DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This Office action is in response to Applicant's amendment filed on 2/13/2026.
Claim 1, 3-6, 12-13, 26 and 28-33 are pending. Claim 1 and 26 are amended. Claim 1, 3-6, 12-13, 26 and 28-33 are rejected.
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 1-13, 15 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is directed to statutory category process. The claim recites “determining and pushing articles based on the vocabulary level of the child; testing the vocabulary level of the child accordingly to obtain the characters that the child knows to form a character set to be taken as the vocabulary level of the child based on the order of the characters in the set of high-frequency characters; updating the order of the characters in the set of high-frequency characters according to the child's actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high- frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child; wherein the method further comprises: checking the vocabulary level of the child in the process of article reading; updating and pushing new articles based on one or more check results of the vocabulary level of the child; wherein checking the vocabulary level of the child in the process of article reading comprises: counting the number of characters not recognized by and clicked by the child in the process of reading; updating the vocabulary level of the child based on characters clicked by the child in the articles; mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading; and updating the vocabulary level of the child based on the one or more check results of the child; marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading; and verifying checked characters after checking the vocabulary level of the child in the process of article reading,
wherein the checked characters refer to the characters clicked by the child in the process of article reading; and mixing the checked characters with interfering characters, determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit”. The processes of determining article based on child vocabulary level, testing vocabulary level with high frequency words, updating word/character order, checking vocabulary level by counting unrecognized words, updating vocabulary level based on child’s provided indication of the words, guiding the child to vocabulary level check, updating the vocabulary level based on check results, mixing checked words with interfering words, determining vocabulary level based on the result of the checked words, extracting characters/words to be reviewed and mixing those words with interfering words and using rule of Ebbinghaus forgetting curve involve observation, judgement and evaluation. Accordingly, the claims recite a mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements –“obtaining vocabulary level of the child”; wherein obtaining the vocabulary level of the child comprises: obtaining a set of high-frequency characters that fits the vocabulary level of the child”; and further “wherein before obtaining the vocabulary level of the child, the method further comprises: obtaining age of the child; saving the adjusted set of high-frequency characters by classifying the age of the child as a label; and obtaining the adjusted set of high-frequency characters based on age of subsequent child”. Above mentioned steps of receiving user specific information recites insignificant extra-solution activity of mere data gathering is “obtaining information” as identified in MPEP 2106.05 (g). The claim also recites additional limitations – “guiding the child to find the checked characters by voice”- above additional element recites insignificant extra-solution activity of presenting data. Viewing the additional limitations together and the claim individually as a whole, nothing provides integration into a practical application. Therefore, claim 1 directed to an abstract idea.
At step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering and outputting data such are also well-understood, routine, and conventional(OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claims individually as a whole does not change this conclusion and the claim is ineligible. Therefore, claim 1 is directed to an abstract idea.
Claim 26 differs from claim 1 in that the steps of the claimed method are implemented by instructions when executed by one or more processors. The invention of claim 26 is a system including one or more processors and a memory storing the instructions to perform recited steps. For reasons discussed above, the claimed steps are directed to mental steps. Use of a processor to execute instructions stored in memory constitutes use of a generic computer as a tool and does not constitute an application of significantly more than the abstract idea, see MPEP 2106.05 (f). Therefore, claim 26 is not patent eligible.
Dependent claim 3, 4 and 5 are directed to the same abstract idea as the independent claim from which they depend and further recite additional elements “….classifying the age of the child as a label”, “determining articles comprises: comparing and counting the characters in articles to be selected to get a recognition rate of all articles to be selected based on the vocabulary level of the child; and determining articles to be pushed to the child based on the recognition rate of articles to be selected”, “deduplicating the same character refers to a deduplication of a character that appears repeatedly in an article; and counting a same character with different pronunciations in an article based on the pronunciation” and “after determining articles to be pushed to the child based on the recognition rate of articles to be selected the method further comprises: updating the articles to be selected based on the number of characters that the child does not recognize in the articles, thus controlling the number of characters that the child does not recognize in the recommended articles”. The process of classifying child age as label, determining articles by comparing and counting words in articles to be selected, determining articles to pushed by rate of recognition, deduplicating and counting same word with different pronunciation and updating the articles based on number of unrecognized words involve observation, judgement and evaluation and can practically be performed in human mind. Accordingly, recited limitations fall into abstract idea groupings of mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “obtaining age of the child before obtaining the vocabulary level of the child; saving the adjusted set of high-frequency characters by ……….; and obtaining the adjusted set of high-frequency characters based on age of subsequent child” recite insignificant extra-solution activity of data gathering, mere data gathering as “obtaining information” as identified in MPEP 2106.05 (g). Viewing the additional limitations together and the respective claims as a whole, nothing provides integration into a practical application. Therefore, claim 3, 4 and 5 are directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements of mere data gathering, is well-understood, routine or conventional activities (This step is insignificant extra solution activity of mere data gathering. Accessing a database is WURC, based on Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) (storing and retrieving information in memory)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claim as a whole does not change this conclusion and the claim 3, 4 and 5 are ineligible.
