DETAILED ACTION
This is responsive to the amendment filed 23 September 2025.
Claims 1, 5-6, 8 and 13-16 remain pending and are considered below.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 23 September 2025 regarding the 35 USC 101 rejection have been fully considered but they are not persuasive.
Applicant argues:
The Applicant respectfully disagrees with the Examiner's assertion that the present invention can be conducted solely in the human mind. Instead, the above processing steps are specifically designed to scan texts comprising a large number of Chinese characters, allowing for simultaneous processing of multiple pieces of text. These texts are truncated into hundreds, if not thousands, of block units of varying block sizes. Given the complexity of the subsequent processing steps as detailed above, it is evident that such tasks cannot be managed and processed by the human mind. Humans have intrinsic limitations in processing and analyzing large volumes of information quickly. The computational efficiency and speed at which the invention operates far exceed human capabilities, as individuals typically require significantly more time to read, comprehend, and categorize information.
The method employs automated and systematic categorization based on semantic radicals and their relative positions within each character forming the block units. Given the vast number of block units of varying sizes, it is clearly impossible for a human to process accurately without bias or error. The method requires a structured analysis of semantic radicals and their meanings, which demands advanced understanding and computational capacity that can be practically difficult for humans, especially with nuanced languages like Chinese.
Additionally, the processing steps further involve comparing newly processed block units with previously stored data for efficient categorization. Humans have limited memory and may struggle to recall all relevant information or previous categorizations accurately, especially when dealing with a large number of block units.
Furthermore, the ability to dynamically define and adjust category groups based on context of the specific text being analyzed requires a level of technical adaptability that is difficult for humans to maintain accuracy consistently. This is especially true when managing multiple pieces of text with extensive character counts. A human mind is not equipped to automatically detect, define and adjust the category groups as recited by the claims, regardless of whether a pen or a paper are used. The presenting and visually summarizing complex data characteristics of multiple texts based on the dynamically varied and defined category groups at high speed is highly challenging, if not impossible for human capability.
Accordingly, the present invention leverages computational power and algorithms to achieve a technical solution which is impractical to perform entirely in a humans' mind, especially at scale. The invention offers a fast, effective solution to address known challenges in analyzing Chinese language, presenting a significant improvement in the technical field of language analytics. The processing steps which involve scanning and successive truncations of multiple texts, and the complex processing and comparing of block units to previously processed and stored data to re-employ already learned categorization of same or similar block units also increase processing efficiency, reduce memory requirements, and enhance accuracy of the analyses.
The present invention therefore possesses a technical character, offering a technical solution to address the complexity and difficulties in learning Chinese language. Unlike prior art translation technologies that rely on word-for-word translations and human's subjective interpretation based on dictionary meanings, this invention provides a fast and accurate solution for systematically analyzing large texts and multiple texts at high speeds.
…
Applicant is of the view that the present invention, which automatically scans a piece of text or multiple texts having a large number of Chinese characters, cannot be practically performed in the human mind. The invention is capable of scanning, truncating, processing and analyzing vast volumes of text in real-time or nearly real-time with high accuracy. For example, a detailed analysis of an entire literary work consisting of hundreds or thousands of characters can be processed and completed in seconds. This solution is achieved through a combination of specific, technically complex method steps, as detailed above. Given the intricacy of these processes and the scale of data involved, it is clear that these tasks cannot be practically performed in the human mind. Human cognition is not equipped to automatically process and analyze thousands of characters simultaneously, particularly when it involves successive truncation and identification of semantic radicals and their relative positions and part-of-speech ratios. Furthermore, the display of related terms, words, vocabularies, expressions or reference texts based on a level of matching with the overall characteristics; and the subsequent matching from a library of reference texts having the same or similar category groups which are dynamically created specific to the respective text, and suggesting in high speeds based on a degree of matching is clearly impractical and impossible for mental execution of human.
