DETAILED ACTION
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 . Claims 1-20 are pending.
Claim Objections
Claims 6, 13, and 20 are objected to because of the following informalities.
Claims 6, 13, and 20 recite “retaining the at least one AI model using the at least one insight, wherein the evaluating is further based on the retraining of the at least one AI model, wherein the retaining, which is a typo and should read “retraining.” (Fixed in rejections below.)
Appropriate correction is required.
Claim Rejections - 35 USC § 101 (Non-Statutory Subject Matter)
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 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the computer-readable storage medium don’t exclude transitory signals. Applicant may overcome the rejection by amending to recite a “non-transitory computer-readable storage medium” in claims 15-20. Such an amendment does not constitute new matter.
Appropriate correction is required.
Claim Rejections - 35 USC § 101 (Abstract Idea)
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1 (The Statutory Categories): Is the claim to a process, machine, manufacture, or composition of matter? MPEP 2106.03.
Per Step 1, claims 1-7 are to a method (i.e., a process), claims 8-14 to an apparatus (i.e., a machine). Thus, the claims are directed to statutory categories of invention. However, the claims are rejected under 35 U.S.C. 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The analysis proceeds to Step 2A Prong One.
(Examiner notes that claims 15-20, while failing at Step 1, are considered in the Abstract Idea rejection below, for the purposes of compact prosecution.)
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? MPEP 2106.04.
The abstract idea of claims 1, 8, and 15 is (claim 1 being representative):
validating first user credentials of a first user to create an idea generator account;
receiving an idea package comprising a disclosure from the idea generator account, wherein the disclosure comprises an idea title, an idea summary, and an idea specification;
evaluating the disclosure using at least one model, wherein the at least one model comprises a first model, wherein the first model is configured for assessing novelty, obviousness, and usefulness of the disclosure;
generating a patentability score using the first model based on the assessing of the novelty, the obviousness, and the usefulness of the disclosure, wherein the patentability score corresponds to a metric representing a patentability of the disclosure;
[extracting] the idea title, the idea summary, and the idea specification from the disclosure and encoding the idea title, the idea summary, the idea specification, and the patentability score into an encoded package comprising an encoded idea, an encoded idea summary, an encoded idea specification, and an encoded patentability score for storage;
generating an idea listing, comprising the idea title and the patentability score for display through a listings catalog comprising one or more idea listings, wherein the listings catalog comprises the idea listing; and
notifying a plurality of idea purchaser accounts of the idea listing.
The abstract idea steps italicized above are those which could be performed mentally, including with pen and paper. The steps describe, at a high level, validating a user, receiving an idea package, evaluating a disclosure, generating a patentability score, extracting portions of the disclosure and encoding (i.e., assigning alphanumeric values), generating an idea listing, and notifying a user. These are all steps an administrator could accomplish with pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, including observations, evaluations, judgements, and/or opinions, then it falls within the Mental Processes – Concepts Performed in the Human Mind grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Additionally and alternatively, the abstract idea steps italicized above describe a commercial interaction pertaining to the listing and exchange of intellectual property, which constitutes a process that, under its broadest reasonable interpretation, covers commercial activity. This is further supported by [0002] of applicant’s specification as filed. If a claim limitation, under its broadest reasonable interpretation, covers commercial interactions, including contracts, legal obligations, advertising, marketing, sales activities or behaviors, and/or business relations, then it falls within the Certain Methods of Organizing Human Activity – Commercial or Legal Interactions grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Additionally and alternatively, the abstract idea steps italicized above describe the rules or instructions pertaining to the listing and exchange of intellectual property, which constitutes a process that, under its broadest reasonable interpretation, covers managing personal behavior relationships, interactions between people. This is further supported by [0002] of applicant’s specification as filed. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior relationships, interactions between people, including social activities, teaching, and/or following rules or instructions, then it falls within the Certain Methods of Organizing Human Activity – Managing Personal Behavior Relationships, Interactions Between People grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? MPEP 2106.04.
This judicial exception is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP 2106.05(f).
Claim 1, 8, and 15 recite the following additional elements: received through a first user interface; artificial intelligence (Al); AI; operating an ingestion engine to; in an idea trading platform database; on a second user interface; through operation of a listings generator; through operation of a reporter.
Claim 8 also recites the following additional elements: a computing apparatus; a processor; a memory storing instructions that, when executed by the processor, configure the computing apparatus for.
