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 .
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required: The Specification does not appear to disclose a “user base”, wherein a comprehensive list of word families applicable across a user base, or applicable to a diverse user base, is generated (claims 8 and 20) (see Specification, [0014], “The system starts by obtaining a comprehensive list of word families and identifying those that are already familiar to the user.”).
Claim Objections
Claims 1, 3-4, 9, 15, and 17-20 are objected to because of the following informalities:
“the backlog item’s target familiarity level” recited in claim 1, ln. 16 should likely read “[[the]]a backlog item’s target familiarity level”;
“the user interface” recited in claim 3, ln. 2 should likely read “[[the]]a user interface”;
“user reading backlog” recited in claim 4, ln. 5 should likely read “user’s reading backlog”;
“allows the user to modify their reading backlog” recited in claim 9, ln. 1 should likely read “allows the user to modify a reading backlog”;
“the one or more processors” recited in claim 15, ln. 1, claim 17, ln. 1, and claim 19, ln. 1 should likely read “the at least one processor[[s]” for consistency purposes;
“examples” recited in claim 18, ln. 1 & 2 should likely read “usage examples” for consistency purposes and to avoid claim ambiguity;
“the user” recited in claim 20, ln. 11 should likely read “[[the]]a user”; and
“each word family” recited in claim 20, ln. 16 should likely read “each unfamiliar word family” to avoid claim ambiguity.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1, ln. 11 recites in part “obtain usage frequences of the word families”. It is indefinite as to whether “the word families” is intended to refer to the plurality of word families (claim 1, ln. 7), the plurality of word families familiar to the user (claim 1, ln. 8), both, or neither.
Claim 1, ln. 13 recites in part “the familiar running words”. There is insufficient antecedent basis for this limitation in the claim.
Claim 1, ln. 17 recites in part “the indicated word families”. There is insufficient antecedent basis for this limitation in the claim (see claim 1, ln. 14-16, “indicate a normalized to a predefined amount of text content number of text ranked word families” (emphasis added)).
Claim 2 recites “The system of claim 1, wherein the indicated number of top ranked word families to be learned to reach a backlog item’s target familiarity level is not normalized to a predefined amount of text content.” It is indefinite as to how the indicated number of top ranked words families to be learned to reach a backlog item’s target familiarity level is not normalized to a predefined amount of text content, as recited in claim 2, wherein claim 1, from which claim 2 depends, recites wherein the indicated number of top ranked word families to be learned to reach the backlog item’s target familiarity level is normalized to a predefined amount of text content.
Claim 5 recites in part “wherein the displayed word families of the selected backlog item can be ordered based at least partly on the usage frequencies of the word families in the selected item and if any, in at least one of the other items in the backlog”. It is indefinite what “and if any, in at least one of the other items in the backlog” is intended to mean. It is noted that claim 4, upon which claim 5 depends, previously recites wherein the plurality of unfamiliar word families displayed include those word families used in the selected backlog item as well as in at least one item of the user reading backlog. Accordingly, the displayed word families are used in the selected item and in at least one of the other items in the backlog.
A suggested amendment is as follows: “wherein the displayed word families of the selected backlog item can be ordered based at least partly on the usage frequencies of the word families in the selected item and
Claim 6 recites in part “the given item”. There is insufficient antecedent basis for this limitation in the claim.
A suggested amendment is as follows: “the backlog item”.
Claim 8 recites in part “generate a comprehensive list of word families applicable across a user base”. It is indefinite as to what it means for the comprehensive list to be “applicable across a user base”, and the Specification does not offer further guidance.
Claim 8 further recites in part “maintain a personalized inventory of word families for a user, identifying those which are familiar”. It is indefinite as to whether familiar word families are identified within the personalized inventory of word families, or rather, the personalized inventory of word families as a whole identifies the word families which are familiar for a user.
