Office Action Predictor
Last updated: April 15, 2026
Application No. 18/038,966

RECOMMENDATION DEVICE, RECOMMENDATION SYSTEM, RECOMMENDATION METHOD, PROGRAM AND STORAGE MEDIUM

Final Rejection §101§103
Filed
May 25, 2023
Examiner
MEINECKE DIAZ, SUSANNA M
Art Unit
3625
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Nec Corporation
OA Round
2 (Final)
31%
Grant Probability
At Risk
3-4
OA Rounds
4y 3m
To Grant
55%
With Interview

Examiner Intelligence

Grants only 31% of cases
31%
Career Allow Rate
211 granted / 689 resolved
-21.4% vs TC avg
Strong +25% interview lift
Without
With
+24.6%
Interview Lift
resolved cases with interview
Typical timeline
4y 3m
Avg Prosecution
47 currently pending
Career history
736
Total Applications
across all art units

Statute-Specific Performance

§101
34.3%
-5.7% vs TC avg
§103
31.7%
-8.3% vs TC avg
§102
11.6%
-28.4% vs TC avg
§112
15.4%
-24.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 689 resolved cases

Office Action

§101 §103
DETAILED ACTION This final Office action is responsive to Applicant’s amendment filed September 11, 2025. Claims 1, 10, and 13 have been amended. Claims 11-12 are canceled. Claims 1-10 and 13 are presented for examination. Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Arguments Applicant's arguments filed September 11, 2025 have been fully considered but they are not persuasive. On page 6 of the response, “Applicant notes that paragraph [0013] of the specification provides for a practical application, namely, that ‘a user can more easily determine validity of a recommended company recommended as a cooperation candidate of a target company.’” Applicant does not explain how the incorporation of the additional elements integrates the abstract ideas into a practical application. Applicant’s arguments are not persuasive. Regarding the art rejection, Applicant submits that the claim amendments are not addressed by the Iguider reference (pages 6-7 of Applicant’s response). The Meyssami reference (previously only applied to the rejection of claim 5) has been incorporated into all of the rejections in order to help address the claim amendments. 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 1-10 and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-10 and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claimed invention is directed to “presenting a recommended company in accordance with a target company” (Spec: ¶ 1) without significantly more. Step Analysis 1: Statutory Category? Yes – The claims fall within at least one of the four categories of patent eligible subject matter. Process (claim 10), Apparatus (claims 1-9, 13) Independent claims: Step Analysis 2A – Prong 1: Judicial Exception Recited? Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite: [Claims 1, 10, 13] carrying out: an extracting process of extracting a recommended company recommended as a cooperation candidate of a target company, from a plurality of companies on the basis of (i) target company information including a cooperation detail desired by the target company and (ii) cooperation candidate company information including a cooperation detail desired by each of the plurality of companies, the plurality of companies being cooperation candidates of the target company; a specifying process of specifying a first important part in the target company information and a second important part in cooperation candidate company information of the recommended company; and a presenting process of presenting the cooperation candidate company information of the recommended company, the first important part, and the second important part, wherein the first important part is at least one important phrase in a need text of the target company, the second important part is at least one important phrase in a need text of the recommended company. Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106.04(a)(1)(III), “[t]he courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. A human user can extract information, perform analysis on the extracted information, and present data (mentally and with the use of pen and paper) for example. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to “presenting a recommended company in accordance with a target company” (Spec: ¶ 1), which (under its broadest reasonable interpretation) is an example of evaluating business relations and of marketing (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity. Extracting relevant information (as recited in the independent claims) is an example of filtering content. MPEP § 2106.04(a)(2)(II)(C) cites the following as an example of managing personal behavior, i.e., organizing human activity: “filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis).” MPEP § 2106.04(a)(2)(III)(D) cites the following as an example of a mental process: “An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356.” 2A – Prong 2: Integrated into a Practical Application? No – The judicial exception(s) is/are not integrated into a practical application. Claim 1 recites a recommendation device, comprising at least one processor, the at least one processor carrying out the recited functions. Claim 10 recites that the recommended method is performed by a recommendation device (in the preamble of the claim). Claim 13 recites a recommendation system, comprising the recommendation device recited in claim 1 and a user terminal, the user terminal carrying out: an input process of obtaining input information; and a displaying process of displaying information presented by the presenting process. The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶¶ 135-139). The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s). The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)). Claim 6 recites wherein: the extracting process includes extracting the recommended company with reference to information outputted from a trained model that receives input of the target company information and the cooperation candidate company information; and the specifying process includes specifying the first important part and the second important part on the basis of a part to which the trained model pays attention in the target company information and a part to which the trained model pays attention in the cooperation candidate company information. Considering that the implementation of the machine learning model and/or the training of the model is performed using processing elements, such an implementation is presented as a generic recitation of machine learning in the claims and as a general link to technology. The machine learning-based processing elements are simply tools to generally automate the underlying process that could be performed by a human. It is further noted that, as described in Applicant’s Specification, the machine learning operations are generic machine learning operations (Spec: ¶¶ 67-71). The Specification presents no assertion that there is any improvement in the automated machine learning process itself. Such a generic recitation of machine learning, as recited in the claims, is little more than automating an analogous process that can be performed by a human. There is no transformation or reduction of a particular article to a different state or thing recited in the claims. Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately. 2B: Claim(s) Provide(s) an Inventive Concept? No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible. Dependent claims: Step Analysis 2A – Prong 1: Judicial Exception Recited? Yes – Aside from the additional elements identified in Step 2A – Prong 2 below, the claims recite: [Claim 2] wherein: the specifying process includes specifying a correspondence between the first important part and the second important part; and the presenting process includes further presenting information indicative of the correspondence. [Claim 3] wherein the cooperation detail includes at least one selected from the group consisting of a name of the company, a description of business of the company, a service provided by the company, a product provided by the company, and a corporate philosophy of the company. [Claim 4] wherein the specifying process includes specifying the first important part and the second important part on the basis of an interword distance between each word included in the target company information and each word included in the cooperation candidate company information. [Claim 5] wherein the specifying process includes specifying the first important part and the second important part on the basis of a level of importance of each word included in the target company information and a level of importance of each word included in the cooperation candidate company information. [Claim 6] wherein: the extracting process includes extracting the recommended company with reference to information outputted from a model that receives input of the target company information and the cooperation candidate company information; and the specifying process includes specifying the first important part and the second important part on the basis of a part to which the model pays attention in the target company information and a part to which the model pays attention in the cooperation candidate company information. [Claim 7] wherein the extracting process includes extracting, as the recommended company, a company other than a competitor company of the target company, with reference to company information of each of the plurality of companies. [Claim 8] wherein the presenting process includes displaying the target company information and the cooperation candidate company information on a display device such that (i) the first important part and a part other than the first important part are displayed in respective different display modes in the target company information and (ii) the second important part and a part other than the second important part are displayed in respective different display modes in the cooperation candidate company information. [Claim 9] wherein the presenting process includes displaying the first important part and the second important part such that a display of the first important part and a display mode of the second important part correspond to each other. The dependent claims further present details of the abstract ideas identified in regard to the independent claims above. Aside from the additional elements, the aforementioned claim details exemplify the abstract idea(s) of a mental process (since the details include concepts performed in the human mind, including an observation, evaluation, judgment, and/or opinion). As explained in MPEP § 2106.04(a)(1)(III), “[t]he courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).” The limitations reproduced above, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting the additional elements identified in Step 2A – Prong 2 below, nothing in the claim elements precludes the steps from practically being performed in the mind and/or by a human using a pen and paper. For example, but for the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the respectively recited steps/functions of the claims, as drafted and set forth above, are a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind and/or with the use of pen and paper. A human user can extract information, perform analysis on the extracted information, and present data (mentally and with the use of pen and paper) for example. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with pen and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Aside from the additional elements, the aforementioned claim details exemplify a method of organizing human activity (since the details include examples of commercial or legal interactions, including advertising, marketing or sales activities or behaviors, and/or business relations and managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions). More specifically, the evaluated process is related to “presenting a recommended company in accordance with a target company” (Spec: ¶ 1), which (under its broadest reasonable interpretation) is an example of evaluating business relations and of marketing (i.e., organizing human activity); therefore, aside from the recitations of generic computer and other processing components (identified in Step 2A – Prong 2 below), the limitations identified in the more detailed claim listing above encompass the abstract idea of organizing human activity. Extracting relevant information (as recited in the independent claims) is an example of filtering content. MPEP § 2106.04(a)(2)(II)(C) cites the following as an example of managing personal behavior, i.e., organizing human activity: “filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis).” MPEP § 2106.04(a)(2)(III)(D) cites the following as an example of a mental process: “An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356.” 