Accordingly, the present invention transcends the limitations of human mental processes. Manual searching and matching of characters against dictionaries cannot achieve the analytical depth required to interpret semantic radicals and their positions accurately or to recognize patterns across extensive texts, as achievable by the present invention. This approach is impractical if replaced by human mental processes, which will unavoidably lack the accuracy and speed necessary for comprehensive understanding and effective learning.
The Examiner respectfully disagrees. The claimed methods are not rendered patent eligible by the fact that (using existing machine learning technology) they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. The courts have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. See, e.g., Content Extraction, 776 F.3d at 1347; DealerTrack, 674 F.3d at 1333. Whether the issue is raised at step one or step two, the increased speed and efficiency resulting from use of computers (with no improved computer techniques) do not themselves create eligibility. See, e.g., Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355, 1363 (Fed. Cir. 2023) (rejecting argument that “humans could not mentally engage in the ‘same claimed process’ because they could not perform ‘nanosecond comparisons’ and aggregate ‘result values with huge numbers of polls and members’”) (internal citation omitted); Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (holding claims abstract where “[t]he only improvements identified in the specification are generic speed and efficiency improvements inherent in applying the use of a computer to any task”).
Applicant further argues:
The current claim recites limitations of technical scanning, truncating, and subsequently, analysing including automatic identifying, categorizing and computing based on computation implementation. While the subject matter involves processes that may involve or rely upon computation, the claimed subject matter, when considered as a whole, provides a practical application that reflects an improvement to the technical field of language processing, providing a technical solution to a technical problem.
…
The technical solution offered being the highly efficient evaluation of texts comprising Chinese characters based on semantic radicals analysis, with the results being presented in an easily understandable, visual representation showing a number of dynamically defined category groups having only some of the highest number of block units which are indicative of characteristics, such as the theme, genre, grade and/or level of difficulty, of the multiple texts analyzed. Analyzing radicals and their position in the character helps to reveal the underlying meaning of characters, as radicals often convey essential concepts or themes. In contrast to the traditional, word for word translation, analysis to the level of semantic radicals can further provide information on patterns and structures within the language, aiding in recognizing and predicting underlying meanings of characters. As the block units are categorized into the dynamically defined category groups based on meanings of the semantic radicals forming the characters, the results are generated at an enhanced accuracy, when compared to the direct word for word comparison or translation by traditional language analysis method, which is highly difficult, if not impossible, to be upscale to multiple pieces of texts of large number of characters.
Additionally, the present invention offers fast and effective searching and suggestions for related terms, words, vocabularies, or expressions, as well as reference texts of Chinese characters, tailored to the theme, the genre, the grade and/or the level of difficulty of the input texts. This functionality is particularly beneficial for learners of the Chinese language, especially when processing lengthy texts or multiple documents with extensive word counts.
The technical solution is achieved by the specific combination of the technical steps as defined by the currently amended independent claim, with the steps, when executed, provide specific technical functions to significantly improve the technological field of language processing, searching and language analytics. The subject matter is therefore clearly not a mere abstract idea, but instead, provides a practical technical solution to technical problem. Furthermore, the unique combination of technical steps as currently defined in the independent claim are not found in any of the prior art references cited by the Examiner. The present invention therefore presents a significant technical advancement over the prior art and provides a practical solution to a practical problem.
However, The claims do not impose any limits on how the piece of text is received and scanned. The claims also do not impose any limits how the visual statistic, the predetermined number of category groups, the related terms, words, vocabularies, or expressions based on the overall characteristics of the text are displayed. The claims further do not impose any limits on how the matched reference texts are output. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. In particular, these limitations represent the extra-solution activity or gathering, displaying and outputting data. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
Applicant also argues:
Furthermore, the present invention surpasses the capabilities of generic computer systems that primarily rely on word-for-word translations from dictionaries, without contextual understanding. While standard computer components may execute basic translations, they fail to analyze semantic radicals, categorize meanings, or synthesize insights from complex linguistic structures. In contrast, the present solution employs advanced computation specifically designed to dissect and interpret the intricate relationships between radicals, their positions and their meanings, delivering a level of analysis unattainable by conventional systems. The present invention therefore offers significant improvements over generic computer operations.