Dependent claim 6, 12 and 13 are directed to the same abstract idea as the independent claim from which they depend and further recite additional elements “counting a time of testing the vocabulary level of the child to get the recognition speed of the child in the process of obtaining the vocabulary level of the child; and determining a number of characters in articles to be selected based on the recognition speed of the child in the process of determining articles based on the vocabulary level of the child”, “after the extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit; recognizing the characters to be reviewed and counting the recognition result(s)one or more recognition results of the review”, “updating the characters to be reviewed and the vocabulary level of the child according to the recognition result(s)one or more recognition results of the review; wherein characters to be reviewed refer to the characters recognized by the child as determined based on the vocabulary level of the child” and “updating the memory habit of the child based on the recognition result(s)one or more recognition results of review”. The process of counting time for determining word recognition speed, extracting words to be reviewed and mixing them with interfering words, counting word recognition results, updating words to be reviewed based on word recognition result and determining words to reviewed based on vocabulary level of the child involve observation, judgement and evaluation and can practically be performed in human mind. Accordingly, recited limitations fall into abstract idea groupings of mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “voice guidance” recite insignificant extra-solution activity of outputting data. Viewing the additional limitations together and the respective claims as a whole, nothing provides integration into a practical application. Therefore, claim 6, 12 and 13 are directed to an abstract idea.
At step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of outputting data such is well-understood, routine, and conventional(OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claims individually as a whole does not change this conclusion and the claim 6, 12 and 13 are ineligible.
Claim 28, 29, 30, 31, 32 and 33 differs from claim 3, 4, 5, 6, 12 and 13 respectively in that the steps of the claimed method are implemented by instructions when executed by one or more processors. The invention of claim 27, 28, 29, 30, 31 and 32 are referring a system including one or more processors and a memory storing the instructions to perform recited steps. For reasons discussed above, the claimed steps are directed to mental steps. Use of a processor to execute instructions stored in memory constitutes use of a generic computer as a tool and does not constitute an application of significantly more than the abstract idea. Accordingly, claim 27, 28, 29, 30, 31, 32 and 33 are 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.
Claim 1, 3, 6, 12-13, 26, 28 and 31-33 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, Li (Chinese Patent Document No. CN 110188187) hereafter referred to as Yu, in view of Wang, Xiao-pu (Chinese Patent Document No. CN 110827986), hereafter referred to as Wang, in view of Nariaki, Amano (Japanese Patent Document No. JP 2005107483), hereafter referred to as Nariaki, in view of New; Cecil (US Patent No. 6155834), hereafter referred to as New, in further view of Li, Yong (Chinese Patent Document No. CN 110276005 A), hereafter referred to as Li.
Regarding claim 1(Currently Amended), Yu teaches A method for recommending independent reading for a child, comprising: obtaining vocabulary level of the child determining and pushing articles based on the vocabulary level of the child(Yu, abstract discloses obtaining vocabulary level of person/user (kids or adult) and providing reading content for any person/user (kids or adult) according user’s vocabulary level “the embodiment of the invention claims a recommending method for article, comprising: a vocabulary level data of user is obtained, obtaining a plurality of article difficulty value article to be recommended corresponding to the article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching, the articles to be recommended article difficulty value corresponding to the matching to recommend to the user”);
wherein the method further comprises: checking the vocabulary level of the child in the process of article reading(Yu, page 3 para 3 discloses checking/testing vocabulary level of user “vocabulary test request initiated by receiving the user; obtaining the pre-stored for testing content of the user vocabulary level and display; the test result input by the receiving user; vocabulary level determined according to the test result of the user, and generates the vocabulary level data”); updating and pushing new articles based on one or more check results of the vocabulary level of the child(Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”);
wherein checking the vocabulary level of the child in the process of article reading comprises(Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”):
updating the vocabulary level of the child based on characters clicked by the child in the articles(Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”);
and updating the vocabulary level of the child based on the one or more check results of the child(Yu, page 5 para 2 updating vocabulary level data is being determined based on reading/checking an article “vocabulary level of the user may be enhanced with the reading ability of the user is improved and thus, vocabulary level data may also be updated. one embodiment: push once test content to the user every one period, according to the vocabulary level test result to update user data of user feedback. wherein the test content push can be same or difficulty increases, the second time the test content is pushed to the user”); and verifying checked characters after checking the vocabulary level of the child in the process of article reading, wherein the checked characters refer to the characters clicked by the child in the process of article reading(Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”);
But Yu does not explicitly teach wherein obtaining the vocabulary level of the child comprises: obtaining a set of high-frequency characters that fits the vocabulary level of the child; testing the vocabulary level of the child accordingly to obtain the characters that the child knows to form a character set to be taken as the vocabulary level of the child based on the order of the characters in the set of high-frequency characters;
and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child's actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high- frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child; wherein before obtaining the vocabulary level of the child, the method further comprises: obtaining age of the child; saving the adjusted set of high-frequency characters by classifying the age of the child as a label; and obtaining the adjusted set of high-frequency characters based on age of subsequent child;
counting the number of characters not recognized by and clicked by the child in the process of reading; mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading; marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading; and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of learning assessment Wang teaches
wherein obtaining the vocabulary level of the child comprises: obtaining a set of high-frequency characters that fits the vocabulary level of the child(Wang, Page 5 para 3 discloses getting high-frequency word/character for assessment of a child’s reading capability “Chinese character. assuming that the target object is a child, then the appointed Chinese word can be based on the region of the target object, a high-frequency word and the low frequency word grade selected from the language teaching schema matching”; where Yu teaches obtaining vocabulary level on an user);
testing the vocabulary level of the child accordingly to obtain the characters that the child knows to form a character set to be taken as the vocabulary level of the child based on the order of the characters in the set of high-frequency characters(Wang, Page 5 para 3 further discloses testing the reading ability by how accurately & quickly high frequency words can be read “Chinese word can be based on the region of the target object, a high-frequency word and the low frequency word grade selected from the language teaching schema matching, for example, select a 150 high frequency word and the 60 low frequency word, displaying high frequency word with 5 screen, 2 screen display low-frequency words, each screen display 30 words to target object quickly and accurately read the words on each screen” ); wherein before obtaining the vocabulary level of the child, the method further comprises: obtaining age of the child; saving the adjusted set of high-frequency characters by classifying the age of the child as a label(Wang, page 5 para 3 discloses providing high-frequency word per matching; page 5 para 5 further teaches labeling child age “demographic label of target object of the target object may be gender, age, region, low achievement label of the target object is used for indicating whether the target object belongs to low achievement. assuming that the target object is a child” );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of evaluating children with high frequency words of Wang into evaluating vocabulary level of Yu to produce an expected result of evaluating children with high frequency words. The modification would be obvious because one of ordinary skill in the art would be motivated to improve users screen reading disorder by assessing the risk using content and user level tagging system and providing reading tasks accordingly for improvement (Wang, abstract, para 3-5 of page 2).
