DETAILED ACTION
Introduction
This office action is in response to Applicant’s submission filed on July 26, 2024.
Claims 1-20 are pending in the application. As such, claims 1-20 have been examined.
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 .
Drawings
The drawings were received on July 26, 2024. These drawings have been accepted and considered by the Examiner.
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) is/are: a model that is configured to generate in claim 6 line 2.
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. Specifically, for purposes of examination, the examiner interprets this as a machine learning model that is configured to generate.
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.
Double Patenting
Claims 1-6 and 13-20 of this application are patentably indistinct from claims 1-12 and 21-22, respectively, of Application No. 18/764,616. Pursuant to 37 CFR 1.78(f), when two or more applications filed by the same applicant or assignee contain patentably indistinct claims, elimination of such claims from all but one application may be required in the absence of good and sufficient reason for their retention during pendency in more than one application. Applicant is required to either cancel the patentably indistinct claims from all but one application or maintain a clear line of demarcation between the applications. See MPEP § 822.
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-6 and 13-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-12 and 21-22 of copending Application No. 18/764,616 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because they claim the same inventive concept element by element (see following table).
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
The differences between the claims being compared are in bold.
Instant Application: 18/785,645
Reference Application: 18/764,616
1. A method comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining split scores comprising determining a split score for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the split scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
1. A method comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining classification scores comprising determining a classification score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the classification scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
2. The method of claim 1, wherein the sequence of text represents one or more legal documents.
2. The method of claim 1, wherein the sequence of text represents one or more legal documents.
3. The method of claim 1, wherein obtaining data representing a sequence of text comprises receiving the data from a user.
3. The method of claim 1, wherein obtaining data representing a sequence of text comprises receiving the data from a user.
4. The method of claim 1, further comprising providing the at least two segments to a user.
4. The method of claim 1, further comprising providing the at least two segments to a user.
5. The method of claim 1, further comprising: receiving a query from a user; identifying one or more relevant segments to the query from the at least two segments; and providing the one or more identified relevant segments to the user.
5. The method of claim 1, further comprising: receiving a query from a user; identifying one or more relevant segments from the at least two segments; and providing the one or more identified relevant segments to the user.
6. The method of claim 1, wherein dividing the text into a plurality of sentence fragments comprises providing the sequence of text as input to a model that is configured to generate a plurality of sentence fragments given an input sequence of text.
6. The method of claim 1, wherein dividing the text into a plurality of sentence fragments comprises providing the sequence of text as input to a model that is configured to generate a plurality of sentence fragments given an input sequence of text.
13. The method of claim 1, wherein determining a split score for each of a plurality of pairs of sentence fragments comprises using a language model to identify whether two sentence fragments are similar in the pair of sentence fragments.
7. The method of claim 1, wherein determining a classification score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments comprises: for each pair of sentence fragments, determining the classification score for the pair of sentence fragments by providing data representing the pair of sentence fragments to the machine learning model, wherein the machine learning model is configured to generate a classification score representing a likelihood that an input pair of sentence fragments are not similar.
14. The method of claim 1, wherein assigning one or more split positions based on the split scores comprises determining one or more split positions that each reflect a lowest similarity between two sentence fragments in a particular pair of sentence fragments among the plurality of pairs of sentence fragments.
8. The method of claim 1, wherein assigning one or more split positions based on the classification scores comprises determining one or more split positions that each reflect a highest likelihood that two sentence fragments in a particular pair of sentence fragments are not similar among the plurality of pairs of sentence fragments.
15. The method of claim 14, wherein the one or more split positions that each reflect a lowest similarity between two sentence fragments have a highest split score among the plurality of pairs of sentence fragments.
9. The method of claim 8, wherein the one or more split positions that each reflect a highest likelihood that two sentence fragments in a particular pair of sentence fragments are not similar have a highest classification score among the plurality of pairs of sentence fragments.