However, Applicant’s computer components are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0014], [0034] and [0038]-[0040]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
Applicant finally argues:
Lastly, the present invention emphasizes the analytical dimension of language processing. It systematically categorizes text of block units based on semantic radicals and their meanings, generating meaningful statistics that reflect the thematic, genre, and difficulty characteristics of the text. Moreover, the invention suggests reference texts that share similar themes, genres, grades, or difficulty levels in relation to the input Chinese text. This process involves sophisticated analysis of character structures and their explicit and implicit meanings, as well as language patterns formed by various block units such as words and sentences. Consequently, users gain insights that far exceed the capabilities of generic processing of data gathering and outputting alone.
Accordingly, Applicant is of the view that the invention as defined by the currently amended claim 1 is beyond mere mental processes or abstract ideas, as it cannot be practically performed by the human mind alone. The specific combination of steps executed by the defined technical components surpasses the operations of generic computers. Instead, it directs to a unique combination of technical features specifically designed to provide a tangible, technical solution, representing a significant technical improvement over general computer functionality that exceeds a human's mind and a computer's ordinary of capacity. The invention addresses the conventional challenges in analyzing Chinese characters, providing a technical solution that improves both accuracy and speed of the analysis. The invention goes beyond merely collecting or receiving data; the specific processing steps provide advanced language analytics at the level of semantic radicals, with the results presented in easily understandable representation. All these indicate that the present invention qualifies a statutory subject matter under 35 USC §101. Removal of the present rejections are warranted.
However, other than reciting a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16) nothing in the claims precludes the steps from practically being performed in the mind.
For example, a person may truncate the piece of text into a plurality of first block units each having a first predefined number of N characters, where N is an integer and is greater than or equal to one (e.g. a human may segment a piece of Chinese text into blocks of characters); determining for a selected character from the N characters of each of the first block units, one or more radicals forming said selected character (e.g. a human may identify radicals for some of the characters); identifying from the one or more radicals forming said selected character, one or more semantic radicals in respect of a position parameter by comparing the one or more radicals with a database comprising semantic radicals and their associated meanings (e.g. a human may determine semantic radicals from the identified radicals using a database as claimed), and determining one or more meanings of the one or more semantic radicals in relation to said selected character, wherein said position parameter comprises a relative position of the radical within the character (e.g. a human may determine meanings of the semantic radicals as claimed); categorizing the plurality of first block units into automatically generated category groups based on the determined meanings of the semantic radicals of the selected character of each of the first block units; wherein the step of categorizing the plurality of first block units further comprises categorizing one or more first block units of the plurality of first block units is based on one or more part-of-speeches of the corresponding meanings of the semantic radicals of the selected character of each of the first block units (e.g. a human may classify the blocks into categories based on part-of-speeches as claimed); computing a number of the first block units categorized in the respective generated category groups indicative of one or more characteristics of the text; wherein the one or more characteristics are determined by one or more ratios of the part-of-speeches of the semantic radicals of the selected character of each of the first block units; wherein the one or more characteristics comprise one or more of a theme a genre, a grade and/or a level of difficulty of the text (e.g. a human may count blocks in each of the categories as claimed); successively truncating the text via the truncating module into one or more second block units each having a second predefined number of M characters, wherein M is an integer greater than N by at least a value of 1; and repeating the determining, identifying and categorizing steps prior to the computing step to suggest an overall characteristic of the text; wherein the categorizing step comprises comparing the second block units to previously processed block units stored in a database to re-employ already learned categorizations of same or similar block units (e.g. a human may segment the piece of Chinese text into second blocks of characters as claimed); and matching, from a library of texts, one or more pieces of reference texts having same or similar category groups (e.g. a human may match, from a library, texts in similar categories).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements – a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16) which are recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using a generic computer components. The claims are therefore directed to an abstract idea.