2A – Prong 2: Integrated into a Practical Application? No – The judicial exception(s) is/are not integrated into a practical application. The dependent claims incorporate the additional elements of the claims from which they depend. Claim 1 recites a recommendation device, comprising at least one processor, the at least one processor carrying out the recited functions. Claim 9 recites that information is displayed on a display device in a display mode. Claim 10 recites that the recommended method is performed by a recommendation device (in the preamble of the claim). Claim 13 recites a recommendation system, comprising the recommendation device recited in claim 1 and a user terminal, the user terminal carrying out: an input process of obtaining input information; and a displaying process of displaying information presented by the presenting process. The claims as a whole merely describe how to generally “apply” the abstract idea(s) in a computer environment. The claimed processing elements are recited at a high level of generality and are merely invoked as a tool to perform the abstract idea(s). Simply implementing the abstract idea(s) on a general-purpose processor is not a practical application of the abstract idea(s); Applicant’s specification discloses that the invention may be implemented using general-purpose processing elements and other generic components (Spec: ¶¶ 135-139). The use of a processor/processing elements (e.g., as recited in all of the claims) facilitates generic processor operations. The additional elements are recited at a high-level of generality (i.e., as generic processing elements performing generic computer functions) such that the incorporation of the additional processing elements amounts to no more than mere instructions to apply the judicial exception(s) using generic computer components. There is no indication in the Specification that the steps/functions of the claims require any inventive programming or necessitate any specialized or other inventive computer components (i.e., the steps/functions of the claims may be implemented using capabilities of general-purpose computer components). Accordingly, the additional elements do not integrate the abstract ideas into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea(s). The processing components presented in the claims simply utilize the capabilities of a general-purpose computer and are, thus, merely tools to implement the abstract idea(s). As seen in MPEP § 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)). Claim 6 recites wherein: the extracting process includes extracting the recommended company with reference to information outputted from a trained model that receives input of the target company information and the cooperation candidate company information; and the specifying process includes specifying the first important part and the second important part on the basis of a part to which the trained model pays attention in the target company information and a part to which the trained model pays attention in the cooperation candidate company information. Considering that the implementation of the machine learning model and/or the training of the model is performed using processing elements, such an implementation is presented as a generic recitation of machine learning in the claims and as a general link to technology. The machine learning-based processing elements are simply tools to generally automate the underlying process that could be performed by a human. It is further noted that, as described in Applicant’s Specification, the machine learning operations are generic machine learning operations (Spec: ¶¶ 67-71). The Specification presents no assertion that there is any improvement in the automated machine learning process itself. Such a generic recitation of machine learning, as recited in the claims, is little more than automating an analogous process that can be performed by a human. There is no transformation or reduction of a particular article to a different state or thing recited in the claims. Additionally, even when considering the operations of the additional elements as an ordered combination, the ordered combination does not amount to significantly more than what is present in the claims when each operation is considered separately. 2B: Claim(s) Provide(s) an Inventive Concept? No – The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s). As discussed above with respect to integration of the abstract idea(s) into a practical application, the use of the additional elements to perform the steps identified in Step 2A – Prong 1 above amounts to no more than mere instructions to apply the exceptions using a generic computer component(s). Mere instructions to apply an exception using a generic computer component(s) cannot provide an inventive concept. The claims are not patent eligible. 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 1-3, 5, 7-10, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Iguider et al. (Y. Iguider and H. Morita, "Toward Next Generation E-Marketplace for Small Business." International Journal of Computer Information Systems and Industrial Management Applications. ISSN 2150-7988 Volume 5 (2013) 227-234.) in view of Meyssami et al. (US 2009/0132345). [Claim 1] Iguider discloses a recommendation device, comprising at least one processor (p. 229 – “And also with the goal to help bridging the digital divide with traders in many developing countries, especially in rural areas. The system may accept also the information that is captured from handwritten document and transformed to digital data. Moreover the recent advances in on-line data capturing technologies and its widespread deployment in devices like PDAs and notebook PCs is creating large amounts of handwritten data that need to be archived and retrieved efficiently, especially that recognition algorithms and engines are already available for all major language scripts [12][13].”; p. 232 – “The results are automatically visualized via an experimental interactive graphical user interface.” The ability to gather data and present information as disclosed, including through the use of PDAs and PCs implies the use of at least one processor and at least one user terminal.), the at least one processor carrying out: an extracting process of extracting a recommended company recommended as a cooperation candidate of a target company (p. 227 – “The objective of this work is to shift the emarketplaces' focus from search-oriented matching, toward assistance-providing business matching systems for the next generation e-marketplaces for small business. By addressing the issue of business-matching and recommending in business-to-business e-marketplaces, through the use of Collective Intelligence (CI) means. To make the most of CI's capabilities, this work considers also the need for converting the business information