Claim 10 recites in part “assuming the user assimilates all recommended word families from prior backlog entries incrementally”. It is indefinite as to whether “all recommended word families from prior backlog entries” is intended to refer to “the requisite word families to learn for achieving a target familiarity level for each item”, or rather, something else.
Claim 11 is rejected by virtue of its dependency on claim 10.
Claim 14 recites in part “The system of claim 12, wherein the metric can be normalized on any number of pages, number of running words or other derived characteristics”. However, claim 12, upon which claim 14 depends, recites wherein the normalization is done to a size of the book. Accordingly, it is indefinite as to how the normalization can be to the size of the book, while also being on any number of pages, number of running words, or other derived characteristics, as recited in claim 14.
Dependent claims 2-7 and 9-19 are rejected by virtue of their dependencies on claims 1 and 8, respectively.
Claim 20 recites in part “generating a comprehensive list of word families applicable to a diverse user base”. First, it is indefinite as to what it means for the comprehensive list to be “applicable to a diverse user base”, and the Specification does not offer further guidance. Second, the term “diverse” is a relative term which renders the claim indefinite. The term “diverse” is not defined by the claim, the Specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 3 and 7 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 3 recites the claim language previously recited in claim 1 (ln. 14-18), from which claim 3 depends.
Claim 7 recites the claim language previously recited in claim 1 (ln. 9-10), from which claim 7 depends.
Applicant may cancel the claims, amend the claims to place the claims in proper dependent form, rewrite the claims in independent form, or present a sufficient showing that the dependent claims comply with the statutory requirements.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea(s) without significantly more.
Regarding claim 1, analyzed as representative claim:
[Step 1] Claim 1 recites in part “A system”, which falls within the “machine” statutory category of invention.
[Step 2A – Prong 1] The claim recites a series of steps which can be practically performed by one or more humans through mental process (i.e., observation, evaluation, judgment, and/or opinion) (see MPEP 2106.04(a)(2)(III)) and/or certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people – including social activities, teaching, and following rules or instructions) (see MPEP 2106.04(a)(2)(II)).
Claim 1 recites: A system for recommending reading materials and a user’s vocabulary growth trajectory based on a vocabulary of the user, the system comprising:
a computing device, one or more processors, and a memory, wherein the memory is coupled to the one or more processors to store instructions executable by the one or more processors, wherein the one or more processors are configured to:
obtain a plurality of word families (insignificant extra-solution activity (i.e., data gathering));
obtain a plurality of word families familiar to the user (insignificant extra-solution activity (i.e., data gathering));
facilitate the user to add and remove items referring text-containing documents to the user’s ordered reading backlog (mental process: evaluation; human activity: managing personal behavior (i.e., following instructions); and/or insignificant extra-solution activity (i.e., data gathering/data transmission));
obtain usage frequencies of the word families in the documents referred in the reading backlog (mental process: observation/evaluation; and/or insignificant extra-solution activity (i.e., data gathering)); and
facilitate the user to set target shares of the familiar running words in the items of the reading backlog, and, for the items of the reading backlog, indicate a normalized to a predefined amount of text content number of top ranked word families to be learned to reach the backlog item’s target familiarity level, assuming the user has already learned the indicated word families from preceding items in the backlog, wherein the word families are ranked based at least partly on the usage frequencies of the word families in the given item and if any, in at least one of the other items in the backlog (mental process: evaluation; human activity: managing personal behavior (i.e., following instructions); and/or insignificant extra-solution activity (i.e., data gathering/data transmission)).
The limitations, under their broadest reasonable interpretation, encompass mental processes and/or certain methods of organizing human activity, but for the recitation of generic computer components, as indicated above. That is, a user (e.g., student) can mentally, or be instructed by a human (e.g., teacher), to select books desired to be read and set target shares of the familiar running words in the selected books, wherein a human (e.g., the teacher) may mentally calculate a number, normalized to a predefined amount of text content, of mentally determined top ranked word families for the user to learn to reach a target familiarity level of a book. Thus, the claim recites abstract idea(s).