Using the broadest reasonable interpretation consistent with the specification as Chinese characters are equivalent to word in English language, the examiner is interpreting the limitation “character” to mean at least any word as well.
But Yu and Wang don’t explicitly teach and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child's actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high- frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child; and obtaining the adjusted set of high-frequency characters based on age of subsequent child; counting the number of characters not recognized by and clicked by the child in the process of reading; mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading; marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading; and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word/character recognition Nariaki teaches and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child's actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high-frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child(Nariaki, page 7 para 3 discloses testing with re-ordering words for assessment of reading ability “collecting the learner's reaction to the output in the reaction collecting unit 14, and analyzing the collected reaction in the reaction analyzing unit 15, Estimate words that the learner does not know. Subsequently, …. and the word output unit 13 rearranges the words obtained by the extraction in the order of familiarity and outputs them together with the word meaning sentence to the learner. To learn words”; where Yu in view of Wang in Page 5 para 3 teaches obtaining high frequency word/character based on child’s vocabulary level).
and obtaining the adjusted set of high-frequency characters based on age of subsequent child(Nariaki, page 11 para 2 teaches adjusted or re-ordered words for subsequent learning “In the subsequent learning stage, by setting c = 0.1 in step 38 described above, the kanji extraction condition for learning kanji that falls within the interval whose familiarity is [5.0, 5.1] is set. Set. Based on this extraction condition, in the above-described step 39, the kanji whose intimacy is in this section, the reading information of the kanji, and the intimacy are extracted from the kanji dictionary 210. In step 40, the extracted kanji characters are rearranged in the order of familiarity, and in steps 41 to 43, the extracted kanji characters are presented to the learner together with the reading information one by one. .”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of presenting reordered characters/words to users for evaluation of Nariaki into evaluating vocabulary level of Yu and Wang to produce an expected result of evaluating children with vocabulary list. The modification would be obvious because one of ordinary skill in the art would be motivated to improve users learning by identifying known and unknown words to users and outputting unknown words with their respective information for learning (Nariaki, abstract).
But Yu, Wang and Nairaka don’t explicitly teach counting the number of characters not recognized by and clicked by the child in the process of reading; mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading; marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading; and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word reorganization assessment New teaches counting the number of characters not recognized by and clicked by the child in the process of reading(New, col 15:6-9 discloses counting incorrect response in recognizing words “Because the student asked for assistance by having the computer display the active word is shown to the student, the active word will be counted as incorrect on the first try”); and guiding the child to the vocabulary level check after the child finishes reading(New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”); marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading(New, col 14:65-67 discloses guiding or helping users on unrecognized words “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”); guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters(New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of counting incorrect response of New into counting response for determining vocabulary level of users of Yu, Wang and Nariaki to produce an expected result of capturing users’ response. The modification would be obvious because one of ordinary skill in the art would be motivated to increase the speed and accuracy of word recognition of individuals by continuously adjust the requirements for word perception and recognition based on characteristics and responses of the individual student (New, abstract).
But Yu, Wang, Nariaki and New don’t explicitly teach mixing the characters in the articles with interfering characters; and mixing the checked characters with interfering characters; wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word reorganization assessment He teaches mixing the characters in the articles with interfering characters(Li, para 2 of page 5/18 discloses words are being mixed with other interfering words for recognition test “in the process of answering each question, the word order is random scrambling, to avoid the memory order inertia effect generated by the answering effect and checked the authenticity”);and mixing the checked characters with interfering characters(Li, para 2 of page 5/18 discloses words are being mixed with other interfering words for recognition test which can similarly be applied for checked or marked characters as well “in the process of answering each question, the word order is random scrambling, to avoid the memory order inertia effect generated by the answering effect and checked the authenticity”); wherein the method further comprises: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit(Li, para 2 of page 5/18 discloses words are being mixed with other interfering words for recognition test “in the process of answering each question, the word order is random scrambling, to avoid the memory order inertia effect generated by the answering effect and checked the authenticity”), wherein a rule of Ebbinghaus forgetting curve is used as the memory habit(Li, para 3 of page 5/18 discloses Ebbinghaus forgetting/memory curve is being used for memory retention related learning “pushing review is based on the theory that the user Ebbinghaus the memory curve word learning record data for algorithm integration, presenting user-specific memory point map, to guide the review node, so as to achieve the learning target high-efficiency memory word”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of using the Ebbinghaus memory curve for word/vocabulary retention form memory of Li into word recognition for user vocabulary level determination of Yu, Wang, Nariaki and New to produce an expected result of increasing memory retention. The modification would be obvious because one of ordinary skill in the art would be motivated to achieve the learning goal of efficient word memorization using Ebbinghaus forgetting/memory curve rules (Li, page 5/18 and para 3).