Claim 15 also recites the following additional elements: a computer-readable storage medium; the computer-readable storage medium including instructions that when executed by a computer, configure the computer for.
These elements are merely instructions to apply the abstract idea to a computer, per MPEP 2106.05(f). Applicant has only described generic computing elements in their specification, as seen in Fig. 14, for example, along with the corresponding sections of applicant’s specification as filed.
Further, the combination of these elements is nothing more than a generic computing system applied to the tasks of the abstract idea. Because the additional elements are merely instructions to apply the abstract idea to a generic computing system, they do not integrate the abstract idea into a practical application, when viewed in combination. See MPEP 2106.05(f).
Therefore, per Step 2A Prong Two, the additional elements, alone and in combination, do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea.
Step 2B (The Inventive Concept): Does the claim recite additional elements that amount to significantly more than the judicial exception? MPEP 2106.05.
Step 2B involves evaluating the additional elements to determine whether they amount to significantly more than the judicial exception itself.
The examination process involves carrying over identification of the additional element(s) in the claim from Step 2A Prong Two and carrying over conclusions from Step 2A Prong Two pertaining to MPEP 2106.05(f).
The additional elements and their analysis are therefore carried over: applicant has merely recited elements that facilitate the tasks of the abstract idea, as described in MPEP 2106.05(f).
Further, the combination of these elements is nothing more than a generic computing system applied to the tasks of the abstract idea. When the claim elements above are considered, alone and in combination, they do not amount to significantly more.
Therefore, per Step 2B, the additional elements, alone and in combination, are not significantly more. The claims are not patent eligible.
The analysis takes into consideration all dependent claims as well:
Dependent claims 2-7, 9-14, and 16-20 recite additional abstract steps and/or information that further narrow the abstract idea. This narrowing of the abstract idea does not integrate it into practical application and/or add significantly more. Some of the dependent claims recite further additional elements, beyond those highlighted above:
Claims 6, 13, and 20: retraining the at least one AI model using the at least one insight, wherein the evaluating is further based on the retraining of the at least one AI model.
Similar to above, these are generic computing processes, claimed in a results-oriented manner, that are equivalent to “apply it,” per MPEP 2106.05(f). Whether viewed alone or in combination, this does not integrate the abstract idea into practical application and/or add significantly more.
Accordingly, claims 1-20 are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 8, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Tran (US 20020095368) in view of Van Luchene (US 20070124166) and Ma (US 20130282598).
Claims 1, 8, and 15
Regarding claim 1, Tran discloses:
A method of operating an idea trading platform {see Abstract: A system supports trading of intellectual property (IP) with a user interface to accept a request to trade an IP asset; and a database coupled to the user interface to store data associated with one or more IP assets, the database supporting the trading of the IP asset.} comprises:
Regarding claim 8, Tran discloses:
A computing apparatus for operating an idea trading platform, the computing apparatus comprising: a processor; and a memory storing instructions that, when executed by the processor {[0028] The portal also provides access to a bid, auction and sale system wherein the computer system establishes a virtual showroom which displays the IPs offered for sale and certain other information, such as the offeror's minimum opening bid price and bid cycle data which enables the potential purchaser or customer to view the IP asset, view rating information regarding the IP asset and place a bid or a number of bids to purchase the IP asset. (It’s noted that the computer system necessarily contains the recited features.)}, configure the computing apparatus for:
Regarding claim 15, Tran discloses:
A computer-readable storage medium for operating an idea trading platform, the computer-readable storage medium including instructions that when executed by a computer {[0028] The portal also provides access to a bid, auction and sale system wherein the computer system establishes a virtual showroom which displays the IPs offered for sale and certain other information, such as the offeror's minimum opening bid price and bid cycle data which enables the potential purchaser or customer to view the IP asset, view rating information regarding the IP asset and place a bid or a number of bids to purchase the IP asset. (It’s noted that the computer system necessarily contains the recited features.)}, configure the computer for:
Regarding claims 1, 8, and 15, Tran discloses:
validating first user credentials of a first user received through a first user interface to create an idea generator account {[0024] After the user signs the agreement by clicking the "Accept" button, he or she will be given a username and password and a registration identification, all of which will be mailed to him at the e-mail address entered in the registration form. [0048] In an exemplary process for marketing an IP asset, as viewed from an IP affiliate's perspective, the IP affiliate registers with the portal and provide credentials, among other information. Next, the process lists the IP affiliate in its directory or list of qualified affiliates after verifying the credential supplied during registration. The affiliate can then be contacted directly by inventors or IP owners, or the affiliate can search for IP assets listed with the portal and contact the owner of the IP asset to represent the owner in marketing the IP asset. Once a party has been identified, the IP affiliate works with the IP owner in developing a marketing plan and prepares marketing collateral. Next, the IP affiliate markets the IP assets, and concludes the transaction by closing a deal or, if time expires, terminates the agreement with the IP owner.};