16. The method of claim 1, wherein assigning one or more split positions based on the split scores comprises assigning one or more split positions based on a current set of split scores at each of a plurality of iterations, and wherein the method comprises, at each iteration: determining that a termination condition has not been met; in response to determining that the termination condition has not been met, assigning a split position corresponding to an index for a pair of sentence fragments with a highest split score in the current set of split scores; modifying the current set of split scores by setting the highest split score to zero; identifying a first set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments preceding the split position; identifying a second set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments following the split position; for each set of the first set and second set: identifying a respective subset of sentence fragments in the set; modifying the current set of split scores by setting one or more of the split scores for the pairs of sentence fragments in the respective subset to zero; and updating the current set of split scores to the split scores for the sentence fragments of the set.
10. The method of claim 1, wherein assigning one or more split positions based on the classification scores comprises assigning one or more split positions based on a current set of classification scores at each of a plurality of iterations, and wherein the method comprises, at each iteration: determining that a termination condition has not been met; in response to determining that the termination condition has not been met, assigning a split position corresponding to an index for a pair of sentence fragments with a highest classification score in the current set of classification scores; modifying the current set of classification scores by setting the highest classification score to zero; identifying a first set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments preceding the split position; identifying a second set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments following the split position; for each set of the first set and second set: identifying a respective subset of sentence fragments in the set; modifying the current set of classification scores by setting one or more of the classification scores for the pairs of sentence fragments in the respective subset to zero; and updating the current set of classification scores to the classification scores for the sentence fragments of the set.
17. The method of claim 16, wherein the respective subset of sentence fragments comprises a cumulative number of tokens greater than or equal to a threshold number of tokens.
11. The method of claim 10, wherein the respective subset of sentence fragments comprises a cumulative number of tokens greater than or equal to a threshold number of tokens.
18. The method of claim 16, wherein the termination condition is defined by a condition where all of the split scores are zero.
12. The method of claim 10, wherein the termination condition is defined by a condition where all of the classification scores are zero.
19. A system comprising: one or more computers; and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining split scores comprising determining a split score for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the split scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
21. A system comprising: one or more computers; and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining classification scores comprising determining a classification score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the classification scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
20. One or more computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining split scores comprising determining a split score for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the split scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
22. One or more computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining classification scores comprising determining a classification score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the classification scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
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.
Claim 20 is 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 broadest reasonable interpretation of the claimed "computer-readable storage media”, consistent with a conclusion reached by one skilled in the art based on both the specification disclosure and the state-of-the-art, is that the full scope covers transitory "signal” embodiments. The state-of-the-art at the time the invention was made included signals, carrier waves and other wireless communication modalities (e.g., RF, infrared, etc.) as media on which executable code was recorded and from which computers acquired such code. Thus, the full scope of the claim covers "signals" and their equivalents, which are non-statutory per se. (In re Nuijten). The examiner suggests clarifying the claim to exclude such non-statutory signal embodiments, such as (but not limited to) by reciting a "non-transitory computer-readable storage media", or equivalent.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 19 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite:
A method comprising:
[claim 19 only] system comprising:
[claim 19 only] one or more computers; and
[claim 19 only] one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
[claim 20 only] one or more computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
obtaining data representing a sequence of text;
dividing the sequence of text into a plurality of sentence fragments;
determining split scores comprising determining a split score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments;
assigning one or more split positions based on the split scores; and
combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
The claim limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind. For example,
“obtaining data representing a sequence of text” in the context of this claim encompasses a person acquiring a text document,
“dividing the sequence of text into a plurality of sentence fragments” in the context of this claim encompasses a person manually dividing the text into segments on paper,
“determining split scores comprising determining a split score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments” in the context of this claim encompasses a person classifying the segments by pairs and writing down the scores,
“assigning one or more split positions based on the split scores” in the context of this claim encompasses a person determining where to indicate splits,
“combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments” in the context of this claim encompasses a person rewriting the entire document from the segments including split indications.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites these additional elements. These additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea.
one or more computers
one or more storage devices
one or more computer-readable storage media
a machine learning model.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea that do not provide an inventive concept. The claim is not patent eligible.
The dependent claims do not add limitations that would either integrate the recited abstract idea into a practical application or could help the Claim as a whole to amount to significantly more than the Abstract idea identified for the Independent Claim.