Claim 2, cancelled.
Regarding claim 3(Original), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 1 and Yu further teaches wherein determining articles comprises: comparing and counting the characters in articles to be selected to get a recognition rate of all articles to be selected based on the vocabulary level of the child(Yu, page 5 para 4 discloses recognition or accuracy rate (rate implies counting as well) “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”); and determining articles to be pushed to the child based on the recognition rate of articles to be selected(Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”).
Regarding claim 6(Original), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 1 and Yu further teaches further comprising: counting a time of testing the vocabulary level of the child to get the recognition speed of the child in the process of obtaining the vocabulary level of the child and determining a number of characters in articles to be selected based on the recognition speed of the child in the process of determining articles based on the vocabulary level of the child (Yu, page 3 para 3 discloses checking/testing vocabulary level of user “vocabulary test request initiated by receiving the user; obtaining the pre-stored for testing content of the user vocabulary level and display; the test result input by the receiving user; vocabulary level determined according to the test result of the user, and generates the vocabulary level data”; Yu Page 8 para 5 further teaches time taken, accuracy and operation frequency (speed) to complete the vocabulary test “The article on a learning data of the user, includes article reading time of the user, making question accuracy, operation frequency, etc. the article the recommended current should study, if the reading time of the user over all users of average reading time of the current article”);
and determining a number of characters in articles to be selected based on the recognition speed of the child in the process of determining articles based on the vocabulary level of the child (Yu, discloses Page 5 para 4 discloses determination of vocabulary level by frequency of operation (speed of recognition) “vocabulary level may also determining user according to the reading data of the article, reading data may include reading time, operation frequency of the user, as accuracy and so on. wherein as question accuracy suitable for articles of learning, learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate”; Yu page 4 last para further discloses word/character count is being considered for vocabulary level determination “the test result after its own standard answer of the test answer accuracy for comparing, calculating content of the user. when determining the vocabulary level of the user, can be determined according to the preset corresponding relation, according to the corresponding relation of question accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”).
Claim 7-12, cancelled.
Regarding claim 12(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 1 and Li further teaches after the extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, further comprising(Li, para 2 of page 5/18 discloses words are being mixed with other interfering words for recognition test “in the process of answering each question, the word order is random scrambling, to avoid the memory order inertia effect generated by the answering effect and checked the authenticity”);
New teaches recognizing the characters to be reviewed and counting one or more recognition results of the review according to a voice guidance (New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”);
Yu teaches and updating the characters to be reviewed and the vocabulary level of the child according to the one or more recognition results of the review; wherein characters to be reviewed refer to the characters recognized by the child as determined based on the vocabulary level of the child (Yu, Page 5 para 2 discloses updating vocabulary level data is being determined based on reading an article “vocabulary level of the user may be enhanced with the reading ability of the user is improved and thus, vocabulary level data may also be updated. one embodiment: push once test content to the user every one period, according to the vocabulary level test result to update user data of user feedback. wherein the test content push can be same or difficulty increases, the second time the test content is pushed to the user”).
Regarding claim 13(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 12 and Johnson further teaches wherein updating the memory habit of the child based on the one or more recognition results of review (Li, para 3 of page 5/18 discloses Ebbinghaus forgetting/memory curve is being used for memory retention related learning by review “pushing review is based on the theory that the user Ebbinghaus the memory curve word learning record data for algorithm integration, presenting user-specific memory point map, to guide the review node, so as to achieve the learning target high-efficiency memory word”).
Claim 14-25, Cancelled.