available on handwritten documents into electronic data toward enabling it to become searchable online.”; p. 231 – “To study our prototype using real-word data, experimental simulations were conducted based on data collected from JETRO (Japan External Trade Organization)’s online business matching database.”; p. 232 – “To process TTPP business proposals in depth, a set of entries (Figure 9) was indexed into a SQLite database. To proceed, the contents were parsed by randomly looping through TTPP URLs to crawl their entry contents.”), from a plurality of companies on the basis of (i) target company information including a cooperation detail desired by the target company and (ii) cooperation candidate company information including a cooperation detail desired by each of the plurality of companies, the plurality of companies being cooperation candidates of the target company (p. 229 – “Unlike most existing e-marketplaces, where the system usually simply matches companies and lists to the user straightforward search results from available static databases [5], the proposed system model (Figure 3) uses a CI approach toward the process of business-matching and business opportunity recommending. As shown in Figure 3, at first, various data are collected from the collectively submitted users’ business (selling or buying) proposals, as well as from their company’s profile and background. With the goal to allow traders to have access to the untapped business opportunities which are not available electronically, but on paper… The collected data are then processed and carefully indexed. Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”); a specifying process of specifying a first important part in the target company information and a second important part in cooperation candidate company information of the recommended company (p. 229 – “Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”; p. 229 -- PNG media_image1.png 318 448 media_image1.png Greyscale ); and a presenting process of presenting the cooperation candidate company information of the recommended company, the first important part, and the second important part (p. 227 – “The following sections present and discuss a new business-matching and recommending system. The recommended matches are later served via a novel visual interactive graphical interface.”; p. 229 – “Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”). Iguider explains that contents of business proposals are parsed by crawling entry contents and ignoring words that are deemed to not carry important meaning (Iguider: p. 232); however, Iguider does not explicitly disclose wherein the first important part is at least one important phrase in a need text of the target company, the second important part is at least one important phrase in a need text of the recommended company. Meyssami allows for would-be business partners to be identified by matching criteria in the user profiles of the business partners (Meyssami: ¶¶ 62, 141). Attributes used for matching may be given an associated importance measure to convey how critical each attribute is for a match in order to strengthen the match (Meyssami: ¶¶ 178-179). Meyssami also evaluates a degree of association and relative strength of matching criteria (Meyssami: ¶ 110 – “Once again, the specific values presented for each score may be modified as experience dictates by those of ordinary skill in the art to customize the relative strength of each criteria without departing from the spirit and scope of the invention. Likewise, other values and metrics (i.e., behaviors) could be added to the above to provide a more refined scoring for each attendee and the degree of association they have with any given Exhibitor Company.”). This suggests that, when two entities mutually place a similar degree of importance on similar matching criteria and attributes, they are more likely to have common goals. Additionally, Meyssami uses keywords and/or phrases to identify attributes of a user and potential business partners (Meyssami: ¶¶ 78, 83, 86). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Iguider wherein the first important part is at least one important phrase in a need text of the target company, the second important part is at least one important phrase in a need text of the recommended company in order to strengthen the matches (as suggested in ¶ 179 of Meyssami). [Claim 2] Iguider discloses wherein: the specifying process includes specifying a correspondence between the first important part and the second important part (p. 229 – “Table 1. illustrates an example, where a part of the user’s information is scored and matched against the data of other identified business-partner candidates. With the goal to evaluate the user’s compatibility with the identified business-partner candidates, and qualify the potential of their proposed business opportunities, the user’s attributes are mapped against the attributes of the identified partner-candidates, via several correlation means, including the matching via Euclidean Distance Scoring (1).”; p. 229 – PNG media_image2.png 508 446 media_image2.png Greyscale ); and the presenting process includes further presenting information indicative of the correspondence (p. 229 – “To comply with the recommendation of Dr. Engelbart (CI’s founder) about the importance of creating new ways and symbols for structuring facts, to extend the user’s capability of manipulating the created knowledge [1], the matching results and personalized recommendations are later conveyed to the user via a new visual graphic interface, as illustrated by Figure 4 and Table 2…Colors, shapes and sizes are used to symbolize characteristics of the candidate partners, to help the user visually explore the recommended business opportunities via the graphical navigational interface.”; p. 229 – PNG media_image3.png 476 458 media_image3.png Greyscale ; p. 230 – PNG media_image4.png 474 416 media_image4.png Greyscale ). [Claim 3] Iguider discloses wherein the cooperation detail includes at least one selected from the group consisting of a name of the company, a description of business of the company, a service provided by the company, a product provided by the company, and a corporate philosophy of the company (p. 229 – “Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”; p. 229 -- PNG media_image1.png 318 448 media_image1.png Greyscale ). [Claim 5] Iguider identifies business matches based on various parameters (as discussed in the rejection of the independent claim above); however, Iguider does not explicitly disclose wherein the