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 .
DETAILED ACTION
Status of the Application
1. The following is a Final Office Action in response to communication received on 3/9/2026. Claims 1, 3-10, and 12-18 are pending in this office action.
Claim Interpretation
2. Claims 1 and 3-9 recite a process as the claims recite a method. Claims 10 and 12-18 recite an article of manufacture as the claims recite a non-transitory computer readable medium with instructions being executed by one or more computer processors.
Response to Amendment
3. Applicant’s amendments to claims 1, 3, 7-10, and 12 are acknowledged. Applicant’s cancellation of claims 2 and 11 are acknowledged.
Response to Arguments
4. On Remarks pages 9-11, Applicant argues the 101 rejection. Here Applicant argues Applicants amendments in combination with the other elements of the claim improve the operation of the computer processor by iteratively searching with broadening criteria until the desired target entity identification. This improves efficiency by stopping when the desired target entity is identified, preventing unnecessary iterations from being executed. The Examiner has carefully considered Applicant’s arguments however the Examiner respectfully disagrees.
First, the Examiner does not interpret the two amended “wherein” clauses in the independent claims of “wherein the transaction information is for a transaction with the desired target entity” and “wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-level search algorithm broadens the search” to limit claim scope, see MPEP 2111.04. As such claim language suggests or makes optional but does not require steps to be performed or limit the claim to a particular structure. As these limitations are interpreted to not limit claim scope they are therefore accordingly interpreted as limitations that do not result in a practical application or significantly more.
However, even if the “wherein” clauses as amended did limit claim scope for which the Examiner does not contend based on the above, these limitations are so broadly recited as a results based claim that they do not include any additional elements beyond the abstract idea.
A multi-level search algorithm as broadly recited in the claim is interpreted as multiple rules, which can be processed or performed as a mental process steps or human activity and therefore part of the abstract idea as broadly recited in the claim.
The amended “wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-;level search algorithm broadens the search” recites mental process or certain methods of organizing human activity steps. It is a mental process and certain methods of organizing human activity steps for a user requesting information to be provided other relevant information of potential interest, for example a user requesting information on cats and another user providing the information to the user (like a secretary, sales person, etc.) knowing the user or looking information up about the user, etc. would provide information on donkeys and pineapples as the user has recently expressed interest in those subjects (donkeys and pineapples are additional levels that broaden the search from just cats requested by the user).
It is noted that “improves efficiency by stopping” and “preventing unnecessary iterations” as argued is not recited nor required by the claims. Further Applicant has not argued where such improvements are referenced or mentioned in Applicant’s specification and upon review the Examiner does not find where such improvements are mentioned in Applicant’s specification. Improvements to the computer are based on the claims and additionally take into consideration improvements disclosed in the specification (see MPEP 2106.05(a)).
Therefore the Examiner respectfully disagrees.
5. On Remarks pages 11, Applicant argues the claim objections and rejections under 112 second/b. Based on Applicant’s amendments and arguments, the Examiner has withdrawn the previous 112 second/b rejections.
6. On Remarks pages 11-14, Applicant argues the rejection under 102 in view of Applicant’s amendments to the claims.
First, the Examiner does not interpret the two amended “wherein” clauses in the independent claims of “wherein the transaction information is for a transaction with the desired target entity” and “wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-level search algorithm broadens the search” to limit claim scope, see MPEP 2111.04. As such claim language suggests or makes optional but does not require steps to be performed or limit the claim to a particular structure. Therefore these limitations that do not limit claim scope, are not interpreted as limitations that distinguish the claims over the prior art.
As to Applicant’s arguments that the searches are not “transaction data” as claimed. The Examiner respectfully disagrees. The claims clearly teach a user searching for a job and taking into account preference information like user previous searches, resumes, and expressed interest in applying for a job which are transaction data as broadly claimed. Further paragraphs 0068 and 0073 go on to teach taking into account other types of preferences like computer size and location based on user’s previous interactions (transactions) with the system. Therefore the Examiner respectfully disagrees.