Regarding claim 26 (Currently Amended), Yu teaches A device for recommending independent reading, comprising: one or more processors; a non-transitory storage coupled to the one or more processors; and a plurality of programs stored in the non-transitory storage that, when executed by the one or more processors, cause the client device to perform acts comprising(Yu, page 8 para 4 discloses a client/device to communicate with server/apparatus for sending request according to user vocabulary level and server/apparatus obtaining module (201) matches article and receives recommendation from server recommendation module (203)):
obtaining vocabulary level of a child; determining and pushing articles based on the vocabulary level of the child; wherein obtaining the vocabulary level of the child comprises(Yu, abstract discloses obtaining vocabulary level of person/user (kids or adult) and providing reading content for any person/user (kids or adult) according user’s vocabulary level “the embodiment of the invention claims a recommending method for article, comprising: a vocabulary level data of user is obtained, obtaining a plurality of article difficulty value article to be recommended corresponding to the article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching, the articles to be recommended article difficulty value corresponding to the matching to recommend to the user”):
wherein the plurality of programs cause the device to perform acts further comprising: checking the vocabulary level of the child in the process of article reading (Yu, page 3 para 3 discloses checking/testing vocabulary level of user “vocabulary test request initiated by receiving the user; obtaining the pre-stored for testing content of the user vocabulary level and display; the test result input by the receiving user; vocabulary level determined according to the test result of the user, and generates the vocabulary level data”); updating and pushing new articles based on one or more check results of the vocabulary level of the child (Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”); wherein checking the vocabulary level of the child in the process of article reading comprises (Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”): updating the vocabulary level of the child based on characters clicked by the child in the articles (Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”); and updating the vocabulary level of the child based on the one or more check results of the child (Yu, page 5 para 2 updating vocabulary level data is being determined based on reading/checking an article “vocabulary level of the user may be enhanced with the reading ability of the user is improved and thus, vocabulary level data may also be updated. one embodiment: push once test content to the user every one period, according to the vocabulary level test result to update user data of user feedback. wherein the test content push can be same or difficulty increases, the second time the test content is pushed to the user”); and verifying checked characters after checking the vocabulary level of the child in the process of article reading, wherein the checked characters refer to the characters clicked by the child in the process of article reading (Yu, page 5 para 4 discloses recognition or accuracy rate by test to determine vocabulary level “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”’; page 4 last para further teaches clicking/selecting question for answer “test content can include selecting questions, fill in the blank questions and judgement questions, the test results may include user input or selected content and options. …. accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”);
But Yu does not explicitly teach obtaining a set of high-frequency characters that fits the vocabulary level of the child; testing the vocabulary level of the child accordingly to obtain the characters that the child knows to form a character set to be taken as the vocabulary level of the child based on the order of the characters in the set of high-frequency characters; and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child’s actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high-frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child, wherein before performing the acts of obtaining the vocabulary level of the child, the plurality of programs cause the device to perform acts further comprising: obtaining age of the child; saving the adjusted set of high-frequency characters by classifying the age of the child as a label; and obtaining the adjusted set of high-frequency characters based on age of subsequent child;
counting the number of characters not recognized by and clicked by the child in the process of reading; mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading; marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading; and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the plurality of programs cause the device to perform acts further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of learning assessment Wang teaches obtaining a set of high-frequency characters that fits the vocabulary level of the child (Wang, Page 5 para 3 discloses getting high-frequency word/character for assessment of a child’s reading capability “Chinese character. assuming that the target object is a child, then the appointed Chinese word can be based on the region of the target object, a high-frequency word and the low frequency word grade selected from the language teaching schema matching”; where Yu teaches obtaining vocabulary level on an user); testing the vocabulary level of the child accordingly to obtain the characters that the child knows to form a character set to be taken as the vocabulary level of the child based on the order of the characters in the set of high-frequency characters (Wang, Page 5 para 3 further discloses testing the reading ability by how accurately & quickly high frequency words can be read “Chinese word can be based on the region of the target object, a high-frequency word and the low frequency word grade selected from the language teaching schema matching, for example, select a 150 high frequency word and the 60 low frequency word, displaying high frequency word with 5 screen, 2 screen display low-frequency words, each screen display 30 words to target object quickly and accurately read the words on each screen” ); wherein before performing the acts of obtaining the vocabulary level of the child, the plurality of programs cause the device to perform acts further comprising: obtaining age of the child; saving the adjusted set of high-frequency characters by classifying the age of the child as a label(Wang, page 5 para 3 discloses providing high-frequency word per matching; page 5 para 5 further teaches labeling child age “demographic label of target object of the target object may be gender, age, region, low achievement label of the target object is used for indicating whether the target object belongs to low achievement. assuming that the target object is a child” );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of evaluating children with high frequency words of Wang into evaluating vocabulary level of Yu to produce an expected result of evaluating children with high frequency words. The modification would be obvious because one of ordinary skill in the art would be motivated to improve users screen reading disorder by assessing the risk using content and user level tagging system and providing reading tasks accordingly for improvement (Wang, abstract, para 3-5 of page 2).
Using the broadest reasonable interpretation consistent with the specification as Chinese characters are equivalent to word in English language, the examiner is interpreting the limitation “character” to mean at least any word as well.
But Yu and Wang don’t explicitly teach and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child’s actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high-frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child, and obtaining the adjusted set of high-frequency characters based on age of subsequent child; counting the number of characters not recognized by and clicked by the child in the process of reading;
mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading;
marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading;
and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the plurality of programs cause the device to perform acts further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word/character recognition Nariaki teaches and in the process of obtaining the vocabulary level of the child, updating the order of the characters in the set of high-frequency characters according to the child’s actual knowledge to the characters in the set of high-frequency characters, and thus forming an adjusted set of high-frequency characters to be taken as a subsequent set of high-frequency characters for testing the vocabulary level of a subsequent child (Nariaki, page 7 para 3 discloses testing with re-ordering words for assessment of reading ability “collecting the learner's reaction to the output in the reaction collecting unit 14, and analyzing the collected reaction in the reaction analyzing unit 15, Estimate words that the learner does not know. Subsequently, …. and the word output unit 13 rearranges the words obtained by the extraction in the order of familiarity and outputs them together with the word meaning sentence to the learner. To learn words”; where Yu in view of Wang in Page 5 para 3 teaches obtaining high frequency word/character based on child’s vocabulary level), and obtaining the adjusted set of high-frequency characters based on age of subsequent child(Nariaki, page 11 para 2 teaches adjusted or re-ordered words for subsequent learning “In the subsequent learning stage, by setting c = 0.1 in step 38 described above, the kanji extraction condition for learning kanji that falls within the interval whose familiarity is [5.0, 5.1] is set. Set. Based on this extraction condition, in the above-described step 39, the kanji whose intimacy is in this section, the reading information of the kanji, and the intimacy are extracted from the kanji dictionary 210. In step 40, the extracted kanji characters are rearranged in the order of familiarity, and in steps 41 to 43, the extracted kanji characters are presented to the learner together with the reading information one by one. .”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of presenting reordered characters/words to users for evaluation of Nariaki into evaluating vocabulary level of Yu and Wang to produce an expected result of evaluating children with vocabulary list. The modification would be obvious because one of ordinary skill in the art would be motivated to improve users learning by identifying known and unknown words to users and outputting unknown words with their respective information for learning (Nariaki, abstract).
