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 .
Response to Arguments
Applicant's arguments and amendments received February 04, 2026 have been fully considered. with regard to 35 U.S.C. § 101 and 35 U.S.C. § 102, Applicant argues that the cited prior art does not disclose “see applicant argument pages 5-7”. This language corresponds to claims 1, 3-6 and 7.
As such, these have been considered but they are not persuasive as addressed below. See the rejection how the art on record reads on the claimed invention as well as the examiner's interpretation of the cited art in view of the presented claim set as outlined below. Furthermore, in response to applicant argument rejection under 35 U.S.C. § 101 the examiner stands with the rejection since storing and retrieving information in memory element that the courts have recognized as well-understood, routine, conventional activity.
Examiner is forced to interpret the claim limitations as broadly and as reasonably possible, in determining patentability of the disclosed invention. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir.1993).
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. MPEP 2106.05 (d)(II)
At least: Receiving or transmitting data over a network, sending messages over a network, computer receives and sends information over a network, Storing and retrieving information in memory. The claimed invention falls within similar to the court recognized computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner. As such, the examiner stands with the rejection.
Applicant argument in regarding rejection under 35 U.S.C. § 102, the cited art or art of Lee re-verification or filtering process consider excluding candidates that are not needed final output.
Applicant argument in regarding the claimed invention “candidate hypothesis” and “set of the generated candidate hypotheses”.
Lee teaches:
[0066] The abductive reasoning method may be a reasoning method where if a phrase “looking for a assassinated person” is included in a query, there is a possibility that a phrase ‘died person’ or ‘killed person’ instead of a phrase ‘assassinated person’ is described in a resource such as an actual knowledge base or Internet encyclopedia, and thus, by extending a word ‘assassinated’ to another form or extending to synonyms, that a person to look for is died is found. That is, the abductive reasoning unit 166 may perform a function of reasoning out a similarity between a query and an answer hypothesis by extending a meaning of the word. The abductive reasoning method may be, for example, a meaning similarity calculation algorithm for words and sentences based on deep learning.
[0069] The answer verifying module 170 may compare the calculated reliability ratio with a predetermined threshold value. If the calculated reliability ratio is equal to or more than the predetermined threshold value, a final answer reasoned out by the reliability reasoning unit 124 may be determined as not being against a query axiom, and the answer verifying module 170 may not perform re-verification on the final answer reasoned out by the reliability reasoning unit 124.
[0070] On the other hand, if the calculated reliability ratio is less than the predetermined threshold value, the reliability of a No. 1 rank final answer reasoned out by the reliability reasoning unit 124 cannot be ensured, and thus, the answer verifying module 170 may perform a re-verification process of again determining an answer candidate, which is the highest in similarity with the query axiom, as No. 1 rank from among answer candidates.
As outlined above, the abductive reasoning of Lee, provides an output based on input (background history and query) with the process of re-verification from among answer candidates, similar to the claimed invention candidate hypothesis based on input “background history and query” to get a generate set of candidate hypothesis. As such, the examiner stands with the rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 2-6 and 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 6 recites “generating…, determining…, excluding.. and searching…”. These claimed steps are collecting and analyzing information which are similar to the concepts identified by the courts as abstract ideas, such as collecting information, analyzing it, and displaying certain results of the collection and analysis (Elec. Power Grp., LLL v. Alstom S.A, 119 USPQ2d 1739 (Fed. Cir. 2016)).
The claims does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because the claim recites additional elements a “processor and memory”, Generic computer elements such as these performing generic computer functions, when viewed either individually or as an ordered combination, do not amount to significantly more than the abstract idea as they would be routine in any computer implementation.
The claim does not include significant element that are sufficient to amount to significantly more than the judicial exception.
Claims 1 and 3-5 list all similar elements of claim 6, but in apparatus form rather than method form. Therefore, the supporting rationale of the rejection to claim 6 applies equally as well to claims 1 and 3-5. The claims does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because the claim recites additional elements a “processor and memory”. Generic computer elements such as these performing generic computer functions, when viewed either individually or as an ordered combination, do not amount to significantly more than the abstract idea as they would be routine in any computer implementation.
Claim 7 list all the similar elements of claim 1, but in non-transitory computer-readable storage medium form rather than method form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claim 7. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because the claim recites additional elements a “non-transitory computer-readable medium including instructions that, when executed by at least one processor of a computer system, cause the computer system to perform”. Generic computer elements such as these performing generic computer functions, when viewed either individually or as an ordered combination, do not amount to significantly more than the abstract idea as they would be routine in any computer implementation.
Claim Rejections - 35 USC § 102
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.
Claims 1-7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. US 2018/0011927.
In regarding to claim 1 Lee teaches:
1. An abductive reasoning apparatus comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: generate a candidate hypothesis from background knowledge and a query logical expression,
[0020] The query input unit 110 may output a natural language query sentence (hereinafter referred to as a query) to the system managing module 120.
[0026] The integration unit 122 may integrate answer candidates processed by the modules 140, 150, 160 and 170 and features of the answer candidates and may transfer a result of the integration to the reliability reasoning unit 124.
