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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) [and associated disclosure] is/are:
“text input unit (3)” [Fig. 1, Element 3, Specification: P[0017], P[0029]]
“an in-text word extracting unit (5)” [Fig. 1, Element 5, Specification: P[0017], P[0029]]
“a key sentence extracting unit (7)” [Fig. 1, Element 7, Specification: P[0017], P[0029]]
“a text evaluating unit (9)” [Fig. 1, Element 9, Specification: P[0017], P[0029]]
as recited in claim 7.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is mental process without significantly more.
Independent claims 1, 7, 8, and 9 regard a computer-based learning support method, system, program, and non-transitory computer readable information recording medium that, as drafted under its broadest reasonable interpretation (BRI), covers identifying words and phrases within text and evaluating the text based on the identified phrases and stored evaluation information. For example, under the BRI the method relates to: a text input step in which a text to be evaluated is input into the computer (a person can receive or read a text to be evaluated mentally or with a pen and paper); an in-text word extracting step of extracting an in-text word as a word included in the text to be evaluated by the computer (a person can mentally identify a particular word contained in a written text, ex., by reading or underlining the word); a key sentence extracting step of extracting a key sentence included in the text to be evaluated by the computer, the key sentence including one or more in-text words and one or more postpositional particles (a person can mentally identify words and their associated grammatical particles and identify the resulting phrase or sentence, (ex. by reading or marking the words and particles with a pen and paper)); and a text evaluating step of evaluating the text on a basis of the key sentence by the computer, wherein the text evaluating step includes a step of reading evaluation information relating to the key sentence from a storage unit (a person can evaluate a text based on an identified phrase by consulting previously stored information, (ex. an answer key, table, dictionary, or list)), and the evaluation information is information relating to whether the key sentence is correct as the text to be evaluated, or information relating to which category the key sentence belongs to (a person can mentally compare a sentence to known information to determine whether it is correct or can mentally classify the sentence into a particular category).
As described above, these limitations can be carried out as a series of mental steps. The judicial exception is not integrated into a practical application because the only additional elements recited are non-transitory computer-readable readable information recording medium that is conventional components that utilizes the basic functions of a computer.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as described above, the only additional elements recited are a non-transitory computer-readable information storing medium that is conventional components that utilizes the basic functions of a computer.
The remaining dependent claims fail to add patent eligible subject matter to independent claim 1:
Claim 2 simply adds inputting speech into the computer and analyzing the speech to not obtain the text to be evaluated, which does not make the underlying text evaluation patent eligible because a person can listen to speech and identify or transcribe the words spoken mentally with a pen and paper. To the extent a computer performs speech recognition, the claim merely uses conventional speech recognition to obtain the information subject to the mental process.
Claim 3 simply specifies that the text to be evaluated is a descriptive text or an answer text, which merely limits the type of information being evaluated and does not alter the mental nature of identifying and evaluating the content of that text.
Claim 4 simply specifies that the evaluation information indicates which category the key sentence belongs to, which is itself a mental classification that a person can perform by reading the key sentence and assigning it to a particular category mentally or with a pen and paper.
Claim 5 simply specifies that the key sentence may be a group of words that are contiguous or dispersed within the text, which a person can determine mentally or with a pen and paper by identifying words occurring next to each other or at separate locations within a text.
Claim 6 simple applies the method of claim 1 to a computer-based learning support method, which merely limits the abstract text-evaluation process to a particular field of use. A teacher or tutor can mentally evaluate a learner’s answer by identifying relevant words or phrases and determining whether the answer is correct or belongs to a particular category.
Claim 8 is also 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 under the grounds of not falling within one of the four enumerated statutory categories as being directed to a computer program.
Claim Rejections - 35 USC § 103
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1 and 3-9 are rejected under 35 U.S.C. 103 as being unpatentable over Leacock et al. (hereinafter Leacock) (US 20030200077 A1) in view of Sumida et al. (hereinafter Sumida) (JP-2013178633-A) (see attached translated copy for page numbers).