But Yu, Wang and Nairaka don’t explicitly teach counting the number of characters not recognized by and clicked by the child in the process of reading;
mixing the characters in the articles with interfering characters, and guiding the child to the vocabulary level check after the child finishes reading;
marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading;
and mixing the checked characters with interfering characters, guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters; wherein the plurality of programs cause the device to perform acts further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word reorganization assessment New teaches counting the number of characters not recognized by and clicked by the child in the process of reading (New, col 15:6-9 discloses counting incorrect response in recognizing words “Because the student asked for assistance by having the computer display the active word is shown to the student, the active word will be counted as incorrect on the first try”); and guiding the child to the vocabulary level check after the child finishes reading (New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”); marking characters that the child does not recognize in the articles based on the vocabulary level of the child in the process of determining articles, and guiding the child to click the marked characters in the process of article reading (New, col 14:65-67 discloses guiding or helping users on unrecognized words “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”); guiding the child to find the checked characters by voice, and determining the one or more check results of the vocabulary level of the child based on the one or more results of finding the checked characters (New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of counting incorrect response of New into counting response for determining vocabulary level of users of Yu, Wang and Nariaki to produce an expected result of capturing users’ response. The modification would be obvious because one of ordinary skill in the art would be motivated to increase the speed and accuracy of word recognition of individuals by continuously adjust the requirements for word perception and recognition based on characteristics and responses of the individual student (New, abstract).
But Yu, Wang, Nariaki and New don mixing the characters in the articles with interfering characters, and mixing the checked characters with interfering characters; wherein the plurality of programs cause the device to perform acts further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit, wherein a rule of Ebbinghaus forgetting curve is used as the memory habit.
However, in the same field of endeavor of word reorganization assessment Li teaches mixing the characters in the articles with interfering characters(Johnson, col 18: 66~ col 19:1 discloses words are being mixed with other interfering words for recognition test “Recognition Test Old words were randomly mixed with an equal number of new words (words that are similar but not on the list to be memorized)”), and mixing the checked characters with interfering characters (Johnson, col 18: 66~ col 19:1 discloses words are being mixed with other interfering words for recognition test which can similarly be applied for checked or marked characters as well “Recognition Test Old words were randomly mixed with an equal number of new words (words that are similar but not on the list to be memorized)”); wherein the plurality of programs cause the device to perform acts further comprising: extracting characters to be reviewed and mixing them with interfering characters according to the child's memory habit(Li, para 2 of page 5/18 discloses words are being mixed with other interfering words for recognition test “in the process of answering each question, the word order is random scrambling, to avoid the memory order inertia effect generated by the answering effect and checked the authenticity”), wherein a rule of Ebbinghaus forgetting curve is used as the memory habit(Li, para 3 of page 5/18 discloses Ebbinghaus forgetting/memory curve is being used for memory retention related learning “pushing review is based on the theory that the user Ebbinghaus the memory curve word learning record data for algorithm integration, presenting user-specific memory point map, to guide the review node, so as to achieve the learning target high-efficiency memory word”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of using the Ebbinghaus memory curve for word/vocabulary retention form memory of Li into word recognition for user vocabulary level determination of Yu, Wang, Nariaki and New to produce an expected result of increasing memory retention. The modification would be obvious because one of ordinary skill in the art would be motivated to achieve the learning goal of efficient word memorization using Ebbinghaus forgetting/memory curve rules (Li, page 5/18 and para 3).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of recognition of words in a mixture of interfering word sequence of Johnson into word recognition for user vocabulary level determination of Yu, Wang, Nariaki and New to produce an expected result of performing word recognition test with interfering words. The modification would be obvious because one of ordinary skill in the art would be motivated to perform a word recognition test where words are scrambled with other interfering word for truthful/proper evaluation (Johnson, col 19: 9-12).
Claim 27, Cancelled.
Regarding claim 28(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 26 and Yu further teaches wherein determining articles comprises: comparing and counting the characters in articles to be selected to get a recognition rate of all articles to be selected based on the vocabulary level of the child (Yu, page 5 para 4 discloses recognition or accuracy rate (rate implies counting as well) “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”); and determining articles to be pushed to the child based on the recognition rate of articles to be selected (Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”).