Lee, 0019-0026 and Figs. 1, 5, emphasis added.
the background knowledge being a set of given rules that if an antecedent holds, a consequent holds, and the query logical expression indicating observed information by using a logical expression;
[0032] The query axiom generating module 130 may extract desired information, such as word-based answer type information (hereinafter referred to as word answer type information), meaning-based answer type information (hereinafter referred to as meaning answer type information), query type information, and query restriction information, from the input query and the generated entailment query and may generate various query axioms, which are to be used for finding an answer, from the extracted information.
Lee, 0032 and Figs. 1, 5, emphasis added.
determine whether or not the generated candidate hypothesis contradicts a logical constraint to be satisfied by the generated candidate hypothesis and exclude the candidate hypothesis from a set of the generated candidate hypotheses when the candidate hypothesis contradicts the logical constraints;
0050] Moreover, the answer candidate filtering module 150 may filter (or verify) the input answer candidates by using query axioms corresponding to the word answer type information, the meaning answer type information, and the query restriction information among the input query axioms. Here, the answer candidates may include the first answer candidates generated by the retrieval-based answer candidate generating unit (142 in FIG. 2) and the second answer candidates generated by the knowledge base-based answer candidate generating unit (146 in FIG. 2).
Lee, 0050 and Figs. 1, 5, emphasis added.
and search for a best hypothesis based on the set after the exclusion and then output the best hypothesis.
0062] The deductive reasoning unit 164 may reason out an answer by calculating a similarity with a knowledge base. That is, the deductive reasoning unit 164 may request entity-property combinations included in a query and entity-property combinations included in an answer hypothesis from a knowledge base to obtain a similarity of the answer hypothesis from the knowledge base.
[0067] Referring again to FIG. 1, the answer verifying module 170 may again verify a result of the reasoning by the reliability reasoning unit 124, for correcting an error of probabilistic answer reasoning by the reliability reasoning unit 124.
Lee, 0062-0067 and Figs. 1, 5, emphasis added.
wherein the at least one processor is further configured to execute the instructions to: each time generating one candidate hypothesis, determine whether or not the candidate hypothesis contradicts the logical constraint, and if the candidate hypothesis contradicts the logical constraint, exclude the candidate hypothesis from the set.
[0070] On the other hand, if the calculated reliability ratio is less than the predetermined threshold value, the reliability of a No. 1 rank final answer reasoned out by the reliability reasoning unit 124 cannot be ensured, and thus, the answer verifying module 170 may perform a re-verification process of again determining an answer candidate, which is the highest in similarity with the query axiom, as No. 1 rank from among answer candidates.
[0071] A result of the re-verification may be input to the system managing module 120, and the system managing module 120 may detect a final answer, which is again reasoned out, as a response according to the re-verification result.
[0076] Subsequently, in step S515, answer candidates may be generated from the input query. Here, the generated answer candidates may include a first answer candidate and a second answer candidate. The first answer candidate may be an answer candidate generated from a document retrieved from an unstructured knowledge base (144 in FIG. 2) by using keywords included in the input query, and the second answer candidate may be an answer candidate which is generated from the previously built structured knowledge base 146 by using a combination of entity and property obtained by parsing a sentence structure of a query.
Lee, 0070-0076 and Figs. 1, 5, emphasis added.
In regarding to claim 3 Lee teaches:
3. The abductive reasoning apparatus according to claim 2, wherein the at least one processor is further configured to execute the instructions to: extend the set by attempting to generate the next candidate hypothesis after the exclusion, and search for the best hypothesis after convergence of the extension of the set and then output the best hypothesis.
Lee, 0070-0076 and Figs. 1, 5.
In regarding to claim 4 Lee teaches:
4. The abductive reasoning apparatus according to claim 2, wherein the at least one processor is further configured to execute the instructions to: list, each time generating one of the candidate hypotheses, the logical constraint to be satisfied by the generated candidate hypothesis, and each time the logical constraint is listed, determine whether or not the candidate hypothesis contradicts the logical constraint, and if the candidate hypothesis contradicts the logical constraint, exclude the candidate hypothesis from the set.
Lee, 0070-0076 and Figs. 1, 5.
In regarding to claim 5 Lee teaches:
5. The abductive reasoning apparatus according to claim 4, wherein the at least one processor is further configured to execute the instructions to: construct the set of candidate hypotheses by extending a directed graph corresponding to the set of candidate hypotheses, and list the logical constraints to be satisfied by the extension of the directed graph.
Lee, 0070-0076 and Figs. 1, 5.
Claims 6-7 list all similar elements of claim 1, but in method and non-transitory readable medium form rather than apparatus form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claims 6-7.
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Becker et al. US 2009/0165110 see at least Figs. 1-4
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL T TEKLE whose telephone number is (571)270-1117. The examiner can normally be reached Monday-Friday 8:00-4:30 ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William Vaughn can be reached at 571-272-3922. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL T TEKLE/Primary Examiner, Art Unit 2481
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