[Step 2A – Prong 2] The claim fails to recite additional limitations to integrate the abstract idea(s) into a practical application. The computing device, one or more processors, and memory, configured to perform the limitations discussed above, are recited at a high level of generality such that they do not amount to a particular machine or technical improvement thereof, nor do they represent an improvement in other technology. Rather, the generic manner in which the additional elements are claimed amount to no more than instructions to apply the abstract idea(s) using a generic computer, and/or to implement the abstract idea(s) in a computer environment (see MPEP 2106.05(f) & (h)).
Moreover, the additional limitations of “obtaining” a plurality of word families and a plurality of word families familiar to a user are directed to the insignificant extra-solution activity of data gathering, which do not integrate the abstract idea(s) into a practical application (see MPEP 2106.05(g)). Additionally, and/or alternatively, the limitations of facilitating the user to add and remove items referring text-containing documents to the user’s ordered reading backlog, obtaining usage frequencies of the word families in the documents referred in the reading backlog, and facilitating the user to set target shares of the familiar running words in the items of the reading backlog are directed to insignificant extra-solution activity (data gathering and data transmission), which similarly also do not integrate the abstract idea(s) into a practical application.
There is no indication that the combination of elements improves the functioning of a computer or other technology (see MPEP 2106.05(a)), recites a “particular machine” to apply or use the abstract idea(s) (see MPEP 2106.05(b)), recites a particular transformation of an article to a different thing or state (see MPEP 2106.05(c)), or recites any other meaningful limitation (see MPEP 2106.05(e)).
Accordingly, the claim is directed to the abstract idea(s).
[Step 2B] As discussed above with respect to integration of the abstract idea(s) into a practical application, the claim does not further include additional elements that are sufficient to amount to significantly more than the judicial exception. Rather, the additional limitations amount to mere instructions to apply the abstract idea(s) using a generic computer and/or to implement the abstract idea(s) in a computer environment, and insignificant extra-solution activity. The Specification further demonstrates that the recited computer components are recited for their well-understood, routine, and conventional functionality, wherein the Specification refers to the elements in a manner that indicates that they are sufficiently well-known that the Specification does not need to describe the particulars of such additional elements to satisfy enablement (see Specification, Fig. 1; [0031], “Examples of the user computing device 104 may include a smartphone, a tablet computer, a laptop, or any other portable communication device.”; [0040], “The processor 108 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions.”; [0041], “The memory 110 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read-only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. The memory 110 may include various modules. The memory 110 includes routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types.”). Thus, claim 1 is not patent eligible.
Claims 2-7 are dependent from claim 1 and therefore recite the same abstract idea(s) noted above. While dependent claims 2-7 may have a narrower scope than the independent claim, the claims fail to recite additional limitations that would integrate the abstract idea(s) into a practical application or provide significantly more. Therefore, claims 2-7 are also not patent eligible.
Regarding claim 8, analyzing as representative claim:
[Step 1] Claim 8 recites in part “A vocabulary-based reading material recommendation system”, which falls within the “machine” statutory category of invention.
[Step 2A – Prong 1] The claim recites a series of steps which can be practically performed by one or more humans through mental process (i.e., observation, evaluation, judgment, and/or opinion) (see MPEP 2106.04(a)(2)(III)) and/or certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people – including social activities, teaching, and following rules or instructions) (see MPEP 2106.04(a)(2)(II)).