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein the sequence of text represents one or more legal documents.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein the sequence of text represents one or more legal documents” in the context of this claim encompasses a person ensuring the text to be examined is a legal document.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 3 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein obtaining data representing a sequence of text comprises receiving the data from a user.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein obtaining data representing a sequence of text comprises receiving the data from a user” in the context of this claim encompasses a person interacting with a user to obtain the text.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
further comprising providing the at least two segments to a user.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“further comprising providing the at least two segments to a user” in the context of this claim encompasses a person showing the segments to the user.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
further comprising:
receiving a query from a user;
identifying one or more relevant segments to the query from the at least two segments; and
providing the one or more identified relevant segments to the user.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“receiving a query from a user” in the context of this claim encompasses a person interacting with a user to obtain the text,
“identifying one or more relevant segments to the query from the at least two segments” in the context of this claim encompasses a person identifying key segments,
“providing the one or more identified relevant segments to the user” in the context of this claim encompasses a person showing the segments to the user.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein dividing the text into a plurality of sentence fragments comprises
providing the sequence of text as input to a model that is configured to generate a plurality of sentence fragments given an input sequence of text.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein dividing the text into a plurality of sentence fragments” in the context of this claim encompasses a person manually dividing the text into segments on paper,
“providing the sequence of text as input to a model that is configured to generate a plurality of sentence fragments given an input sequence of text” in the context of this claim encompasses a person obtaining the text from a user and feeding the text into a generic segmentation model.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites these additional elements. These additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea.
a model.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea that do not provide an inventive concept. The claim is not patent eligible.
7-12
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining a split score for each of a plurality of pairs of sentence fragments comprises:
generating a corresponding embedded sentence fragment for each of the plurality of sentence fragments;
for each pair of sentence fragments:
determining a first similarity score between two sentence fragments in the pair of sentence fragments;
determining one or more second similarity scores, wherein each second similarity score is determined between two sentence fragments in the plurality of sentence fragments; and
determining the split score for the pair of sentence fragments by combining the first similarity score and the one or more second similarity scores.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“determining a split score for each of a plurality of pairs of sentence fragments” in the context of this claim encompasses a person determining scores for where to indicate splits,
“generating a corresponding embedded sentence fragment for each of the plurality of sentence fragments” in the context of this claim encompasses a person creating embedding vectors for each fragment,
“determining a first similarity score between two sentence fragments in the pair of sentence fragments” in the context of this claim encompasses a person determining the cosine similarity between vectors,
“determining one or more second similarity scores, wherein each second similarity score is determined between two sentence fragments in the plurality of sentence fragments” in the context of this claim encompasses a person determining the cosine similarity between other vectors,
“determining the split score for the pair of sentence fragments by combining the first similarity score and the one or more second similarity scores” in the context of this claim encompasses a person combining scores.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining a first similarity score comprises
computing a similarity between the corresponding embedded sentence fragments for the two sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“determining a first similarity score” in the context of this claim encompasses a person determining a score for similarity,
“determining one or more split positions that each reflect a highest likelihood that two sentence fragments in a particular pair of sentence fragments are not similar among the plurality of pairs of sentence fragments” in the context of this claim encompasses a person determining where to indicate splits according to specific rules indicated.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining one or more second similarity scores comprises,
for each of the one or more second similarity scores:
computing a similarity between a first embedded sentence fragment and a second embedded sentence fragment,
wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments, and
wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“determining one or more second similarity scores” in the context of this claim encompasses a person determining a score for similarity,
“computing a similarity between a first embedded sentence fragment and a second embedded sentence fragment” in the context of this claim encompasses a person determining a cosine score for similarity between two vectors,
“wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments” in the context of this claim encompasses a person ensuring the first embedded sentence fragment is the first particular sentence fragment of the two sentence fragments,
“wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments” in the context of this claim encompasses a person ensuring the second embedded sentence fragment is the second particular sentence fragment of the two sentence fragments.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining a first similarity score comprises
providing the corresponding embedded sentence fragments for the two sentence fragments to a machine learning model that is configured to generate a similarity score between vectors.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein determining a first similarity score” in the context of this claim encompasses a person manually deciding similarity scores,
“providing the corresponding embedded sentence fragments for the two sentence fragments to a machine learning model that is configured to generate a similarity score between vectors” in the context of this claim encompasses a person obtaining the text from a user and feeding the text into a generic segmentation model.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites these additional elements. These additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea.
a machine learning model.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea that do not provide an inventive concept. The claim is not patent eligible.
