Systems and methods for feed-back based updateable content

1. A system for providing feed-back based updateable content, in terms of feedback output signals correlative to text items from content, served on an internet enabled device with sensors, the internet enabled device configured to serve an e-book having content and corresponding text items, the system comprising a computer processor communicably coupled with the internet enabled device, the processor configured to:

define and enforce rules, concerning a text analyzer, to analyze the content to determine, per content or portion thereof, analyzed text vectors, the analyzed text vectors being selected from a group of vectors consisting of readability indicator vector, verbosity indicator vector, regional colloquialism vector, genre vector, and sub-genre vector;

define and enforce rules, concerning a reader profiler, to analyze and profile a reader in terms of the analyzed text vectors to obtain reader classification vectors, the reader classification vectors being selected from a group of vectors consisting of language proficiency vector, content affinity vector, frequency vector, usage parameter-based vector, and cluster vector;

dynamically form clusters of readers based on at least a selected reader classification vector;

select two or more the dynamically formed clusters;

parse the served content through the selected two or more dynamically formed clusters to obtain cluster-specific analyzed text vectors;

provide a first feedback output signal, by a feedback output signal provider, to be displayed in consonance with at least a first start signal text item and a first end signal text item, the text items being from the content, the first feedback output signal being in the form of tagging of text items starting from the at least a first start signal text item and ending with the at least a first end signal text item, the first feedback output signal being in correlation with a pre-defined cluster of readers in correlation with a specific analyzed text vector;

change first feedback output signal tagged text items, causing changed content, to cause a change in the specific analyzed text vector;

serve the changed content vide changed text items to the two or more dynamically formed clusters;

parse the changed content through the selected two or more dynamically formed clusters to obtain changed cluster-specific analyzed text vectors;

provide a next feedback output signal, by a feedback output signal provider, to be displayed in consonance with at least a first start signal text item and a first end signal text item, the text items being from the content, the next feedback output signal being in the form of tagging of text items starting from the at least a first start signal text item and ending with the at least a first end signal text item, the next feedback output signal being in correlation with the pre-defined cluster of readers in correlation with the specific analyzed text vector;

check if the specific analyzed text vector fits within pre-defined ranges of values, provided by optimum text analyzed vectors, across the two or more dynamically formed clusters; and

serve the changed content, from the internet-enabled device to the e-book reader, only if the checked analyzed text vector conforms to the pre-defined ranges of values across the two or more dynamically formed clusters.

2. The system as claimed in claim 1 wherein, the system comprises a text indexer based on screen polling, in that, a screen polling mechanism is configured to poll screen size of the internet enabled device serving the e-book, the corresponding text indexer being configured to annotate each text item from content items of the e-book with a unique first signal, selected from a first set of signals, by a first signal generating mechanism; each signal from the first set of signals being called a first signal, the text indexer being communicably coupled with the screen polling mechanism to tag an object-correlative start text item per object per polled screen size, with an object-correlative start first signal, and to further tag an object-correlative end text item per object per screen polled size, with an object-correlative end first signal; thereby providing a set of object-correlative start first signals corresponding to object-correlative start text items configured with a screen-relevant/screen dependent object number and further providing a set of object-correlative end first signals corresponding to object-correlative end text items configured with a screen-relevant/screen dependent object number, each of the first set of signals being activated on the internet enabled device to be sensed by a sensor array of the internet enabled device, the object being a page object, an e-book object, a chapter object, or a sentence object.

3. The system as claimed in claim 1 wherein, the system comprises a second set of signals, each signal from the second set of signals being called a second signal, generated by a second signal generating mechanism configured to be activated at text items, at pre-defined repeating intervals throughout the e-book, or portions thereof, irrespective of screen size or page size, the repetition rate being constant throughout the e-book; thereby, forming a set of signals which are repetitive, periodically occurring, signals throughout the e-book and activated on the e-book, through the internet enabled device, to be sensed by a sensor array of the internet enabled device.

4. The system as claimed in claim 1 wherein a first sensor of the sensors is configured to trace user-engagement, with a page-correlative start first signal and its corresponding page-correlative start first signal, with a first timer, the first timer, coupled with the first sensor, is configured to record time spent corresponding to number of screen-relevant pages in conjunction with a prolonged time span, all recorded by the first timer, the sensed data being fed to a computer processor configured to obtain analyzed text vectors and to record speed of engagement with the repetitive, periodically occurring, signals per defined time span.