generating an idea listing, comprising the idea title and the patentability score for display through a listings catalog on a second user interface comprising one or more idea listings through operation of a listings generator, wherein the listings catalog comprises the idea listing {[0047] The IP owner and the buyer can directly deal with each other with respect to payment and exchange of ownership. Alternatively, the portal provides an escrow service to facilitate the trading of IP assets. Using the escrow service, the IP owner provides the portals with the details of the transaction: IP asset identification, selling price, current and future owners, and email addresses in an online form. [0048] In an exemplary process for marketing an IP asset, as viewed from an IP affiliate's perspective, the IP affiliate registers with the portal and provide credentials, among other information. Next, the process lists the IP affiliate in its directory or list of qualified affiliates after verifying the credential supplied during registration. The affiliate can then be contacted directly by inventors or IP owners, or the affiliate can search for IP assets listed with the portal and contact the owner of the IP asset to represent the owner in marketing the IP asset. Once a party has been identified, the IP affiliate works with the IP owner in developing a marketing plan and prepares marketing collateral. Next, the IP affiliate markets the IP assets, and concludes the transaction by closing a deal or, if time expires, terminates the agreement with the IP owner.};
notifying a plurality of idea purchaser accounts of the idea listing through operation of a reporter {[0017] The operations of exemplary buttons are discussed next. First, the Buy button allows a user to bid on a particular asset. In this embodiment, there are no fees charged to the buyer for this service and the seller pays fees. A user can simply search for desired IP assets and submit an offer using an interactive form. Upon receiving an offer, the system forwards it to the seller and notifies the buying party whether the offer has been accepted, rejected, or if there is a counteroffer. If the offer is accepted, the buyer will be mailed a purchase contract and detailed escrow instructions to sign, similar to those used in a real estate or business opportunity transaction.};
Tran doesn’t explicitly disclose, however, Van Luchene, in a similar field of endeavor directed to automated patent preparation, teaches:
using artificial intelligence (Al) models {[0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.};
receiving an idea package comprising a disclosure from the idea generator account, wherein the disclosure comprises an idea title, an idea summary, and an idea specification {The end user can enter additional information such as: [0131] 1. Title [0132] 2. Abstract [0133] 3. Description/Specification [0134] 4. Invention Class and Sub Class [0135] 5. Inventor Name [0136] 6. Inventor City [0137] 7. Inventor State [0138] 8. Inventor Country [0139] 9. Attorney or Agent [0140] 10. PCT Information [0141] 11. Date of Invention [0142] 12. Background of the invention [0143] 13. Invention Figures [0144] 14. Assignee Name [0145] 15. Assignee City [0146] 16. Assignee State [0147] 17. Assignee Country [0148] 18. Claims}.
evaluating the disclosure using at least one artificial intelligence (Al) model, wherein the at least one Al model comprises a first artificial intelligence (Al) model, wherein the first Al model is configured for assessing novelty, obviousness, and usefulness of the disclosure {[0302] Certified Search Database 130, which may store and associate data such as: [0303] a. Search ID [0304] b. Patent Application ID [0305] c. Prior Art ID 1-N [0306] d. Distinguishing Language Over Prior Art 1-N [0307] e. Prior Art Score [0308] f. Novelty Score [0309] g. Usefulness Score [0310] h. Non-obvious Score [0311] i. Search Score [0312] j. Clarity Score; [0161] In an alternate embodiment, the system can recommend one of the previous three choices to an end user based on the current status of an application. According to this embodiment, the system analyzes the patent application document and compares it to previously filed patent applications. The patent application is scored and the system determines whether the application should be sent to a researcher, an attorney, or to the patent office. [0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.};
generating a patentability score using the first Al model based on the assessing of the novelty, the obviousness, and the usefulness of the disclosure, wherein the patentability score corresponds to a metric representing a patentability of the disclosure {[0302] Certified Search Database 130, which may store and associate data such as: [0303] a. Search ID [0304] b. Patent Application ID [0305] c. Prior Art ID 1-N [0306] d. Distinguishing Language Over Prior Art 1-N [0307] e. Prior Art Score [0308] f. Novelty Score [0309] g. Usefulness Score [0310] h. Non-obvious Score [0311] i. Search Score [0312] j. Clarity Score; [0161] In an alternate embodiment, the system can recommend one of the previous three choices to an end user based on the current status of an application. According to this embodiment, the system analyzes the patent application document and compares it to previously filed patent applications. The patent application is scored and the system determines whether the application should be sent to a researcher, an attorney, or to the patent office. [0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.};
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Tran to include the features of Van Luchene. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Van Luchene, in order to facilitate evaluating the strength of a patent {para. [0002] of Van Luchene}.