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining one or more second similarity scores comprises,
for each of the one or more second similarity scores:
providing a first embedded sentence fragment and a second embedded sentence fragment to a machine learning model that is configured to generate a similarity score between vectors,
wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments, and
wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“determining one or more second similarity scores” in the context of this claim encompasses a person manually deciding similarity scores,
“providing a first embedded sentence fragment and a second embedded sentence fragment to a machine learning model that is configured to generate a similarity score between vectors” in the context of this claim encompasses a person obtaining the text from a user and feeding the text into a generic segmentation model,
“wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments” in the context of this claim encompasses a person ensuring the first embedded sentence fragment is the first particular sentence fragment of the two sentence fragments,
“wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments” in the context of this claim encompasses a person ensuring the second embedded sentence fragment is the second particular sentence fragment of the two sentence fragments.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites these additional elements. These additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea.
a machine learning model.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea that do not provide an inventive concept. The claim is not patent eligible.
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein combining the first similarity score and the one or more second similarity scores comprises
computing a weighted sum of the first similarity score and the one or more second similarity scores.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“combining the first similarity score and the one or more second similarity scores” in the context of this claim encompasses a person averaging two scores,
“computing a weighted sum of the first similarity score and the one or more second similarity scores” in the context of this claim encompasses a person averaging two weighted scores.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein determining a split score for each of a plurality of pairs of sentence fragments comprises
using a language model to identify whether two sentence fragments are similar in the pair of sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“determining a split score for each of a plurality of pairs of sentence fragments” in the context of this claim encompasses a person classifying the segments by pairs and writing down the scores,
“using a language model to identify whether two sentence fragments are similar in the pair of sentence fragments” in the context of this claim encompasses a person using a generic computer for classifying the segments by pairs and writing down the scores, and deciding how likely any two segments are similar.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites these additional elements. These additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea.
a language model.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are generic computer components and the hardware is generic computer components that are merely being used as a tool to perform the abstract idea that do not provide an inventive concept. The claim is not patent eligible.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein assigning one or more split positions based on the split scores comprises
determining one or more split positions that each reflect a lowest similarity between two sentence fragments in a particular pair of sentence fragments among the plurality of pairs of sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“assigning one or more split positions based on the split scores” in the context of this claim encompasses a person determining where to indicate splits,
“determining one or more split positions that each reflect a lowest similarity between two sentence fragments in a particular pair of sentence fragments among the plurality of pairs of sentence fragments” in the context of this claim encompasses a person determining where to indicate splits according to specific rules indicated.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein the one or more split positions that each reflect a lowest similarity between two sentence fragments have a highest split score among the plurality of pairs of sentence fragments.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein the one or more split positions that each reflect a lowest similarity between two sentence fragments have a highest split score among the plurality of pairs of sentence fragments” in the context of this claim encompasses a person ensuring the split positions are representative of the specific rules listed.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein assigning one or more split positions based on the split scores comprises
assigning one or more split positions based on a current set of split scores at each of a plurality of iterations, and wherein the method comprises, at each iteration:
determining that a termination condition has not been met;
in response to determining that the termination condition has not been met,
assigning a split position corresponding to an index for a pair of sentence fragments with a highest split score in the current set of split scores;
modifying the current set of split scores by setting the highest split score to zero;
identifying a first set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments preceding the split position;
identifying a second set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments following the split position;
for each set of the first set and second set:
identifying a respective subset of sentence fragments in the set;
modifying the current set of split scores by setting one or more of the split scores for the pairs of sentence fragments in the respective subset to zero; and
updating the current set of split scores to the split scores for the sentence fragments of the set.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“assigning one or more split positions based on the split scores” in the context of this claim encompasses a person deciding where to indicate split positions,
“assigning one or more split positions based on a current set of split scores at each of a plurality of iterations” in the context of this claim encompasses a person identifying split positions based on scores,
“determining that a termination condition has not been met” in the context of this claim encompasses a person identifying the absence of any indication to stop,
“assigning a split position corresponding to an index for a pair of sentence fragments with a highest split score in the current set of split scores” in the context of this claim encompasses a person identifying split positions based on highest scores,
“modifying the current set of split scores by setting the highest split score to zero” in the context of this claim encompasses a person resetting all the scores,
“identifying a first set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments preceding the split position” in the context of this claim encompasses a person identifying segments before split positions,
“identifying a second set of sentence fragments comprising one or more sentence fragments of the plurality of sentence fragments following the split position” in the context of this claim encompasses a person identifying segments after split positions,
“identifying a respective subset of sentence fragments in the set” in the context of this claim encompasses a person identifying a subset of segments,
“modifying the current set of split scores by setting one or more of the split scores for the pairs of sentence fragments in the respective subset to zero” in the context of this claim encompasses a person resetting some scores to zero,
“updating the current set of split scores to the split scores for the sentence fragments of the set” in the context of this claim encompasses a person determining all the scores again.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein the respective subset of sentence fragments comprises a cumulative number of tokens greater than or equal to a threshold number of tokens.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein the respective subset of sentence fragments comprises a cumulative number of tokens greater than or equal to a threshold number of tokens” in the context of this claim encompasses a person ensuring at least a threshold of tokens exist.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
Claim 18 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
wherein the termination condition is defined by a condition where all of the split scores are zero.