As to Applicant’s arguments that the reference of Dedhia does not teach the amended “wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-level search algorithm broadens the search” the Examiner respectfully disagrees. The Examiner interprets this to be at least taught in paragraphs 0068, 0070, and 0073,
Here the reference teaches adding search terms to create a more complete search from the original search (see paragraph 0070), where this can be preference information which can be aggregated based on previous interest (see paragraphs 0068 and 0073). The system using this preference data comprises a multi levels search algorithm as it broadens the search because the system is searching and returning information previously not searched or considered in the first user search based on adding in preference data. Here a level could be company size or preferred technology (see paragraph 0073) or salary or location (see paragraph 0068) for example.
Therefore the Examiner respectfully disagrees.
Claim Rejections - 35 USC § 101
7. 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.
8. Claims 1, 3-10, and 12-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim(s) recite(s) collecting various interest and interaction information and using it to provide relevant information to a user or connect a user with another entity.
The claims are recited at such a high level of abstraction that the claims recite observations, evaluations, judgements and or opinions that could be performed in the human mind or with pen and paper and accordingly the claims recite a mental process (see MPEP 2106.04(a)).
Further the idea of collecting various interest and interaction information and using it to provide relevant information to a user or connect a user with another entity, is subject matter related to managing personal behavior or relationships or interactions between people (including social activities, teaching, or following rules or interactions) which is a certain method of organizing human activities (see MPEP 2106.04(a)).
Mental processes and certain methods of organizing human activities are in the groupings of enumerated abstracts ideas, and hence the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the claims merely recite limitations that are not indicative of integration into a practical application in that the claims merely recite:
(1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) and (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
Specifically as recited in the claims:
As per claim 1, the claims recite collecting various interest and interaction information and using it to provide relevant information to a user or connect a user with another entity which are mental process steps or human activities. It is noted a backend is interpreted as a third party performing functions for other parties, which is a function that can be performed as a mental process step or human activity and therefore part of the abstract idea given the broad recitation in the claim. Further a multi-level search algorithm is interpreted as multiple rules, which can be processed or performed as a mental process steps or human activity and therefore part of the abstract idea as broadly recited in the claim. Further it is noted that it is mental process or certain method of organizing human activity steps that rules can broaden or narrow a search as claimed. These are part of the abstract idea.
The additional elements that these mental process steps or human activities are instead being performed by software or specifically as recited “an entity identification computer program executed” and requests from users are coming from “a requestor electronic device” merely results in apply it. Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g. to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more.
Further these mental process or human activity steps being performed instead by software or specifically as recited “an entity identification computer program executed” and requests from users are coming from “a requestor electronic device” merely results in generally linking it to the field of computers.
As per claim 3, the claims recite searching for an entity name of a desired entity, which are human activities or mental process steps as broadly recited in the claim. There are no additional elements in this claim beyond those discussed above in claim 1.
As per claim 4, the claims recite collected information related to the requestor like job position, job responsibility, and past product offered, which are human activities or mental process steps. There are no additional elements in this claim beyond those discussed above in claim 1.
As per claim 5, the claims recite collected information related to past history including engagements and products offered, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by “the entity identification computer program” have been addressed in claim 1.
As per claim 6, the claims recite information returned according to rules (e.g. multi level search algorithm), which are human activities or mental process steps. There are no additional elements in this claim beyond those discussed above in claim 1.
As per claim 7, the claims recite identifying a conflict of interest and restricting an individual from accessing information, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by “the entity identification computer program” have been addressed in claim 1.
As per claim 8, the claims recite prepopulating transaction details with public or private information for the target entity (returned result), which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by “then entity identification computer program” have been addressed in claim 1.
As per claim 9, the claims recite providing a suggestion to work on a transaction involving a target entity based on identification, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by “the entity identification computer program” have been addressed in claim 1.
As per claim 10, the claims recite collecting various interest and interaction information and using it to provide relevant information to a user or connect a user with another entity which are mental process steps or human activities.. Further a multi-level search algorithm is interpreted as multiple rules, which can be processed or performed as a mental process step or human activity and therefore part of the abstract idea as broadly recited in the claim. Further it is noted that it is mental process or certain method of organizing human activity steps that rules can broaden or narrow a search as claimed. These are part of the abstract idea.