Regarding claim 31(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 26 and Yu further teaches counting a time of testing the vocabulary level of the child to get the recognition speed of the child in the process of obtaining the vocabulary level of the child (Yu, page 3 para 3 discloses checking/testing vocabulary level of user “vocabulary test request initiated by receiving the user; obtaining the pre-stored for testing content of the user vocabulary level and display; the test result input by the receiving user; vocabulary level determined according to the test result of the user, and generates the vocabulary level data”; Yu Page 8 para 5 further teaches time taken, accuracy and operation frequency (speed) to complete the vocabulary test “The article on a learning data of the user, includes article reading time of the user, making question accuracy, operation frequency, etc. the article the recommended current should study, if the reading time of the user over all users of average reading time of the current article”);
and determining a number of characters in articles to be selected based on the recognition speed of the child in the process of determining articles based on the vocabulary level of the child (Yu, discloses Page 5 para 4 discloses determination of vocabulary level by frequency of operation (speed of recognition) “vocabulary level may also determining user according to the reading data of the article, reading data may include reading time, operation frequency of the user, as accuracy and so on. wherein as question accuracy suitable for articles of learning, learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate”; Yu page 4 last para further discloses word/character count is being considered for vocabulary level determination “the test result after its own standard answer of the test answer accuracy for comparing, calculating content of the user. when determining the vocabulary level of the user, can be determined according to the preset corresponding relation, according to the corresponding relation of question accuracy corresponding relation with the vocabulary, vocabulary and vocabulary quantity level”).
Regarding claim 32(Currently Amended), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 26 and New teaches wherein the plurality of programs cause the device to perform acts further comprising: recognizing the characters to be reviewed and counting one or more recognition results of the review according to a voice guidance(New, col 14:65-67 discloses reviewing words with voice guidance (saying/pronouncing words ) “Say Word(s). Counts as First Try Missed." follows step 760. Because the student asked for assistance by having the computer pronounce the active or target word for the student, the active word will be counted as incorrect on the first try”);
Yu teaches and updating the characters to be reviewed and the vocabulary level of the child according to the one or more recognition results of the review; wherein characters to be reviewed refer to the characters recognized by the child as determined based on the vocabulary level of the child(Yu, Page 5 para 2 discloses updating vocabulary level data is being determined based on reading an article “vocabulary level of the user may be enhanced with the reading ability of the user is improved and thus, vocabulary level data may also be updated. one embodiment: push once test content to the user every one period, according to the vocabulary level test result to update user data of user feedback. wherein the test content push can be same or difficulty increases, the second time the test content is pushed to the user”).
Regarding claim 33(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 32 and Li further teaches wherein updating the memory habit of the child based on the one or more recognition results of review (Li, para 3 of page 5/18 discloses Ebbinghaus forgetting/memory curve is being used for memory retention related learning by review “pushing review is based on the theory that the user Ebbinghaus the memory curve word learning record data for algorithm integration, presenting user-specific memory point map, to guide the review node, so as to achieve the learning target high-efficiency memory word”).
Claim 4 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, Li (Chinese Patent Document No. CN 110188187) hereafter referred to as Yu, in view of Wang, Xiao-pu (Chinese Patent Document No. CN 110827986), hereafter referred to as Wang, in view of Nariaki, Amano (Japanese Patent Document No. JP 2005107483), hereafter referred to as Nariaki, in view of New, Cecil (US Patent No. 6155834), hereafter referred to as New, in view of Li, Yong (Chinese Patent Document No. CN 110276005), hereafter referred to as Li, in further view of Choi, Jeong et al(Korean Patent Document No. KR 20050038973), hereafter referred to as Choi.
Regarding claim 4(Original), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 3 and Yu further teaches wherein obtaining the recognition rate of articles to be selected comprises(Yu, page 5 para 4 discloses recognition or accuracy rate (rate implies counting as well) “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”): deduplicating the same character refers to a deduplication of a character that appears repeatedly in an article (Yu, page 5, para 1 discloses words/vocabulary are being selected based on their frequency in the article, frequency represents grouping of multiple instances of same word as one and, which implies deduplication of multiple instances of a word/vocabulary “counting eash word in the article appearance frequency ….then ordering all words according to the word frequency, selecting…..”);
But Yu, Wang, Nariaki, New and Li don’t explicitly teach and counting a same character with different pronunciations in an article based on the pronunciation.
However, in the same field of endeavor of counting words Choi teaches and counting a same character with different pronunciations in an article based on the pronunciation(Choi, page 4 para 4 discloses considering word pronouncing differently as different words “the number of words pronounced differently according to variation and adjacent sounding according to adjacent numbers are treated as different words, and the connection rate of each word is increased by using the grammar of the language model”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of differently pronounced same word as different words of Choi into counting words of Yu, Wang, Nariaki, New and Li to produce an expected result of considering instances of same word/character that pronounced differently. The modification would be obvious because one of ordinary skill in the art would be motivated to enhance the word count process by considering each instance of differently pronounced word/character having different meaning using phoneme-based pronunciation dictionary model (Choi, page 4 para 4).
Regarding claim 29(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 28 and Yu further teaches wherein obtaining the recognition rate of articles to be selected comprises(Yu, page 5 para 4 discloses recognition or accuracy rate (rate implies counting as well) “learning article in the type generally comprises a test question corresponding to the article content, as test question of the question accuracy represents the user correct rate, which can reflect the understanding degree of user to the article content”): deduplicating the same character refers to a deduplication of a character that appears repeatedly in an article (Yu, page 5, para 1 discloses words/vocabulary are being selected based on their frequency in the article, frequency represents grouping of multiple instances of same word as one and, which implies deduplication of multiple instances of a word/vocabulary “counting eash word in the article appearance frequency ….then ordering all words according to the word frequency, selecting…..”);
But Yu, Wang, Nariaki, New and Li don’t explicitly teach and counting a same character with different pronunciations in an article based on the pronunciation.