Claim 8 recites: A vocabulary-based reading material recommendation system, comprising:
a computing device that includes at least one processor and a memory, wherein the memory is configured to store instructions that, when executed by the at least one processor, enable the system to:
generate a comprehensive list of word families applicable across a user base (mental process: observation/evaluation);
maintain a personalized inventory of word families for a user, identifying those which are familiar (mental process: observation/evaluation; and/or insignificant extra-solution activity (i.e., data gathering/data storage));
provide a user interface allowing users to peruse an assortment of reading materials, including both individual books and collections thereof, which are contributed by the users themselves or by system administrators, and for each material, display: the percentage of text composed of word families already known to the user, and the count of additional word families that the user would need to learn to achieve predetermined levels of familiarity with the material (mental process: observation/evaluation; and/or insignificant extra-solution activity (i.e., data display/data transmission));
upon selection of a specific reading material by the user, present a detailed enumeration of unfamiliar word families within that material, alongside the frequency of each such family’s appearance therein (insignificant extra-solution activity (i.e., data display/data transmission));
facilitate user selection of word families from this presentation for targeted learning (mental process: evaluation; human activity: managing personal behavior (i.e., following instructions)); and
update the display to reflect a new aggregate familiarity score, incorporating both pre-existing knowledge and the newly acquired vocabulary, thus providing a real-time measure of the user’s evolving comprehension capacity relative to the selected material (mental process: evaluation/judgment; and/or insignificant extra-solution activity (i.e., data transmission/data display)).
The limitations, under their broadest reasonable interpretation, encompass mental processes and/or certain methods of organizing human activity, but for the recitation of generic computer components, as indicated above. That is, a user can mentally generate a list of word families and identify those which are familiar, mentally (e.g., via visual observation) peruse an assortment of reading materials and select a specific reading material, and mentally, or be instructed by a human (e.g., teacher), to select word families for targeted learning (e.g., previously gathered unfamiliar word families within a selected reading material). Further, a human (e.g., a teacher) could mentally determine a new aggregate familiarity score based on an evaluation of a user (e.g., student). Thus, the claim recites abstract idea(s).
[Step 2A – Prong 2] The claim fails to recite additional limitations to integrate the abstract idea(s) into a practical application. The computing device, at least one processor, memory, and user interface, configured to perform the limitations discussed above, are recited at a high level of generality such that they do not amount to a particular machine or technical improvement thereof, nor do they represent an improvement in other technology. Rather, the generic manner in which the additional elements are claimed amount to no more than instructions to apply the abstract idea(s) using a generic computer, and/or to implement the abstract idea(s) in a computer environment (see MPEP 2106.05(f) & (h)).
Moreover, the additional limitations of “maintain a personalized inventory of word families for a user”, “display: the percentage of text composed of word families already known to the user, and the count of additional word families that the user would need to learn to achieve predetermined levels of familiarity with the material”, “present a detailed enumeration of unfamiliar word families within that material, alongside the frequency of each such family’s appearance therein”, and “update the display to reflect a new aggregate familiarity score, incorporating both pre-existing knowledge and the newly acquired vocabulary, thus providing a real-time measure of the user’s evolving comprehension capacity relative to the selected material” are directed to the insignificant extra-solution activities of (data gathering, storage, display, and/or transmission), which do not integrate the abstract idea(s) into a practical application (see MPEP 2106.05(g)). Particularly, the displaying of data (i.e., percentage of text composed of word families already known to a user, count of additional word families the user would need to learn to achieve predetermined levels of familiarity with a material, enumeration of unfamiliar word families and their frequency within a selected material, and updated familiarity scores) does not amount to a technical improvement, but rather, recites the displaying/presentation of data that is previously gathered and/or could be mentally determined by a user.
There is no indication that the combination of elements improves the functioning of a computer or other technology (see MPEP 2106.05(a)), recites a “particular machine” to apply or use the abstract idea(s) (see MPEP 2106.05(b)), recites a particular transformation of an article to a different thing or state (see MPEP 2106.05(c)), or recites any other meaningful limitation (see MPEP 2106.05(e)).
Accordingly, the claim is directed to the abstract idea(s).