The additional limitations of the claim do not preclude the method from practically being performed in the mind. For example,
“wherein the termination condition is defined by a condition where all of the split scores are zero” in the context of this claim encompasses a person knowing to stop when all scores are zero.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements.
Accordingly, these no additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the no additional elements do not provide an inventive concept. The claim is not patent eligible.
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.
Claims 1, 3-4, 6, 13-15 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US Patent No. 11210470 B2), hereinafter Kim, in view of Sridhar et al. (US Patent Pub. No. 20090067719 A1), hereinafter Sridhar.
Regarding claims 1, 19 and 20, Kim teaches a method, a system, and one or more [non-transitory] computer-readable storage media (Kim in [col 1 ln 58-67] teaches a method of text segmentation)
[claim 19 only] one or more computers (Kim in [col 22 ln 34-50] teaches using a computer);
and
[claim 19 only] one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations (Kim in [col 22 ln 34-50] teaches using a computer which has memory and executes instructions to perform operations)
[claim 20 only] one or more computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations (Kim in [col 22 ln 34-50] teaches using a computer which has memory and executes instructions to perform operations)
comprising:
obtaining data representing a sequence of text (Kim in [col 9 ln 28-41] teaches receiving text to process for segmentation);
dividing the sequence of text into a plurality of sentence fragments (Kim in [col 3 ln 40-60] teaches accurately identifying segmentation points in the text);
determining split scores (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations)
comprising
determining a split score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 3 ln 40-60] teaches using a neural network system specifically trained for identifying segmentation points in a text);
assigning one or more split positions based on the split scores (Kim in [col 3 ln 40-60] teaches accurately identifying segmentation points in the text, for instance, high similarity can be indicative that there is not a segmentation point whereas low similarity can be indicative that there should be a segmentation point);
and
with a boundary of at least one of the at least two segments being identified by one of the one or more split positions (Kim in [col 8 ln 12-24] teaches a user device can be utilized for displaying the subparts of the text after identifying segmentation points (e.g., using joint labeled decision points)).
Kim teaches the boundary of at least one of the at least two segments being identified by one of the one or more split positions.
Kim does not teach, however Sridhar teaches
combining the plurality of sentence fragments back into at least two segments, [with a boundary of at least one of the at least two segments being identified by one of the one or more split positions], and wherein each segment comprises one or more sentence fragments (Sridhar in [0049] teaches performing textual segmentation followed by segment merging).
Sridhar is considered to be analogous to the claimed invention because it is in the same field of segmentation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim further in view of Sridhar to allow for performing textual segmentation followed by segment merging. Motivation to do so would allow for a system for addressing existing issues in order to achieve more effective text segmentation (Sridhar [0016]).
Regarding claim 3, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
wherein obtaining data representing a sequence of text comprises receiving the data from a user (Kim in [col 6 ln 65 – col 7 ln 16] teaches based on the input text, (e.g., provided via a user device or server), text segmentation can be performed to determine subparts of the text).