Regarding claim 1, Leacock discloses:
A method for evaluating a text by a computer, comprising (Leacock, P[0004]: "a method for grading constructed responses is utilized to automatically score short answers"):
a text input step in which a text to be evaluated is input into the computer (Leacock, P[0022]: "the concept rater module may be further configured to accept student responses (or constructed responses) in a file. The file format may be ASCII text, a formatted word processing document (e.g., WORDPERFECT, MICROSOFT WORD, etc.) and other similar text processing documents.", student's textual answer to be evaluated is supplied to the computerized concept rater system);
an in-text word extracting step of extracting an in-text word as a word included in the text to be evaluated by the computer (Leacock, P[0026]-P[0027]: "Tokenization is generally a process where punctuation is separated away from words.", "determine the respective part-of-speech for each word in the formatted output file", Leacock computer-processes the input response into individual words and identifies the words occurring);
and
a text evaluating step of evaluating the text on a basis of the key sentence by the computer (Leacock, P[0022]: "The canonical representation of the constructed response is compared against the canonical representation of the model answer by the concept rater module. A score is generated from the number of matches of concepts in the topics between the canonical representation of the model answer and the canonical representation of the constructed response. ", Leacock further extracts syntactical chunks and a predicate-arguments data structure from each sentence before performing the comparison (thus, the computer evaluates the input answer based on extracted linguistic/conceptual structures)), wherein the text evaluating step includes a step of reading evaluation information relating to the key sentence from a storage unit (Leacock, P[0024]: "The model answer 120 may be considered as a gold standard answer for a given short answer question. ", P[0020]: "the gold standard answer provide a grading key for the concept rater module", the student's canonical representation is then compared against that model representation and a score is generated from concept matches. Leacock's computer system expressly includes memory and secondary storage containing the software/data used by the concept rater system. Thus, stored model answer/concept information constituting the grading key is accessed and used to evaluate the extracted concepts of the response.),
Leacock does not explicitly disclose:
a key sentence extracting step of extracting a key sentence `included in the text to be evaluated by the computer, the key sentence including one or more in-text words and one or more postpositional particles;
and
the evaluation information is information relating to whether the key sentence is correct as the text to be evaluated, or information relating to which category the key sentence belongs to;
However, Sumida discloses:
a key sentence extracting step of extracting a key sentence `included in the text to be evaluated by the computer, the key sentence including one or more in-text words and one or more postpositional particles (Sumida, Page 12 top-middle: "query case element, a query case particle, and a query predicate", Sumida extracts from an input sentence/query a predicate phrase formed from one or more case elements (ex. nouns/content words) together with Japanese case particles and a predicate. Thus the extracted phrase is contained in the input text and includes content words plus postpositional/case particles. The reference specifically explains that a case particle attaches to a noun or noun equivalent and expresses its grammatical relationship to another word.);
and
the evaluation information is information relating to whether the key sentence is correct as the text to be evaluated, or information relating to which category the key sentence belongs to (Sumida, Page 13 Top: "Evaluation polarity dictionary storage means for storing evaluation words associated with semantic attributes related to evaluation;", Page 8 top: "When the predicate matches the evaluation word, the ascending predicate phrase derivation unit 123 assigns the semantic attribute associated with the evaluation word to the predicate.", Sumida assigns an evaluation related semantic classification (ex. positive, negative, or neutral) to a predicate contained in the extracted predicate phrase. Thus, under the "or" category branch of the limitation, Sumida teaches evaluation information relating to the category to which the extracted linguistic structure belongs.).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Leacock in view of Sumida. Doing so would have brought Sumida’s predicate-phrase analysis including case elements and case particles (Sumida, Abstract) with Leacock’s automated answer-evaluation system (Leacock, Abstract, P[0020]-P[0025]) because doing so would have predictably allowed Leacock’s evaluator to account for grammatical relationships between identified words when determining whether a student response corresponds to the model answer, thus, improving the contextual accuracy of the automated answer evaluation.
Regarding claim 3, the combination of Leacock and Sumida discloses the method according to claim 1.
The combination further discloses:
wherein
the text to be evaluated is a descriptive text or an answer text (Leacock, P[0003]: "Another method of evaluating students includes utilizing test questions that require a constructed response, i.e., an answer having between a phrase and several paragraphs.", P[0025]: "The concept rater module 110 may be further configured to process a student constructed response (or answer) into a canonical representation. ", Leacock evaluates a student answer, which directly reads on the claimed alternative that the text to be evaluated is an answer text.).
Regarding claim 4, the combination of Leacock and Sumida discloses the method according to claim 1.
The combination further discloses:
wherein
the evaluation information is information relating to which category the key sentence belongs to (Sumida, "stores evaluation words associated with semantic attributes related to evaluation.", Sumida explains that its evaluation-polarity dictionary associates evaluation words with semantic attributes such as positive or negative. The predicate-phrase derivation unit searches that dictionary and, when a predicate matches an evaluation word, assigns its associated semantic attribute. Sumida's example then associates the resulting predicate phrase with its semantic attribute in the search index. Thus, the information identifies an evaluative category associated with the extracted particle containing predicate phrase reading on information relating to which category the claimed key sentence belongs).
Regarding claim 5, the combination of Leacock and Sumida discloses the method according to claim 1.