The additional elements that these mental process steps or human activities are instead being performed by stored software running on a computer or more specifically as recited in the claims “a non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising:” and requests from users are coming from “a requestor electronic device” merely results in apply it. Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g. to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more.
Further these mental process or human activity steps being performed instead by “a non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising:” and requests from users are coming from “a requestor electronic device” merely results in generally linking it to the field of computers.
As per claim 12, the claims recite searching for an entity name of a desired entity, which are human activities or mental process steps. There are no additional elements in this claim beyond those previously discussed above in claim 10.
As per claim 13, the claims recite collected information related to the requestor like job position, job responsibility, and past product offered, which are human activities or mental process steps. There are no additional elements in this claim beyond those previously discussed above in claim 10.
As per claim 14, the claims recite collected information related to past history including engagements and products offered, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by stored software running on a computer or more specifically as recited in the claims of “further including instructions thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising:” have been addressed in claim 10.
As per claim 15, the claims recite information returned according to rules (e.g. multi level search algorithm), which are human activities or mental process steps. There are no additional elements in this claim beyond those addressed above in claim 10.
As per claim 16, the claims recite identifying a conflict of interest and restricting an individual from accessing information, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by stored software running on a computer or more specifically as recited in the claims “further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising:” have been addressed in claim 10.
As per claim 17, the claims recite prepopulating transaction details with public or private information for the target entity (returned result), which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by software running on a computer or more specifically “further including instructions stored thereon, which when read and executed by the one or more processors, cause the one or more computer processors to perform steps comprising:” have been addressed in claim 10.
As per claim 18, the claims recite providing a suggestion to work on a transaction involving a target entity based on identification, which are human activities or mental process steps. The additional element that these human activities or mental process steps are instead being performed by software running on a computer or more specifically “further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising:” have been addressed in claim 10.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims merely recite limitations that are not indicative of an inventive concept (“significantly more”) in that the claims merely recite:
(1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) and (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), as detailed above with respect to the practical application step.
Claim Rejections - 35 USC § 102
9. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
10. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
11. Claim(s) 1, 3-10, and 12-18 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Dedhia et al. (United States Patent Application Publication Number: US 2008/0140710).
As per claim 1, Dedhia et al. teaches A method for identifying entities of interest, comprising: (see abstract, Examiner’s note: method of providing job search to a job seeker).
receiving, by an entity identification computer program executed by a backend (see paragraphs 0027 and 0037, Examiner’s note: business entity that owns and operates a computer infrastructure connected to a data network in order to provide a job listing service).
and from a requestor via a requestor electronic device, (see paragraph 0028, Examiner’s note: job seeker can use a computing device 102 to communicate with the listing service provider).
transaction information and an entity search term for a desired target entity, wherein the transaction information is for a transaction with the desired target entity; (see paragraphs 0029, 0032, and 0033, Examiner’s note: First examiner notes that the Examiner does not interpret the “wherein” clause to limit claim scope (see MPEP 2114.01), however the Examiner has mapped to the claim in the efforts of compact prosecution. Here the reference teaches receiving search queries and refining results based interactions with the system, which is interpreted as transaction data).
receiving, by the entity identification computer program, (see paragraphs 0037 and 0043, Examiner’s note: performing process by executing instructions).
requestor information for the requestor; (see paragraphs 0052-0053, Examiner’s note: using the resume to determine requestor information).
receiving, by the entity identification computer program, entity preferences for an organization or for the requestor; (see paragraphs 0029, 0035, 0046, and 0050, Examiner’s note: users providing preferences to the system).
applying, by the entity identification computer program, a multi-level search algorithm (see paragraph 0043, Examiner’s note: software running on a computer to perform the functions, which is interpreted as an multi level search algorithm as it takes into account various preferences, interactions, search queries, etc.).
to identify a target entity using the transaction information, the entity search term, (see paragraphs 0029, 0032, 0033, Examiner’s note: receiving search queries and refining results based interactions with the system, which is interpreted as transaction data).
the requestor information, (see paragraphs 0052-0053, Examiner’s note: using the resume to determine requestor information).
and the entity preferences; (see paragraphs 0029, 0035, 0046, and 0050, Examiner’s note: users providing preferences to the system).
Wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-level search algorithm broadens the search; (see paragraphs 0068, 0070, and 0073, Examiner’s note: First examiner notes that the Examiner does not interpret the “wherein” clause to limit claim scope (see MPEP 2114.01), however the Examiner has mapped to the claim in the efforts of compact prosecution. Here the reference teaches adding search terms to create a more complete search from the original search (see paragraph 0070), where can be done through preference information which may be aggregated based on previous interest (see paragraphs 0068 and 0073). The system using this preference data comprises a multi levels search algorithm as it broadens the search because the system is searching and returning information previously not searched or considered in the first user search based on adding in preference data. Here a level could be company size or preferred technology (see paragraph 0073) or salary or location (see paragraph 0068) for example).
. receiving, by the entity identification computer program, an indication that the target entity is the desired target entity; retrieving, by the entity identification computer program, contact information for the target entity; and returning, by the entity identification computer program, the contact information to the requestor (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, and job affinity information).
As per claim 3, Dedhia et al. teaches
wherein the entity search term comprises at least part of an entity name for the desired target entity (see paragraph 0032 and 0034, Examiner’s note: matching based on search queries like “software engineer”).
As per claim 4, Dedhia et al. teaches
wherein the requestor information comprises a job position for the requestor, a job responsibility for the requestor, and a past product offered by the requestor (see paragraphs 0011 and 0052-0053, Examiner’s note: using resume information to provide a more relevant search result for a jobseeker. Here the terms are very broad “a past product offered by the requestor” could include things like education, prior employers, location, industries, specific skills. Further a job position could be prior employer or specific skills, and job responsibility could be industries, specific skills, prior employers, and education (see paragraphs 0052-0053). Further this could additionally read on indication of a previous employment position held by the jobseeker that is similar to the job listing (see paragraph 0011)).
As per claim 5, Dedhia et al. teaches
further comprising: receiving, by the entity identification computer program, historical entity interaction data for a plurality of entities, wherein the historical entity interaction data comprises past engagements with the plurality of entities and past products offered to the entities (see paragraphs 0029, 0066, and 0068, Examiner’s note: teaches interactions or engagements between entities like viewing a job listing, applying for a job listing, or previous employment (see paragraph 0029). Then teaches updating the profile of the user with the metadata of that engaged job listing or information (see paragraphs 0066 and 0068)).
As per claim 6, Dedhia et al. teaches
wherein a first level of the multi-level search algorithm identifies potential target entities from preferred clients that have names that begin with the entity search term, a second level of the multi-level search algorithm adds potential target entities from preferred clients that have names that include the entity search term, a third level of the multi-level search algorithm adds potential target entities from local subsidiaries of preferred clients that have names that begin with the entity search term, and a fourth level of the multi-level search algorithm adds potential target entities from local subsidiaries of preferred clients that have names that includes the entity search term (see paragraph 0032, 0035-0036, 0051, and 0053, Examiner’s note: user search term to compare to different types of metadata (like employer name, job title, location, surrounding areas) to provide results based on search queries and various preferences of the system (see paragraphs 0032 and 0036). Further teaches some positions may be preferred (see paragraph 0035). Further teaches providing jobs based on location preferences (see paragraph 0051 and 0053). Here this is a multi level search algorithm as the Dedhia teaches providing results based on search queries by comparing the search query to various metadata of the listing. Further Dedhia teaches refining the results based on location and user preferences (e.g. user provides preferred results). Here a user can define a local to them result they want rather than for the same company or similar listing in another geographic area like another state. Here “begin” and “include” names are found in the matching of different metadata. Further this broad results based claim could read on returning results based on different metadata categories like employer name vs job title, etc.).