The combination of Tran and Van Luchene doesn’t explicitly teach, however, Ma, in a similar field of endeavor directed to patent assessment, teaches:
operating an ingestion engine to extract the idea title, the idea summary, and the idea specification from the disclosure and encoding the idea title, the idea summary, the idea specification, and the patentability score into an encoded package comprising an encoded idea, an encoded idea summary, an encoded idea specification, and an encoded patentability score for storage in an idea trading platform database {[0032] The Key Term Analyzer identifies essential terminologies or key terms from one or more parts of a patent, such as topic, abstract, specification and/or patent claims. As described above, these essential terminologies can be used in other process of the system, for example, in Patent Analyzer, to be described later. The Key Term Analyzer employs common natural linguistic processing techniques incorporating POS (Part of Speech) tagging and keyword extraction. In one embodiment of the present invention, topic and abstract sections of a patent are used to extract essential terminologies or key terms. With reference to FIG. 5, an exemplary key term extraction system 509 is described. For each patent, the system firstly extracts its "title" and "abstract" data fields (step 504) to form a raw text. Secondly, in step 505, it adopts a POS tagger to assign part-of-speeches to every word in the raw text. There are several POS tagger systems available in the public domain, such as "Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network" by Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram Singer, in Proceedings of HLT-NAACL 2003, pages 252-259. Thirdly, the system uses a key phrase extraction core algorithm 506 to identify key phrases for the text. Optionally, it stores the key phrases of every patent document in a file for later use, as shown in 507.};
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran and Van Luchene to include the features of Ma. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Ma, in order to further ground any patent assessment in empirical data and/or other information from heterogeneous data sources, thereby producing more realistic and meaningful results {para. [0003] of Ma}.
Claims 2-7, 9-14, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Tran, Van Luchene, and Ma, further in view of Baijal (US 20210117669).
Claims 2, 9, and 16
Regarding claims 2, 9, and 16, Van Luchene further teaches: wherein the method comprises: obtaining one or more insights associated with the novelty, the obviousness, and the usefulness using the Al model based on the evaluating {[0302] Certified Search Database 130, which may store and associate data such as: [0303] a. Search ID [0304] b. Patent Application ID [0305] c. Prior Art ID 1-N [0306] d. Distinguishing Language Over Prior Art 1-N [0307] e. Prior Art Score [0308] f. Novelty Score [0309] g. Usefulness Score [0310] h. Non-obvious Score [0311] i. Search Score [0312] j. Clarity Score; [0161] In an alternate embodiment, the system can recommend one of the previous three choices to an end user based on the current status of an application. According to this embodiment, the system analyzes the patent application document and compares it to previously filed patent applications. The patent application is scored and the system determines whether the application should be sent to a researcher, an attorney, or to the patent office. [0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.}; generating a patent search report based on the obtaining of the one or more insights {[0181] Furthermore, any of the processes described above, such as generation of suggested language, suggested researchers, and suggested attorneys could be performed for the new material. As a further embodiment, a new search request or automated research report could be automatically generated for the new subject matter in the CIP.}; and transmitting the patent search report to the first user through the first user interface {[0151] As another example, the system can perform real time prior art search based on the disclosure as the end user types words into the tool. The system could be configured to dynamically display the most relevant prior art choices based on the words and letters being typed. The prior art being displayed would then change in real time as the end user types in more words to describe the invention. It will be appreciated that such real time searching could be used for any type of searching and not just searching for prior art for inventions.}.
The motivation and rationale to include the additional features of Van Luchene are the same as set forth previously.