However, in the same field of endeavor of counting words Choi teaches and counting a same character with different pronunciations in an article based on the pronunciation(Choi, page 4 para 4 discloses considering word pronouncing differently as different words “the number of words pronounced differently according to variation and adjacent sounding according to adjacent numbers are treated as different words, and the connection rate of each word is increased by using the grammar of the language model”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of differently pronounced same word as different words of Choi into counting words of Yu, Wang, Nariaki, New and Li to produce an expected result of considering instances of same word/character that pronounced differently. The modification would be obvious because one of ordinary skill in the art would be motivated to enhance the word count process by considering each instance of differently pronounced word/character having different meaning using phoneme-based pronunciation dictionary model (Choi, page 4 para 4).
Claim 5 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, Li (Chinese Patent Document No. CN 110188187) hereafter referred to as Yu, in view of Wang, Xiao-pu (Chinese Patent Document No. CN 110827986), hereafter referred to as Wang, in view of Nariaki, Amano (Japanese Patent Document No. JP 2005107483), hereafter referred to as Nariaki, in view of New; Cecil (US Patent No. 6155834), hereafter referred to as New, in view of Li, Yong (Chinese Patent Document No. CN 110276005), hereafter referred to as Li, Kristin et al(PGPUB Document No. 20200058230), hereafter referred to as Hosp.
Regarding claim 5(Original), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 3 and Yu further teaches wherein after determining articles to be pushed to the child based on the recognition rate of articles to be selected, the method further comprises(Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”):
But Yu, Wang, Nariaki, New and Li don’t explicitly tech updating the articles to be selected based on the number of characters that the child does not recognize in the articles, thus controlling the number of characters that the child does not recognize in the recommended articles.
However, in the same field of endeavor of word reorganization assessment Hosp teaches updating the articles to be selected based on the number of characters that the child does not recognize in the articles, thus controlling the number of characters that the child does not recognize in the recommended articles (Hosp, discloses determining word mastery level based on selected incorrect and correctly recognized word which determines contents to be pushed “The ways in which the assessment engine 103 may vary based on the purpose of the administration of the assessment. .. in screening, whether a subject read a word correctly or incorrectly may be scored dichotomously (right or wrong), ……is used to identify a specific activity to undertake to improve the level of mastery of the skill; the activity may be a particular intervention in which the assessment engine 103 selects a set of words for the user to practice on, each of the selected words selected for its ability to improve an understanding of an aspect of a phonics skill”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of recommending contents for word recognition skill based on incorrectly or correctly recognized words of Hosp into reading contents recommendation of Yu, Wang, Nariaki, New and Li to produce an expected result of updating content recommendation based on word recognition (incorrectly or correctly) assessment. The modification would be obvious because one of ordinary skill in the art would be motivated to use a process for identifying and recommending specific activities for users which would improve users level of word recognition mastery skill (Hosp, para 0054).
Regarding claim 30(Previously Presented), Yu, Wang, Nariaki, New and Li teach all the limitations of claim 28 and Yu further teaches wherein after determining articles to be pushed to the child based on the recognition rate of articles to be selected, the method further comprises(Yu, Page 8 para 5 further teaches recommending articles based on user’s vocabulary level “201 for a vocabulary level data of user is obtained by the obtaining module, obtaining a plurality of article difficulty value respectively corresponding article to be recommended. determining module 202 used for article difficulty value from a plurality of said article difficulty value is determined from the vocabulary level data matching. a recommendation module 203 for the article difficulty value of the matching corresponding article to be recommended to recommend to the user”):
But Yu, Wang, Nariaki, New and Li don’t explicitly tech updating the articles to be selected based on the number of characters that the child does not recognize in the articles, thus controlling the number of characters that the child does not recognize in the recommended articles.
However, in the same field of endeavor of word reorganization assessment Hosp teaches updating the articles to be selected based on the number of characters that the child does not recognize in the articles, thus controlling the number of characters that the child does not recognize in the recommended articles (Hosp, discloses determining word mastery level based on selected incorrect and correctly recognized word which determines contents to be pushed “The ways in which the assessment engine 103 may vary based on the purpose of the administration of the assessment. .. in screening, whether a subject read a word correctly or incorrectly may be scored dichotomously (right or wrong), ……is used to identify a specific activity to undertake to improve the level of mastery of the skill; the activity may be a particular intervention in which the assessment engine 103 selects a set of words for the user to practice on, each of the selected words selected for its ability to improve an understanding of an aspect of a phonics skill”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of recommending contents for word recognition skill based on incorrectly or correctly recognized words of Hosp into reading contents recommendation of Yu, Wang, Nariaki, New and Li to produce an expected result of updating content recommendation based on word recognition (incorrectly or correctly) assessment. The modification would be obvious because one of ordinary skill in the art would be motivated to use a process for identifying and recommending specific activities for users which would improve users level of word recognition mastery skill (Hosp, para 0054).
Response to Arguments
I. 35 U.S.C §103
In response to applicant’s amendments to independent claims, update abstract idea rejection to claim 1,3-6, 12-13, 26 and 28-33 has been presented in its respective section of this office action.
II. 35 U.S.C §103
Applicant’s arguments filed on 2/13/2026 have been fully considered but are
moot because the independent claim 1 and 26 have been amended with newly added
features which applicant’s arguments are directed towards. Since claims have been amended with new features, a new ground of rejection is presented.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDULLAH A DAUD whose telephone number is (469)295-9283. The examiner can normally be reached M~F: 9:30 am~6:30 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amy Ng can be reached at 571-270-1698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ABDULLAH A DAUD/Examiner, Art Unit 2164 /AMY NG/Supervisory Patent Examiner, Art Unit 2164
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