The combination further discloses:
wherein the key sentence is allowed to be a group of words that are either contiguous or dispersed within the text to be evaluated (Leacock, P[0040]: "The syntactic-chunker function may be configured to group the individual tagged words of the student's constructed response 130 into larger syntactic phrases, i.e., a partial parse, commonly known as chunks, such as noun phrases, verb phrases, prepositional phrases, and other similar grammatical phrases.", P[0041]: "A tuple may be considered a data structure that is formed when the predicate and its respective arguments are extracted from a sentence.", P[0041]: "The PA restructuring module 330 may be configured to select a sentence from the syntactic output file 325, which has been labeled and grouped according to grammar rules, and extract a predicate and the respective arguments from the selected sentence", Leacock groups words from the evaluated text into larger grammatical phrases and also extracts a predicate together with its associated arguments from a sentence. Thus, Leacock teaches a key linguistic structure comprising a group of words from the evaluated text. Under the disjunctive "either contiguous or dispersed language, the disclosed syntactic phrase read on at least he contiguous alternative.).
Regarding claim 6, the combination of Leacock and Sumida discloses the method according to claim 1.
The combination further discloses:
comprising a step of evaluating the text to be evaluated based on the method according to claim 1 (Leacock, P[0003] Another method of evaluating students includes utilizing test questions that require a constructed response, i.e., an answer having between a phrase and several paragraphs.", P[0004]: "a method for grading constructed responses is utilized to automatically score short answers.", P[0022]: "A score is generated from the number of matches of concepts in the topics between the canonical representation of the model answer and the canonical representation of the constructed response. The score may represent the student's ability to cover all the key concepts within the subject matter of the tested subject matter.", Leacock uses a computer-implemented method to evaluate a student's textual answer and generate a score reflecting the student's understanding/coverage of key concepts. Thus, Leacock directly teaches a computer-based learning support method that evaluates the text to be evaluated.).
Regarding claim 7, claim 7 recites the system corresponding to the method of claim 1 and is rejected for the same reasons as above.
The combination further discloses:
A system (1) for evaluating a text by a computer, comprising (Leacock, P[0005]):
Regarding claim 8, claim 8 recites the program corresponding to the method of claim 1 and is rejected for the same reasons as above.
The combination further discloses:
A program for causing a computer to execute a method for evaluating a text, the method comprising (Leacock, P[0006]):
Regarding claim 9, claim 9 recites the non-transitory computer readable information recording medium corresponding to the method of claim 1 and is rejected for the same reasons as above.
The combination further discloses:
A non-transitory computer readable information recording medium storing the program (Leacock, P[0092]).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Leacock et al. (hereinafter Leacock) (US 20030200077 A1) in view of Sumida et al. (hereinafter Sumida) (JP-2013178633-A) (see attached translated copy for page numbers) and in further view of Zechner et al. (hereinafter Zechner) (US 20130158982 A1).
Regarding claim 2, the combination of Leacock and Sumida discloses the method according to claim 1.
The combination does not explicitly disclose:
wherein the text input step includes:
a step in which a speech is input into the computer; and
a step of analyzing the speech to obtain the text to be evaluated by the computer;
However, Zecher discloses:
wherein the text input step includes:
a step in which a speech is input into the computer (Zechner, P[0014]: "an audio recording 102, such as a recording of a test taker providing a non-scripted response in reply to a test prompt, is received and provided to an automatic speech recognizer 104.", Chen receives a spoken response/audio recording into a computer-implemented speech recognition system, thus, teaching inputting speech into the computer); and
a step of analyzing the speech to obtain the text to be evaluated by the computer (Zechner, P[0014]: "The automated speech recognizer 104 may take a variety of forms, such as a Hidden Markov Model that generates hypotheses of words recognized in the audio 102 and confidence scores associated with those hypotheses to generate a recognized speech transcript 106.", "The recognized speech transcript 106 is provided for feature computation 108 where one or more scoring features 110, such as content features, are extracted from the set of words 106 automatically recognized in the non-scripted speech sample audio 102. ", Zechner analyzes the received speech with an automatic speech recognizer to generate a recognized speech transcript, thus, obtaining textual content from the speech for subsequent evaluation).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Leacock in view of Sumida and in further view of Zechner. Doing so would have brought Zechner’s automatic speech-recognition technique (Zechner, Abstract, P[0014]) with Sumida’s predicate-phrase analysis including case elements and case particles (Sumida, Abstract) and with Leacock’s automated answer-evaluation system (Leacock, Abstract, P[0020]-P[0025]) because doing so would have predictably allowed spoken responses to be converted into text and evaluated using the same automated linguistic analysis and scoring process, thus, improving the system by enabling automated evaluation of spoken as well as typed responses.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHASHIDHAR S MANOHARAN whose telephone number is (571)272-6772. The examiner can normally be reached M-F 8:00-4:00.
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/SHASHIDHAR SHANKAR MANOHARAN/Examiner, Art Unit 2655
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655