The combination of Tran, Van Luchene, and Ma doesn’t explicitly teach, however, Baijal, in a similar field of endeavor directed to patentability assessments, teaches: wherein the at least one Al model further comprises a second artificial intelligence (Al) model; second [AI model] {[0062] When the input claim is determined to be novel, the processor may determine inventiveness of the input claim. For example, the processor 150 may input the input claim to a second neural network model trained based on rejected claims and prior arts suggested by an examiner the Intellectual Property Office as references of the rejected claims to determine the inventiveness of the input claim. For convenience of description, the first neural network model and the second neural network model are distinguished in the description, but the first neural network model and the second neural network model may be implemented as a single neural network model.}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran, Van Luchene, and Ma to include the features of Baijal. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Baijal, in order to facilitate determining patentability of a claim, thereby assisting in determining its value prior to exchange {para. [0002] of Baijal}.
Claims 3, 10, and 17
Regarding claims 3, 10, and 17, Tran further discloses: retrieving a second user historical information of a second user associated with the second user interface {[0035] After the user signs in for the first time, the user will be guided to create a personal profile. The profile, in conjunction with a history of usage from the user, is used to personalize his areas of interest and send updates to the pages that are presented to the user. The personal profile is stored as a secured personal legal profile. Based on this information, the server 100 can create personalized pages for members by dynamically serving-up the content to each user utilizing dynamic HTML, among others.}; and generating the one or more idea listings for the second user based on the selecting of the one or more disclosures {[0047] The IP owner and the buyer can directly deal with each other with respect to payment and exchange of ownership. Alternatively, the portal provides an escrow service to facilitate the trading of IP assets. Using the escrow service, the IP owner provides the portals with the details of the transaction: IP asset identification, selling price, current and future owners, and email addresses in an online form. [0048] In an exemplary process for marketing an IP asset, as viewed from an IP affiliate's perspective, the IP affiliate registers with the portal and provide credentials, among other information. Next, the process lists the IP affiliate in its directory or list of qualified affiliates after verifying the credential supplied during registration. The affiliate can then be contacted directly by inventors or IP owners, or the affiliate can search for IP assets listed with the portal and contact the owner of the IP asset to represent the owner in marketing the IP asset. Once a party has been identified, the IP affiliate works with the IP owner in developing a marketing plan and prepares marketing collateral. Next, the IP affiliate markets the IP assets, and concludes the transaction by closing a deal or, if time expires, terminates the agreement with the IP owner.}.
Van Luchene further teaches: analyzing the idea title, the idea summary, and the idea specification of each of the plurality of disclosures and the second user historical information using [an] artificial intelligence (Al) model, wherein the Al model is configured for mapping a suitability of each of the plurality of disclosures with the second user {[0302] Certified Search Database 130, which may store and associate data such as: [0303] a. Search ID [0304] b. Patent Application ID [0305] c. Prior Art ID 1-N [0306] d. Distinguishing Language Over Prior Art 1-N [0307] e. Prior Art Score [0308] f. Novelty Score [0309] g. Usefulness Score [0310] h. Non-obvious Score [0311] i. Search Score [0312] j. Clarity Score; [0161] In an alternate embodiment, the system can recommend one of the previous three choices to an end user based on the current status of an application. According to this embodiment, the system analyzes the patent application document and compares it to previously filed patent applications. The patent application is scored and the system determines whether the application should be sent to a researcher, an attorney, or to the patent office. [0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.}; selecting one or more disclosures from the plurality of disclosures based on the analyzing {See previous citations to [0151], [0161], [0181], [0184], [0302]- [0312].}.
The motivation and rationale to include the additional features of Van Luchene are the same as set forth previously.
Ma further teaches: retrieving a plurality of encoded packages of a plurality of disclosures {[0032] The Key Term Analyzer identifies essential terminologies or key terms from one or more parts of a patent, such as topic, abstract, specification and/or patent claims. As described above, these essential terminologies can be used in other process of the system, for example, in Patent Analyzer, to be described later. The Key Term Analyzer employs common natural linguistic processing techniques incorporating POS (Part of Speech) tagging and keyword extraction. In one embodiment of the present invention, topic and abstract sections of a patent are used to extract essential terminologies or key terms. With reference to FIG. 5, an exemplary key term extraction system 509 is described. For each patent, the system firstly extracts its "title" and "abstract" data fields (step 504) to form a raw text. Secondly, in step 505, it adopts a POS tagger to assign part-of-speeches to every word in the raw text. There are several POS tagger systems available in the public domain, such as "Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network" by Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram Singer, in Proceedings of HLT-NAACL 2003, pages 252-259. Thirdly, the system uses a key phrase extraction core algorithm 506 to identify key phrases for the text. Optionally, it stores the key phrases of every patent document in a file for later use, as shown in 507.}; obtaining the idea title, the idea summary, the idea specification, and the patentability score of each of the plurality of disclosures from the plurality of encoded packages {See previous citation to [0032].}.