Regarding claim 4, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
further comprising providing the at least two segments to a user (Kim in [col 8 ln 12-24] teaches a user device can be utilized for displaying the subparts of the text after identifying segmentation points (e.g., using joint labeled decision points)).
Regarding claim 6, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
wherein dividing the text into a plurality of sentence fragments comprises
providing the sequence of text as input to a model that is configured to generate a plurality of sentence fragments given an input sequence of text (Kim in [col 4 ln 7-25] teaches to perform text segmentation, data can be input into a text segmentation neural network system).
Regarding claim 13, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
wherein determining a split score for each of a plurality of pairs of sentence fragments comprises
using a language model to identify whether two sentence fragments are similar in the pair of sentence fragments (Kim in [col 4 ln 7-25] teaches to perform text segmentation, data can be input into a text segmentation neural network system, and in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations).
Regarding claim 14, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
wherein assigning one or more split positions based on the split scores comprises
determining one or more split positions that each reflect a lowest similarity between two sentence fragments in a particular pair of sentence fragments among the plurality of pairs of sentence fragments (Kim in [col 3 ln 40-60] teaches accurately identifying segmentation points in the text, for instance, high similarity can be indicative that there is not a segmentation point whereas low similarity can be indicative that there should be a segmentation point).
Regarding claim 15, Kim, as modified above, teaches the method of claim 8.
Kim further teaches
wherein the one or more split positions that each reflect a lowest similarity between two sentence fragments have a highest split score among the plurality of pairs of sentence fragments (Kim in [col 3 ln 40-60] teaches accurately identifying segmentation points in the text, for instance, high similarity can be indicative that there is not a segmentation point whereas low similarity can be indicative that there should be a segmentation point).
Claims 2 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Kim, in view of Sridhar, in view of Padmashali et al. (US Patent Pub. No. 20250148020 A1), hereinafter Padmashali.
Regarding claim 2, Kim, as modified above, teaches the method of claim 1.
Kim, as modified above, does not teach, however Padmashali teaches
wherein the sequence of text represents one or more legal documents (Padmashali in [0039] teaches analyzing the text of legal documents).
Padmashali is considered to be analogous to the claimed invention because it is in the same field of segmentation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim, as modified above, further in view of Padmashali to allow for analyzing the text of legal documents. Motivation to do so would allow for summarization, analysis, and other techniques to be applied at the segment level in parallel across the input document, rather than having to process the entire document holistically in one pass (Padmashali [0053]).
Regarding claim 5, Kim, as modified above, teaches the method of claim 1.
Kim, as modified above, does not teach, however Padmashali teaches
further comprising:
receiving a query from a user (Padmashali in [0439] teaches receiving a search query and returning a portion of the output responsive to the search query);
identifying one or more relevant segments from the at least two segments (Padmashali in [0439] teaches receiving a search query and returning a portion of the output responsive to the search query);
and
providing the one or more identified relevant segments to the user (Padmashali in [0439] teaches receiving a search query and returning a portion of the output responsive to the search query).
Padmashali is considered to be analogous to the claimed invention because it is in the same field of segmentation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim, as modified above, further in view of Padmashali to allow for receiving a search query and returning a portion of the output responsive to the search query. Motivation to do so would allow for summarization, analysis, and other techniques to be applied at the segment level in parallel across the input document, rather than having to process the entire document holistically in one pass (Padmashali [0053]).
Claims 7-12 are rejected under 35 U.S.C. 103 as being unpatentable over Kim, in view of Sridhar, in view of Leydon et al. (US Patent Pub. No. 20160004413 A1), hereinafter Leydon.
Regarding claim 7, Kim, as modified above, teaches the method of claim 1.
Kim further teaches
wherein determining a split score for each of a plurality of pairs of sentence fragments comprises:
generating a corresponding embedded sentence fragment for each of the plurality of sentence fragments (Kim in [col 16 ln 60-67] teaches using embedding vectors for the sentence words);
for each pair of sentence fragments:
determining a first similarity score between two sentence fragments in the pair of sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations);
determining one or more second similarity scores, wherein each second similarity score is determined between two sentence fragments in the plurality of sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations [this can be repeated to obtain the additional similarity scores]).
Kim, as modified above, teaches determining the split score for the pair of sentence fragments.