specifying process includes specifying the first important part and the second important part on the basis of a level of importance of each word included in the target company information and a level of importance of each word included in the cooperation candidate company information. Meyssami allows for would-be business partners to be identified by matching criteria in the user profiles of the business partners (Meyssami: ¶¶ 62, 141). Attributes used for matching may be given an associated importance measure to convey how critical each attribute is for a match in order to strengthen the match (Meyssami: ¶¶ 178-179). Meyssami also evaluates a degree of association and relative strength of matching criteria (Meyssami: ¶ 110 – “Once again, the specific values presented for each score may be modified as experience dictates by those of ordinary skill in the art to customize the relative strength of each criteria without departing from the spirit and scope of the invention. Likewise, other values and metrics (i.e., behaviors) could be added to the above to provide a more refined scoring for each attendee and the degree of association they have with any given Exhibitor Company.”). This suggests that, when two entities mutually place a similar degree of importance on similar matching criteria and attributes, they are more likely to have common goals. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Iguider wherein the specifying process includes specifying the first important part and the second important part on the basis of a level of importance of each word included in the target company information and a level of importance of each word included in the cooperation candidate company information in order to strengthen the matches (as suggested in ¶ 179 of Meyssami). [Claim 7] Iguider discloses wherein the extracting process includes extracting, as the recommended company, a company other than a competitor company of the target company, with reference to company information of each of the plurality of companies (p. 229 – “Unlike most existing e-marketplaces, where the system usually simply matches companies and lists to the user straightforward search results from available static databases [5], the proposed system model (Figure 3) uses a CI approach toward the process of business-matching and business opportunity recommending. As shown in Figure 3, at first, various data are collected from the collectively submitted users’ business (selling or buying) proposals, as well as from their company’s profile and background. With the goal to allow traders to have access to the untapped business opportunities which are not available electronically, but on paper… The collected data are then processed and carefully indexed. Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].” The goal is to identify businesses that can work together to fulfill needs that each respective business has, which is an example of recommending companies that are not competitive to one another, at least in regard to identifying well-matched businesses.). [Claim 8] Iguider discloses wherein the presenting process includes displaying the target company information and the cooperation candidate company information on a display device such that (i) the first important part and a part other than the first important part are displayed in respective different display modes in the target company information and (ii) the second important part and a part other than the second important part are displayed in respective different display modes in the cooperation candidate company information (p. 229 – “To comply with the recommendation of Dr. Engelbart (CI’s founder) about the importance of creating new ways and symbols for structuring facts, to extend the user’s capability of manipulating the created knowledge [1], the matching results and personalized recommendations are later conveyed to the user via a new visual graphic interface, as illustrated by Figure 4 and Table 2…Colors, shapes and sizes are used to symbolize characteristics of the candidate partners, to help the user visually explore the recommended business opportunities via the graphical navigational interface.”; p. 229 – PNG media_image3.png 476 458 media_image3.png Greyscale ; p. 230 – PNG media_image4.png 474 416 media_image4.png Greyscale ; p. 230 – “At a later stage, our research aims at creating a CI business-matching system that would enable e-marketplaces to provide automated consulting. The system aggregates the collected data to create new relevant knowledge, by systematically applying best practices of the business world. A personalized expertize would be generated to support users’ decision-making and enhance their market insights and business intelligence. Figure 6 [Figure 5?] illustrates an example where the targeted automated system would systematically uncover strategic partnering opportunities for the user.”; p. 230 – PNG media_image5.png 444 466 media_image5.png Greyscale ). [Claim 9] Iguider discloses wherein the presenting process includes displaying the first important part and the second important part on a display device such that a display mode of the first important part and a display mode of the second important part correspond to each other ((p. 229 – “To comply with the recommendation of Dr. Engelbart (CI’s founder) about the importance of creating new ways and symbols for structuring facts, to extend the user’s capability of manipulating the created knowledge [1], the matching results and personalized recommendations are later conveyed to the user via a new visual graphic interface, as illustrated by Figure 4 and Table 2…Colors, shapes and sizes are used to symbolize characteristics of the candidate partners, to help the user visually explore the recommended business opportunities via the graphical navigational interface.”; p. 229 – PNG media_image3.png 476 458 media_image3.png Greyscale ; p. 230 – PNG media_image4.png 474 416 media_image4.png Greyscale ). [Claim 10] Claim 10 recites limitations already addressed by the rejection of claim 1 above; therefore, the same rejection applies. [Claim 13] Iguider discloses a recommendation system, comprising the recommendation device recited in claim 1 and a user terminal (p. 229 – “And also with the goal to help bridging the digital divide with traders in many developing countries, especially in rural areas. The system may accept also the information that is captured from handwritten document and transformed to digital data. Moreover the recent advances in on-line data capturing technologies and its widespread