The motivation and rationale to include the additional features of Ma are the same as set forth previously.
The combination of Tran, Van Luchene, and Ma doesn’t explicitly teach, however, Baijal, in a similar field of endeavor directed to patentability assessments, teaches: a first additional artificial intelligence (Al) model; first additional [AI model] {[0062] When the input claim is determined to be novel, the processor may determine inventiveness of the input claim. For example, the processor 150 may input the input claim to a second neural network model trained based on rejected claims and prior arts suggested by an examiner the Intellectual Property Office as references of the rejected claims to determine the inventiveness of the input claim. For convenience of description, the first neural network model and the second neural network model are distinguished in the description, but the first neural network model and the second neural network model may be implemented as a single neural network model.}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran, Van Luchene, and Ma to include the features of Baijal. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Baijal, in order to facilitate determining patentability of a claim, thereby assisting in determining its value prior to exchange {para. [0002] of Baijal}.
Claims 4, 11, and 18
Regarding claims 4, 11, and 18, Van Luchene further teaches: wherein the method comprises: determining a technological field associated with the disclosure using the Al model; executing a search using [an] artificial intelligence (Al) model for obtaining at least one information associated with one or more innovations existing in the technological field; analyzing the at least one information using [an] artificial intelligence (Al) model based on the disclosure; predicting a commercial potential of an idea described in the disclosure using the AI model; generating a commercial potential report based on the predicting; and transmitting the commercial potential report to the first user through the first user interface {See previous citations to [0151], [0161], [0181], [0184], [0302]- [0312]. Also see [0085]: Status Change--shall mean a change in status of a patent application as it moves through the patent process. Changes in status can include but are not limited submitting the application for examination, receiving a certified search for the application, placing the patent application in an examiner queue, receiving an office action for the patent application, receiving a notice of allowance for the patent application, receiving a notice of missing parts for the patent application; receiving a patent number for the patent application, and receiving an indication of interest from a potential licensee for the patent application.}.
The motivation and rationale to include the additional features of Van Luchene are the same as set forth previously.
The combination of Tran, Van Luchene, and Ma doesn’t explicitly teach, however, Baijal, in a similar field of endeavor directed to patentability assessments, teaches: wherein the at least one Al model comprises a third artificial intelligence (Al) model; the third [AI Model]; a second additional [AI model]; a third additional [AI model] {[0062] When the input claim is determined to be novel, the processor may determine inventiveness of the input claim. For example, the processor 150 may input the input claim to a second neural network model trained based on rejected claims and prior arts suggested by an examiner the Intellectual Property Office as references of the rejected claims to determine the inventiveness of the input claim. For convenience of description, the first neural network model and the second neural network model are distinguished in the description, but the first neural network model and the second neural network model may be implemented as a single neural network model. [0063] When the input claim is determined to be not novel, the processor 150 may generate an amended claim based on the input claim. For example, the processor 150 may generate the amended claim by inputting the input claim to a third neural network model trained to generate a claim having improved novelty than the input claim from the input claim. [0064] In addition, when the input claim is determined to be not inventive, the processor 150 may generate the amended claim based on the input claim. For example, the processor 150 may generate the amended claim by inputting the input claim to a fourth neural network model trained to generate a claim having improved inventiveness than the input claim from the input claim. For convenience of description, the third neural network model and the fourth neural network model are distinguished in the description, but the third neural network model and the fourth neural network model may be implemented as a single neural network model.}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran, Van Luchene, and Ma to include the features of Baijal. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Baijal, in order to facilitate determining patentability of a claim, thereby assisting in determining its value prior to exchange {para. [0002] of Baijal}.
Claims 5, 12, and 19
Regarding claims 5, 12, and 19, Tran further discloses: obtaining at least one additional information associated with each of the plurality of disclosures {[0035] After the user signs in for the first time, the user will be guided to create a personal profile. The profile, in conjunction with a history of usage from the user, is used to personalize his areas of interest and send updates to the pages that are presented to the user. The personal profi le is stored as a secured personal legal profile. Based on this information, the server 100 can create personalized pages for members by dynamically serving-up the content to each user utilizing dynamic HTML, among others.}.