The claims also recite the additional elements “receiving, via a communication module, the piece of text”, “scanning the piece of text”, “displaying, via the computing module, a visual representation only some of the category groups having a highest number of the first block units indicative of the one or more characteristics of the text”, “displaying, via the computing module, related terms, words, vocabularies, or expressions based on the overall characteristics of the text”; and “outputting, based on a degree of matching, matched reference texts having same or similar category groups to the piece of text”. The claims do not impose any limits on how the piece of text is received and scanned. The claims also do not impose any limits how the visual statistic, the predetermined number of category groups, the related terms, words, vocabularies, or expressions based on the overall characteristics of the text are displayed. The claims further do not impose any limits on how the matched reference texts are output. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. In particular, these limitations represent the extra-solution activity or gathering, displaying and outputting data. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As stated above, the claims recite the additional limitations of a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16). However, these are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0014], [0034] and [0038]-[0040]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
The claims also recite the additional elements “receiving, via a communication module, the piece of text”, “scanning the piece of text”, “displaying, via the computing module, a visual representation only some of the category groups having a highest number of the first block units indicative of the one or more characteristics of the text”, “displaying, via the computing module, related terms, words, vocabularies, or expressions based on the overall characteristics of the text”; and “outputting, based on a degree of matching, matched reference texts having same or similar category groups to the piece of text”. The claims do not impose any limits on how the piece of text is received and scanned. The claims also do not impose any limits how the visual statistic, the predetermined number of category groups, the related terms, words, vocabularies, or expressions based on the overall characteristics of the text are displayed. The claims further do not impose any limits on how the matched reference texts are output. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. These limitations represent the extra-solution activity of gathering/scanning, displaying and outputting data which are well-understood, routine and conventional activities. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Therefore, all of Applicant’s argument regarding the 35 USC 101 rejection have been addressed and they are unpersuasive.
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, 5-6, 8 and 13-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Further, this judicial exception is not integrated into a practical application.
In claims 1 and 16, the limitations
determining,
identifying,
categorizing,
computing,
wherein the one or more characteristics comprise one or more of a theme a genre, a grade and/or a level of difficulty of the text;
successively truncating the text via the truncating module into one or more second block units each having a second predefined number of M characters, wherein M is an integer greater than N by at least a value of 1; and repeating the determining, identifying and categorizing steps prior to the computing step to suggest an overall characteristic of the text; wherein the categorizing step comprises comparing the second block units to previously processed block units stored in a database to re-employ already learned categorizations of same or similar block units;
matching, from a library of texts, one or more pieces of reference texts having same or similar category groups; and interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components.
That is, other than reciting a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16) nothing in the claims precludes the steps from practically being performed in the mind.
For example, a person may truncate the piece of text into a plurality of first block units each having a first predefined number of N characters, where N is an integer and is greater than or equal to one (e.g. a human may segment a piece of Chinese text into blocks of characters);
determining for a selected character from the N characters of each of the first block units, one or more radicals forming said selected character (e.g. a human may identify radicals for some of the characters);
identifying from the one or more radicals forming said selected character, one or more semantic radicals in respect of a position parameter by comparing the one or more radicals with a database comprising semantic radicals and their associated meanings (e.g. a human may determine semantic radicals from the identified radicals using a database as claimed), and determining one or more meanings of the one or more semantic radicals in relation to said selected character, wherein said position parameter comprises a relative position of the radical within the character (e.g. a human may determine meanings of the semantic radicals as claimed);
categorizing the plurality of first block units into automatically generated category groups based on the determined meanings of the semantic radicals of the selected character of each of the first block units; wherein the step of categorizing the plurality of first block units further comprises categorizing one or more first block units of the plurality of first block units is based on one or more part-of-speeches of the corresponding meanings of the semantic radicals of the selected character of each of the first block units (e.g. a human may classify the blocks into categories based on part-of-speeches as claimed);
computing a number of the first block units categorized in the respective generated category groups indicative of one or more characteristics of the text; wherein the one or more characteristics are determined by one or more ratios of the part-of-speeches of the semantic radicals of the selected character of each of the first block units; wherein the one or more characteristics comprise one or more of a theme a genre, a grade and/or a level of difficulty of the text (e.g. a human may count blocks in each of the categories as claimed);
successively truncating the text via the truncating module into one or more second block units each having a second predefined number of M characters, wherein M is an integer greater than N by at least a value of 1; and repeating the determining, identifying and categorizing steps prior to the computing step to suggest an overall characteristic of the text; wherein the categorizing step comprises comparing the second block units to previously processed block units stored in a database to re-employ already learned categorizations of same or similar block units (e.g. a human may segment the piece of Chinese text into second blocks of characters as claimed); and
matching, from a library of texts, one or more pieces of reference texts having same or similar category groups (e.g. a human may match, from a library, texts in similar categories).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements – a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16) which are recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using a generic computer components. The claims are therefore directed to an abstract idea.