deployment in devices like PDAs and notebook PCs is creating large amounts of handwritten data that need to be archived and retrieved efficiently, especially that recognition algorithms and engines are already available for all major language scripts [12][13].”; p. 232 – “The results are automatically visualized via an experimental interactive graphical user interface.” The ability to gather data and present information as disclosed, including through the use of PDAs and PCs implies the use of at least one processor and at least one user terminal.), the user terminal carrying out: an input process of obtaining the input information (p. 227 – “The objective of this work is to shift the emarketplaces' focus from search-oriented matching, toward assistance-providing business matching systems for the next generation e-marketplaces for small business. By addressing the issue of business-matching and recommending in business-to-business e-marketplaces, through the use of Collective Intelligence (CI) means. To make the most of CI's capabilities, this work considers also the need for converting the business information available on handwritten documents into electronic data toward enabling it to become searchable online.”; p. 231 – “To study our prototype using real-word data, experimental simulations were conducted based on data collected from JETRO (Japan External Trade Organization)’s online business matching database.”; p. 232 – “To process TTPP business proposals in depth, a set of entries (Figure 9) was indexed into a SQLite database. To proceed, the contents were parsed by randomly looping through TTPP URLs to crawl their entry contents.”), from a plurality of companies on the basis of (i) target company information including a cooperation detail desired by the target company and (ii) cooperation candidate company information including a cooperation detail desired by each of the plurality of companies, the plurality of companies being cooperation candidates of the target company (p. 229 – “Unlike most existing e-marketplaces, where the system usually simply matches companies and lists to the user straightforward search results from available static databases [5], the proposed system model (Figure 3) uses a CI approach toward the process of business-matching and business opportunity recommending. As shown in Figure 3, at first, various data are collected from the collectively submitted users’ business (selling or buying) proposals, as well as from their company’s profile and background. With the goal to allow traders to have access to the untapped business opportunities which are not available electronically, but on paper… The collected data are then processed and carefully indexed. Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”); and a displaying process of displaying information presented by the presenting process p. 227 – “The following sections present and discuss a new business-matching and recommending system. The recommended matches are later served via a novel visual interactive graphical interface.”; p. 229 – “Then, based on the user’s query, and also based on his/her recorded business background and company’s profile, the system conducts various analysis and correlation operations, on the user’s data vs. the data of the potential candidate partners, and their business proposals and needs. With the goal to reduce the search result overload, and instead convey to the user personalized business recommendations specific to his/her needs, interest and background [14].”). Iguider explains that contents of business proposals are parsed by crawling entry contents and ignoring words that are deemed to not carry important meaning (Iguider: p. 232); however, Iguider does not explicitly disclose wherein the first important part is at least one important phrase in a need text of the target company, the second important part is at least one important phrase in a need text of the recommended company. Meyssami allows for would-be business partners to be identified by matching criteria in the user profiles of the business partners (Meyssami: ¶¶ 62, 141). Attributes used for matching may be given an associated importance measure to convey how critical each attribute is for a match in order to strengthen the match (Meyssami: ¶¶ 178-179). Meyssami also evaluates a degree of association and relative strength of matching criteria (Meyssami: ¶ 110 – “Once again, the specific values presented for each score may be modified as experience dictates by those of ordinary skill in the art to customize the relative strength of each criteria without departing from the spirit and scope of the invention. Likewise, other values and metrics (i.e., behaviors) could be added to the above to provide a more refined scoring for each attendee and the degree of association they have with any given Exhibitor Company.”). This suggests that, when two entities mutually place a similar degree of importance on similar matching criteria and attributes, they are more likely to have common goals. Additionally, Meyssami uses keywords and/or phrases to identify attributes of a user and potential business partners (Meyssami: ¶¶ 78, 83, 86). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Iguider wherein the first important part is at least one important phrase in a need text of the target company, the second important part is at least one important phrase in a need text of the recommended company in order to strengthen the matches (as suggested in ¶ 179 of Meyssami). Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Iguider et al. (Y. Iguider and H. Morita, "Toward Next Generation E-Marketplace for Small Business." International Journal of Computer Information Systems and Industrial Management Applications. ISSN 2150-7988 Volume 5 (2013) 227-234.) in view of Meyssami et al. (US 2009/0132345), as applied to claim 1 above, in view of Ekmekci et al. (US 2020/0242299). [Claim 4] Iguider does not explicitly disclose wherein the specifying process includes specifying the first important part and the second important part on the basis of an interword distance between each word included in the target company information and each word included in the cooperation candidate company information. However, Ekmekci gleans information characterizing entities by matching keywords of interest and filtering sentences that include a matched pair of the closest entity and a keyword of interest within a given threshold distance from the closest entity (Ekmekci: ¶ 42). Iguider evaluates documents to glean business information (
Read full office action