Van Luchene further teaches: analyzing the at least one additional information and each of the idea title, the idea summary, and the idea specification of each of the plurality of disclosure using [an] artificial intelligence (AI) model {[0302] Certified Search Database 130, which may store and associate data such as: [0303] a. Search ID [0304] b. Patent Application ID [0305] c. Prior Art ID 1-N [0306] d. Distinguishing Language Over Prior Art 1-N [0307] e. Prior Art Score [0308] f. Novelty Score [0309] g. Usefulness Score [0310] h. Non-obvious Score [0311] i. Search Score [0312] j. Clarity Score; [0161] In an alternate embodiment, the system can recommend one of the previous three choices to an end user based on the current status of an application. According to this embodiment, the system analyzes the patent application document and compares it to previously filed patent applications. The patent application is scored and the system determines whether the application should be sent to a researcher, an attorney, or to the patent office. [0184] The system can be built using any suitable architectural method. Examples of suitable architectural methods include, but are not necessarily limited to: 1) a simple, table based method 2) a rules based system or 3) an artificial intelligence (AI) system such as Neural Net, or Bayesian Algorithm.}; generating at least one insight using the AI model based on the analyzing of the at least one additional information and each of the idea title, the idea summary, and the idea specification {See previous citations to [0151], [0161], [0181], [0184], [0302]- [0312].}; and transmitting the at least one insight to the first user through the first user interface {[0151] As another example, the system can perform real time prior art search based on the disclosure as the end user types words into the tool. The system could be configured to dynamically display the most relevant prior art choices based on the words and letters being typed. The prior art being displayed would then change in real time as the end user types in more words to describe the invention. It will be appreciated that such real time searching could be used for any type of searching and not just searching for prior art for inventions.}.
The motivation and rationale to include the additional features of Van Luchene are the same as set forth previously.
Ma further teaches: retrieving a plurality encoded packages of a plurality of disclosures {[0032] The Key Term Analyzer identifies essential terminologies or key terms from one or more parts of a patent, such as topic, abstract, specification and/or patent claims. As described above, these essential terminologies can be used in other process of the system, for example, in Patent Analyzer, to be described later. The Key Term Analyzer employs common natural linguistic processing techniques incorporating POS (Part of Speech) tagging and keyword extraction. In one embodiment of the present invention, topic and abstract sections of a patent are used to extract essential terminologies or key terms. With reference to FIG. 5, an exemplary key term extraction system 509 is described. For each patent, the system firstly extracts its "title" and "abstract" data fields (step 504) to form a raw text. Secondly, in step 505, it adopts a POS tagger to assign part-of-speeches to every word in the raw text. There are several POS tagger systems available in the public domain, such as "Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network" by Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram Singer, in Proceedings of HLT-NAACL 2003, pages 252-259. Thirdly, the system uses a key phrase extraction core algorithm 506 to identify key phrases for the text. Optionally, it stores the key phrases of every patent document in a file for later use, as shown in 507.}; obtaining an idea title, an idea summary, an idea specification, and a patentability score of each of the plurality of disclosures from the plurality of encoded packages {See previous citation to [0032].}.
The motivation and rationale to include the additional features of Ma are the same as set forth previously.
The combination of Tran, Van Luchene, and Ma doesn’t explicitly teach, however, Baijal, in a similar field of endeavor directed to patentability assessments, teaches: a fourth artificial intelligence (Al) model; fourth additional [AI model] {See previous citations to [0062]-[0064].}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran, Van Luchene, and Ma to include the features of Baijal. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Baijal, in order to facilitate determining patentability of a claim, thereby assisting in determining its value prior to exchange {para. [0002] of Baijal}.
Claims 6, 13, and 20
Regarding claims 6, 13, and 20, Baijal further teaches: retraining the at least one AI model using the at least one insight, wherein the evaluating is further based on the retraining of the at least one AI model, wherein the retraining of the at least one AI model improves an ability of the first AI model for the assessing of the novelty, the obviousness, and the usefulness of the disclosure {See previous citations to [0062]-[0064]. Also see [0068]: The artificial intelligence model may include a plurality of neural network layers. The plurality of neural network layers have a plurality of weight values, respectively, and execute neural network processing through a processing result of a previous layer and processing between the plurality of weights. The plurality of weights of the plurality of neural network layers may be optimized by the training result of the artificial intelligence model. For example, the plurality of weights may be updated to reduce or to minimize a loss value or a cost value obtained by the artificial intelligence model during the training process. The artificial neural network may include deep neural network (DNN), and, for example, and without limitation, include a convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), restricted Boltzmann machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), generative adversarial network (GAN), deep Q-network, or the like, but there is no limitation to these examples.}
The motivation and rationale to include the additional features of Baijal are the same as set forth previously.