As per claim 7, Dedhia et al. teaches
further comprising: identifying, by the entity identification computer program, an individual in the organization having a conflict of interest with the target entity; and restricting, by the entity identification computer program, the individual from accessing information related to the target entity (see paragraph 0027, 0035, and 0053, Examiner’s note: removing information not relevant (e.g. restricting access) (see paragraph 0035). Further each jobseeker is “an individual in the organization” as they provided past employers information or are a user of the business listing system (see paragraphs 0027 and 0053), and different jobseekers may be removed from different content based on preferences).
As per claim 8, Dedhia et al. teaches
further comprising: pre-populating, by the entity identification computer program, transaction details with public and/or private information for the target entity. (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, job affinity information. It is noted that this is considered at least public information as it is being provided to job seekers in a search engine).
As per claim 9, Dedhia et al. teaches
further comprising: suggesting, by the entity identification computer program, individuals to work on a transaction involving the target entity based on the identification of the target entity. (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, job affinity information.).
As per claim 10, Dedhia et al. teaches A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising: (see paragraphs 0042-0044, Examiner’s note: software included on disks to perform operations).
receiving, from a requestor electronic device, (see paragraph 0028, Examiner’s note: job seeker can use a computing device 102 to communicate with the listing service provider).
transaction information and an entity search term for a desired target entity, wherein the transaction information is for a transaction with the desired target entity; (see paragraphs 0029, 0032, and 0033, Examiner’s note: First examiner notes that the Examiner does not interpret the “wherein” clause to limit claim scope (see MPEP 2114.01), however the Examiner has mapped to the claim in the efforts of compact prosecution. Here the reference teaches receiving search queries and refining results based interactions with the system, which is interpreted as transaction data).
receiving requestor information for the requestor; (see paragraphs 0052-0053, Examiner’s note: using the resume to determine requestor information).
receiving entity preferences for an organization or for the requestor; (see paragraphs 0029, 0035, 0046, and 0050, Examiner’s note: users providing preferences to the system).
applying a multi-level search algorithm (see paragraph 0043, Examiner’s note: software running on a computer to perform the functions, which is interpreted as an multi level search algorithm as it takes into account various preferences, interactions, search queries, etc.).
to identify a target entity using the transaction information, the entity search term, (see paragraphs 0029, 0032, and 0033, Examiner’s note: receiving search queries and refining results based interactions with the system, which is interpreted as transaction data).
the requestor information, (see paragraphs 0052-0053, Examiner’s note: using the resume to determine requestor information).
and the entity preferences; (see paragraphs 0029, 0035, 0046, and 0050, Examiner’s note: users providing preferences to the system).
Wherein each level of the multi-level search algorithm searches for the desired entity using a different search criteria, and each subsequent level of the multi-level search algorithm broadens the search; see paragraphs 0068, 0070, and 0073, Examiner’s note: First examiner notes that the Examiner does not interpret the “wherein” clause to limit claim scope (see MPEP 2114.01), however the Examiner has mapped to the claim in the efforts of compact prosecution. Here the reference teaches adding search terms to create a more complete search from the original search (see paragraph 0070), where can be done through preference information which may be aggregated based on previous interest (see paragraphs 0068 and 0073). The system using this preference data comprises a multi levels search algorithm as it broadens the search because the system is searching and returning information previously not searched or considered in the first user search based on adding in preference data. Here a level could be company size or preferred technology (see paragraph 0073) or salary or location (see paragraph 0068) for example).
receiving an indication that the target entity is the desired target entity; retrieving contact information for the target entity; and returning the contact information to the requestor. (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, job affinity information).
As per claim 12, Dedhia et al. teaches
wherein the entity search term comprises at least part of an entity name for the target desired entity. (see paragraph 0032 and 0034, Examiner’s note: matching based on search queries like “software engineer”).
As per claim 13, Dedhia et al. teaches
wherein the requestor information comprises a job position for the requestor, a job responsibility for the requestor, and a past product offered by the requestor. (see paragraphs 0011 and 0052-0053, Examiner’s note: using resume information to provide a more relevant search result for a jobseeker. Here the terms are very broad “a past product offered by the requestor” could include things like education, prior employers, location, industries, and specific skills. Further a job position could be prior employer or specific skills, and job responsibility could be industries, specific skills, prior employers, and education. (see paragraphs 0052-0053). Further this could read on indication of a previous employment position held by the jobseeker that is similar to the job listing (see paragraph 0011)).