[Step 2B] As discussed above with respect to integration of the abstract idea(s) into a practical application, the claim does not further include additional elements that are sufficient to amount to significantly more than the judicial exception. Rather, the additional limitations amount to mere instructions to apply the abstract idea(s) using a generic computer and/or to implement the abstract idea(s) in a computer environment, and insignificant extra-solution activity. The Specification further demonstrates that the recited computer components are recited for their well-understood, routine, and conventional functionality, wherein the Specification refers to the elements in a manner that indicates that they are sufficiently well-known that the Specification does not need to describe the particulars of such additional elements to satisfy enablement (see Specification, Fig. 1; [0031], “Examples of the user computing device 104 may include a smartphone, a tablet computer, a laptop, or any other portable communication device.”; [0040], “The processor 108 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions.”; [0041], “The memory 110 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read-only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. The memory 110 may include various modules. The memory 110 includes routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types.”; [0043], “The processor 108 may be further configured to facilitate the user to navigate through a user interface of the computing device 104 over the plurality of books and book collections indicating for the books and collections, a current share of familiar running words, and the number of word families to be learned to reach various familiarity levels, assuming the user has already learned the indicated word families from preceding items in the backlog. […] The processor 108 may be further configured to display through a user interface of the computing device 104 a plurality of unfamiliar word families in a selected book or a book collection with the number of times those word families are used in this book or book collection.”). Thus, claim 8 is not patent eligible.
Independent claim 20 is a method of claim 8 and is thereby rejected for similar reasoning.
Claims 9-19 are dependent from claim 8 and therefore recite the same abstract idea(s) noted above. While dependent claims 9-19 may have a narrower scope than the independent claim, the claims fail to recite additional limitations that would integrate the abstract idea(s) into a practical application or provide significantly more. Therefore, claims 9-19 are also not patent eligible.
Acknowledgments
No prior art is provided for claims 1-20. The combination of all the elements of the independent claims do not appear in a single reference of prior art. Additionally, based on the art of record, it does not appear that it would have been obvious to a person of ordinary skill in the art at the time the application was filed to combine various pieces of the cited prior art to obtain each and every limitation as currently required by the independent claims. The closest prior art, U.S. Pub. 2016/0155349 A1 (“Jian”), directed to a vocabulary learning system and method, teaches receiving a user level and selecting a stored vocabulary set of a plurality of vocabulary sets with different levels as the user vocabulary set, wherein extracted words from an electronic document are compared with the user vocabulary set to extract new words in the electronic document and provide said new words to the user for learning. However, Jian fails to disclose, teach, or suggest each and every limitation of the independent claims (e.g., at least adding and removing items to a user’s reading backlog, obtaining usage frequencies of word families in documents/reading material, ranking word families, and determining familiarity scores of a user). Additional, relevant art fails to cure all of the above-mentioned deficiencies of Jian (see, e.g., U.S. 3,680,229 A, teaching matching a student’s reading level to a particular book readability using assigned symbols such that the student can select, read, and fully comprehend books to match their current reading and comprehension abilities; U.S. Pub. 2022/0179917 A1, teaching displaying a potential unknown word list to the user, selecting an unknown word from the list, and generating additional information associated with the selected word; U.S. Pub. 2022/0165178 A1, teaching scanning a page of an e-book a user is currently on for potential words the user might need additional help with based on the user’s reading capability level as stored in a user profile, and providing context meanings of predicted unknown words; U.S. Pub. 2018/0025657 A1, teaching selecting a word to be learned and determining, once the selected word has been learned, to move to a new word; U.S. Pub. 2012/0185239 A1, wherein textual data is extracted from a communication and compared to a reading material (e.g., dictionary) to identify new words, wherein word usage frequency, recency, or likelihood of use is generated for the identified words; and U.S. Pub. 2011/0076654 A1, teaching recommending a book to a user based on an evaluation of the user’s readability (e.g., using metrics such as the user’s phonemic awareness, vocabular, reading comprehension, and reading level)).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALYSSA N BRANDLEY whose telephone number is (571)272-4280. The examiner can normally be reached M-F: 8:30am-5:00pm.
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/ALYSSA N BRANDLEY/Examiner, Art Unit 3715