522 may classify the items into different categories"), the unique classes comprising at least one selected from the group consisting of: benefit type (Rudeegraap et al. ¶ [0068], "application 522 may classify the items into different categories 540-1 (liquor, e.g., ‘Bourbon’), 540-2 (stationery for handwritten notes), 540-3 (Stationery), 540-4 (one-pagers), 540-5 (case study), 540-6 (Info sheets), 540-7 (Mailer), 540-8 (Stationery), 540-9, 540-10, 540-11 (clothing), 540-12 (clothing), 540-13 (e-book), 540-14 (e-book), and 540-15 (e-book), hereinafter, collectively referred to as “categories 540.”"), level of compliance with the relevant compliance policies, and location.
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Yoon et al. in view of Abualhaija et al. to include Rudeegraap et al.’s categorized display because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, Yoon et al. in view of Abualhaija et al. as modified by Rudeegraap et al.’s categorized display can yield a predictable result of improving user experience since the ability to view categories alongside selectable benefits could make gift comprehension quicker and easier. Thus, a person of ordinary skill would have appreciated including in Yoon et al. in view of Abualhaija et al. the ability to do Rudeegraap et al.’s categorized display since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 14
Regarding claim 14, the rejection of claim 1 is incorporated. Yoon et al. in view of Abualhaija et al. disclose all the elements of the claimed invention as stated above. Yoon et al. further disclose wherein the prompt from the sender encompasses a plurality of benefit recipients (Yoon et al. ¶ [0021], "the host platform 120 may provide a user interface which allows the sender 110 to select a gift, one or more recipients, add message content, select a transmission means (e.g., email, text, etc.) and send the gratitude-based message 102" One or more recipients is considered analogous to a plurality of benefit recipients. See Figure 3, which illustrates the ability for a user to select multiple recipients), wherein (i) the automatically searching for, and downloading, digital compliance material and (ii) the applying [the at least one AI model] are performed for each of the plurality of benefit recipients (Yoon et al. ¶ [0021], "the host platform may perform multiple compliance checks (e.g., for each of the sender and the recipient, for each of multiple recipients, and the like)." ¶ [0049], " FIG. 5 illustrates a method 500 of performing a compliance check on a message according to example embodiments." See Figure 5, which illustrates the entire process of performing a compliance check. Steps 510-520 are considered analogous to automatically searching for, and downloading, digital compliance material. Steps 530-540 are considered analogous to applying), and wherein the responding indicates, for each of the plurality of benefit recipients, a respective [plurality] of identified benefit[s] for which conveyance is confidently determined to comply with the relevant compliance policies for conveyance of benefits to that benefit recipient (Yoon et al. ¶ [0051], "In 530, the method may include determining that the transfer of value is a possible violation of a requirement from among the one or more requirements that are associated with the domain name based on content of the requirement. ... For example, the compliance rules that are relevant to the gift may be displayed on the sender's screen to allow the sender to determine whether they are in violation of the compliance rules.").
Yoon et al. in view of Abualhaija et al. do not disclose all of displaying a plurality of benefits together.
However, Rudeegraap et al. disclose wherein the responding indicates, for each of the plurality of benefit recipients (Rudeegraap et al. ¶ [0091], "Prompt 996 may include an option for a group send, which provides the user with the ability to send multiple gift options to a group of recipients. In some embodiments, the group send may also have the group of recipients vote on which gift they want and the winning item is sent to all recipients in the group."), a respective [plurality] of identified benefit[s] (Rudeegraap et al. ¶ [0067], " FIG. 5A illustrates screenshot 500A, which may include a ‘Touches’ tab 530-1 and a swag store tab 530-2 (hereinafter, collectively referred to as “tabs 530”). Tab 530-1 may include a list of gift packages 535-1, 535-2, 535-3, 535-4, and 535-5 (hereinafter, collectively referred to as “packages 535”) that the user has access to.")
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Yoon et al. in view of Abualhaija et al. to include Rudeegraap et al.’s gift and recipient selection UI.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 13.
Claim 18
Regarding claim 18, the rejection of claim 16 is incorporated. The limitations of claim 18 are similar in scope to that of claims 11 and 13 and therefore are rejected fo