Claims 7 and 14
Regarding claims 7 and 14, Van Luchene further teaches: wherein the method comprises: determining at least one risk associated with the patentability of an idea described in the disclosure using the AI model based on the evaluating of the disclosure {See previous citations to [0151], [0161], [0181], [0184], [0302]- [0312]. Also see [0021], which pertains to risk: Degree of infringement--shall mean the statistically measured amount that a product or technical white paper infringes an issued patent application.}.
The motivation and rationale to include the additional features of Van Luchene are the same as set forth previously.
The combination of Tran, Van Luchene, and Ma doesn’t explicitly teach, however, Baijal, in a similar field of endeavor directed to patentability assessments, teaches: wherein the at least one AI model comprises a fourth artificial intelligence (AI) model; fourth [AI model] {{See previous citations to [0062]-[0064].}
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the combination of Tran, Van Luchene, and Ma to include the features of Baijal. Given that Tran is directed to facilitating the exchange of intellectual property, one of ordinary skill in the art would have been motivated to look to Baijal, in order to facilitate determining patentability of a claim, thereby assisting in determining its value prior to exchange {para. [0002] of Baijal}.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
“A Marketplace for Ideas?” (NPL attached), which teaches: Traditionally, patent protection extended only to full-fledged inventions. In recent years, however, the legal landscape has changed. Patent law is gradually extending its reach to cover "embryonic inventions," and even naked ideas. This Essay has two goals. The first is to present an economic case against extending property rights to embryonic inventions and ideas. Specifically, this Essay argues that property rights in ideas will hinder technological progress. This Essay's second goal is to propose an alternative legal regime that would enhance innovation. To this end, this Essay contemplates the possibility of formalizing a very limited and narrow legal entitlement in ideas in order to establish a marketplace where ideas may be exchanged. After rejecting existing models of property and intellectual property protection as the foundation for a market for ideas, we propose an original market design that could enhance innovation without impoverishing the public domain.
US 20030126059, which teaches: An intellectual property (IP) brokering system and method (0110) incorporating an expert system permitting a customer (0120) to automate and optimize the use of IP agents (0130) to affect customer product realization (0140) is disclosed. The present invention in some preferred embodiments permits a customer to define a knowledge database with background and customer sensitivities as well as a requirements database for a given product to be created. This information is then mapped to available technical resources and design architectures by the expert system that then generates an optimized execution plan based on available resources. The disclosed invention permits global optimization of the customer requirements by coordinating disparate IP agents in a unified fashion to achieve an optimal utility function with respect to the desired customer product. The system as disclosed may include a wide variety of optimization algorithms and additionally may permit feedback to the customer to allow recursive optimization to occur. The methods as disclosed herein within a variety of preferred systems contexts permit IP to be brokered and granularized by allowing projects to be fractured according to system functionality and subsequently brokered out for optimal cost realization via a globally-connected IP resource acquisition and coordination system. The present invention is particularly well suited for application as a management element in a counter terrorism information technology system to minimize the impact and social disruption associated with terrorist events.
US 20200219215, which teaches: An embodiment of the present invention provides a patent monetary value evaluation method. The method includes: obtaining a patent factor of a subject patent; obtaining commercial data of a company holding the patent; obtaining technical market information of a technology related to the patent in an application country; and estimating monetary value of the patent by using a preset calculation model based on the patent factor, the commercial data, and the technical market information, where the calculation model comprises a calculation function and variable coefficients corresponding to the patent factor, the commercial data, and the technical market information, and input variables of the calculation function include a product of the patent factor and the corresponding variable coefficient, a product of the commercial data and the corresponding variable coefficient, and a product of the technical market information and the corresponding variable coefficient.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN SAMUEL WASAFF whose telephone number is (571)270-5091. The examiner can normally be reached Monday through Friday 8:00 am to 6:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SARAH MONFELDT can be reached at (571) 270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JOHN SAMUEL WASAFF
Primary Examiner
Art Unit 3629
/JOHN S. WASAFF/Primary Examiner, Art Unit 3629
Prosecution Insights