Prosecution Timeline

May 25, 2023
Application Filed
Mar 08, 2025
Non-Final Rejection — §101, §103
May 26, 2025
Interview Requested
Jun 05, 2025
Examiner Interview Summary
Jun 05, 2025
Examiner Interview (Telephonic)
Sep 11, 2025
Response Filed
Sep 28, 2025
Final Rejection — §101, §103
Apr 02, 2026
Response after Non-Final Action

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12548039
SYSTEM AND METHOD FOR ESTIMATING IN-STORE DEMAND BASED ON ONLINE DEMAND
2y 5m to grant Granted Feb 10, 2026
Patent 12541751
Robot Fleet Management with Workflow Simulation for Value Chain Networks
2y 5m to grant Granted Feb 03, 2026
Patent 12450620
METHODS AND APPARATUS TO GENERATE AUDIENCE METRICS USING MATRIX ANALYSIS
2y 5m to grant Granted Oct 21, 2025
Patent 12380377
Intelligent Guidance System for Queues
2y 5m to grant Granted Aug 05, 2025
Patent 12380380
INTELLIGENT SCHEDULE MANAGEMENT AND ZONE MONITORING SYSTEM
2y 5m to grant Granted Aug 05, 2025
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
31%
Grant Probability
55%
With Interview (+24.6%)
4y 3m
Median Time to Grant
Moderate
PTA Risk
Based on 689 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in for Full Analysis

Enter your email to receive a magic link. No password needed.

Free tier: 3 strategy analyses per month