The claims also recite the additional elements “receiving, via a communication module, the piece of text”, “scanning the piece of text”, “displaying, via the computing module, a visual representation only some of the category groups having a highest number of the first block units indicative of the one or more characteristics of the text”, “displaying, via the computing module, related terms, words, vocabularies, or expressions based on the overall characteristics of the text”; and “outputting, based on a degree of matching, matched reference texts having same or similar category groups to the piece of text”. The claims do not impose any limits on how the piece of text is received and scanned. The claims also do not impose any limits how the visual statistic, the predetermined number of category groups, the related terms, words, vocabularies, or expressions based on the overall characteristics of the text are displayed. The claims further do not impose any limits on how the matched reference texts are output. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. In particular, these limitations represent the extra-solution activity or gathering, displaying and outputting data. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As stated above, the claims recite the additional limitations of a “computer-implemented method for scanning a piece of text having a large number of Chinese characters, or multiple pieces of text simultaneously each having a large number of Chinese characters”, a “communication module”, a “truncating module”, a “determining module”, an “identifying module”, a “categorizing module”, a “computing module” (claim 1) and a “system comprising a memory for storing data and a processor for executing computer readable instructions” (claim 16). However, these are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0014], [0034] and [0038]-[0040]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
The claims also recite the additional elements “receiving, via a communication module, the piece of text”, “scanning the piece of text”, “displaying, via the computing module, a visual representation only some of the category groups having a highest number of the first block units indicative of the one or more characteristics of the text”, “displaying, via the computing module, related terms, words, vocabularies, or expressions based on the overall characteristics of the text”; and “outputting, based on a degree of matching, matched reference texts having same or similar category groups to the piece of text”. The claims do not impose any limits on how the piece of text is received and scanned. The claims also do not impose any limits how the visual statistic, the predetermined number of category groups, the related terms, words, vocabularies, or expressions based on the overall characteristics of the text are displayed. The claims further do not impose any limits on how the matched reference texts are output. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. These limitations represent the extra-solution activity of gathering/scanning, displaying and outputting data which are well-understood, routine and conventional activities. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
The dependent claims, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea.
The dependent claims recite:
wherein the meaning of the one or more semantic radicals comprises explicit, direct meaning and implicit, associated meaning,
wherein the computing step further comprises a step of generating a representation comprising a number of the first block units in each respective category groups,
storing the category groups having highest numbers of the first block units in respect of the piece of text,
wherein the method steps are implemented by a processor of a computer device,
wherein the steps are implemented by a network server,
storing the computed number of first block units categorized in the one or more category groups in a memory unit.
The additional recited limitations further narrow the steps of the independent claims without however providing “a practical application of” or "significantly more than" the underlying “Mental Processes” abstract idea. Therefore, the dependent claims are also not patent eligible.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SAMUEL G NEWAY/ Primary Examiner, Art Unit 2657