As per claim 14, Dedhia et al. teaches
further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising: (see paragraphs 0042-0044, Examiner’s note: software included on disks to perform operations).
receiving historical entity interaction data for a plurality of entities, wherein the historical entity interaction data comprises past engagements with the plurality of entities and past products offered to the entities. (see paragraphs 0029, 0066, and 0068, Examiner’s note: teaches interactions or engagements between entities like viewing a job listing, applying for a job listing, or previous employment (see paragraph 0029). Then teaches updating the profile of the user with the metadata of that engaged job listing or information (see paragraphs 0066 and 0068)).
As per claim 15, Dedhia et al. teaches
wherein a first level of the multi-level search algorithm identifies potential target entities from preferred clients that have names that begin with the entity search term, a second level of the multi-level search algorithm adds potential target entities from preferred clients that have names that include the entity search term, a third level of the multi-level search algorithm adds potential target entities from local subsidiaries of preferred clients that have names that begin with the entity search term, and a fourth level of the multi-level search algorithm adds potential target entities from local subsidiaries of preferred clients that have names that includes the entity search term. (see paragraph 0032, 0035-0036, 0051, and 0053, Examiner’s note: user search term to compare to different types of metadata (like employer name, job title, location, surrounding areas) to provide results based on search queries and various preferences of the system (see paragraphs 0032 and 0036). Further teaches some positions may be preferred (see paragraph 0035). Further teaches providing jobs based on location preferences (see paragraph 0051 and 0053). Here this is a multi level search algorithm as the Dedhia teaches providing results based on search queries by comparing the search query to various metadata of the listing. Further Dedhia teaches refining the results based on location and user preferences (e.g. user provides preferred results). Here a user can define a local to them result they want rather than for the same company or similar listing in another geographic area like another state. Here “begin” and “include” names are found in the matching of different metadata. Further this broad results based claim could read on returning different metadata categories like employer name vs job title, etc.).
As per claim 16, Dedhia et al. teaches
further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising: (see paragraphs 0042-0044, Examiner’s note: software included on disks to perform operations).
identifying an individual in the organization having a conflict of interest with the target entity; and restricting the individual from accessing information related to the target entity. (see paragraph 0027, 0035, and 0053, Examiner’s note: removing information not relevant (e.g. restricting access) (see paragraph 0035). Further each jobseeker is “an individual in the organization” as they provided past employers information or are a user of the business listing system (see paragraphs 0027 and 0053), and different jobseekers may be removed from different content based on preferences).
As per claim 17, Dedhia et al. teaches
further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising: (see paragraphs 0042-0044, Examiner’s note: software included on disks to perform operations).
pre-populating transaction details with public and/or private information for the target entity. (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, and job affinity information. It is noted that this is considered at least public information as it is being provided to job seekers in a search engine).
As per claim 18, Dedhia et al. teaches
further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising: (see paragraphs 0042-0044, Examiner’s note: software included on disks to perform operations).
suggesting individuals to work on a transaction involving the target entity based on the identification of the target entity. (see paragraphs 0032 and 0071-0072, Examiner’s note: return set of job listings. Further teaches job listings can include metadata such as job title, location, surrounding areas, salary, associated keywords, employer name, identifiers, and job affinity information.).
Conclusion
12. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
13. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Grover et al. (United States Patent Application Publication Number: US 2018/0173802) teaches an expanded job search query to generate job results (see abstract)
Carter et al. (United States Patent Application Publication Number: US 2015/0006422) teaches a system for online employment matching based on a query, weights and compatibility (see paragraphs 0138-0140)
Dumais et al. (United States Patent Application Publication Number: US 2007/0016553) teaches a system for retrieving measures of user activity, attention and interest to provide search results (see abstract and title)
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/KIERSTEN V SUMMERS/Primary Examiner, Art Unit 3626
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