Kim, as modified above, does not teach, however Leydon teaches
[determining the split score for the pair of sentence fragments by] combining the first similarity score and the one or more second similarity scores (Leydon in [0134] teaches combining similarity scores).
Leydon is considered to be analogous to the claimed invention because it is in the same field of combining scores. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim, as modified above, further in view of Leydon to allow for combining similarity scores. Motivation to do so would allow for more than one characteristic of a text segment or message to be considered when computing the score, and also allow some characteristics (e.g., sentiment) to be weighted more heavily than other characteristics (e.g., text similarity) when computing a score (Leydon [00134]).
Regarding claim 8, Kim, as modified above, teaches the method of claim 7.
Kim further teaches
wherein determining a first similarity score comprises computing a similarity between the corresponding embedded sentence fragments for the two sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 16 ln 60-67] teaches using embedding vectors for the sentence words).
Regarding claim 9, Kim, as modified above, teaches the method of claim 7.
Kim further teaches
wherein determining one or more second similarity scores comprises,
for each of the one or more second similarity scores:
computing a similarity between a first embedded sentence fragment and a second embedded sentence fragment (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 16 ln 60-67] teaches using embedding vectors for the sentence words),
wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 16 ln 60-67] teaches using embedding vectors for the sentence words),
and
wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 16 ln 60-67] teaches using embedding vectors for the sentence words).
Regarding claim 10, Kim, as modified above, teaches the method of claim 7.
Kim further teaches
wherein determining a first similarity score comprises
providing the corresponding embedded sentence fragments for the two sentence fragments to a machine learning model that is configured to generate a similarity score between vectors (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 3 ln 40-60] teaches using a neural network system specifically trained for identifying segmentation points in a text).
Regarding claim 11, Kim, as modified above, teaches the method of claim 7.
Kim further teaches
wherein determining one or more second similarity scores comprises,
for each of the one or more second similarity scores:
providing a first embedded sentence fragment and a second embedded sentence fragment to a machine learning model that is configured to generate a similarity score between vectors (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 3 ln 40-60] teaches using a neural network system specifically trained for identifying segmentation points in a text),
wherein the first embedded sentence fragment comprises the corresponding embedded sentence fragment for a first particular sentence fragment of the two sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 3 ln 40-60] teaches using a neural network system specifically trained for identifying segmentation points in a text),
and
wherein the second embedded sentence fragment comprises the corresponding embedded sentence fragment for a second particular sentence fragment of the plurality of sentence fragments (Kim in [col 12 ln 22-42] teaches similarity information can be based on a comparison between combinations of the context vectors and the target vectors to determine differences (e.g., comparing each combination of the context vectors and the target vectors), and differences (and similarities) between the context vectors and the target vectors can be indicated using similarity scores determined using distributed representations, and in [col 3 ln 40-60] teaches using a neural network system specifically trained for identifying segmentation points in a text).
Regarding claim 12, Kim, as modified above, teaches the method of claim 7.
Kim, as modified above, teaches combining the first similarity score and the one or more second similarity scores.
Kim, as modified above, does not teach, however Leydon teaches
[wherein combining the first similarity score and the one or more second similarity scores comprises]
computing a weighted sum of the first similarity score and the one or more second similarity scores (Leydon in [0134] teaches combining similarity scores using a weighted sum).
Leydon is considered to be analogous to the claimed invention because it is in the same field of combining scores. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim, as modified above, further in view of Leydon to allow for combining similarity scores using a weighted sum. Motivation to do so would allow for more than one characteristic of a text segment or message to be considered when computing the score, and also allow some characteristics (e.g., sentiment) to be weighted more heavily than other characteristics (e.g., text similarity) when computing a score (Leydon [00134]).
Allowable Subject Matter
Claims 16-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and upon overcoming the 101 rejection and NSDP rejection.
Claim 16 would be allowable because the prior art, either alone or in reasonable combination, does not teach the combination of claim elements as recited in the claims.
Claims 17-18 depend from claim 16 either directly or indirectly, and therefore, by virtue of this dependency, would also be allowable.
Conclusion
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PAUL MUELLER
Examiner
Art Unit 2657
/PAUL J. MUELLER/Examiner, Art Unit 2657
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