5. The system as claimed in claim 1 wherein a first sensor of the sensors is configured to trace user-engagement, with a page-correlative start first signal and its corresponding page-correlative start first signal, with a first timer, the first timer, coupled with the first sensor, the first timer being pre-set with an outer time limit so that if a reader stops engaging with an e-book, on the internet enabled device, the computer processor being configured to realize this event as a reader abandoning the e-book.

6. The system as claimed in claim 1 wherein a second sensor of the sensors is configured to trace user-engagement with a repetitive, periodically occurring, signal in consonance with a second timer, coupled with the second sensor, configured to record time spent from a page-correlative start first signal, per screen-relevant page, and a page-correlative end first signal, per screen-relevant page, all recorded by the second timer, and wherein the sensed data is fed to a computer processor configured to obtain analyzed text vectors and to record speed of engagement per screen, thereby, providing time-engagement data and/or time-responsive data correlative to any two second signal-activated text items in the e-book, or portions thereof.

7. The system as claimed in claim 1 wherein a third sensor of the sensors is configured to trace user-engagement with a book-correlative start first signal and its corresponding book-correlative start first signal with a third timer, the third timer, coupled with the third sensor, is configured to record time spent corresponding to number of screen-relevant e-books in conjunction with a prolonged time span, all recorded by the third timer, and wherein the sensed data is fed to a computer processor configured to obtain analyzed text vectors and to record speed of engagement with the repetitive, periodically occurring, signals per defined time span.

8. The system as claimed in claim 1 wherein a fourth sensor of the sensors is configured to trace user-engagement with a chapter-correlative start first signal and its corresponding chapter-correlative start first signal with a fourth timer, the fourth timer, coupled with the fourth sensor, is configured to record time spent corresponding to number of screen-relevant chapters in conjunction with a prolonged time span, all recorded by the fourth timer, and wherein the sensed data is fed to a computer processor configured to obtain analyzed text vectors and to record speed of engagement with the repetitive, periodically occurring, signals per defined time span.

9. The system as claimed in claim 1 wherein a fifth sensor of the sensors is configured to trace user-engagement with a sentence-correlative start first signal and its corresponding sentence-correlative start first signal with a fifth timer, the fifth timer, coupled with the fifth sensor, is configured to record time spent corresponding to number of screen-relevant sentences in conjunction with a prolonged time span, all recorded by the fifth timer, and wherein the sensed data is fed to a computer processor to obtain analyzed text vectors and to record speed of engagement with the repetitive, periodically occurring, signals per defined time span.

10. The system as claimed in claim 1 wherein, the text analyzer comprises a first parser configured to parse content data between a pre-defined start first signal and an end first signal to determine at least a readability indicator in terms of pre-defined metrics, and the computer processor is configured with rules concerning derivation of readability indicator, for text items, between any two second signal-activated text items wherein at least one of,

the sensors trace and output time-engagement data/time-responsive data,

the text analyzer determines passive voice count for that selected portion of content,

the text analyzer determines number of long sentences for that selected portion of content, and

text analyzer determines clichés for that selected portion of content, characterised in that, in a database a list of clichés are stored which are used to n-grams that fall into the list stored in the database of clichés, the computer processor bucketing total number of words in the order of most common words used to most rarely used words.

11. The system as claimed in claim 1 wherein, the text analyzer comprises a second parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a verbosity indicator for an e-book, the computer processor being configured with rules concerning derivation of verbosity, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data and/or time-responsive data.

12. The system as claimed in claim 1 wherein the text analyzer comprises a second parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a verbosity indicator for an e-book, and wherein in that the verbosity of any content is determined, correlative to defined databases, by:

ranking words, of a dictionary, in terms of their general usage: most common words to most rarely used words; and

defining databases, each database comprising a pre-defined bucket of words in the order of most common words used to most rarely used word such that the verbosity indicator uses,

a first database comprising first 3000 most commonly used words,

a second database comprising 3000th to 10000th most commonly used words,

a third database comprising 10000th to 40000th most commonly used words,

a fourth database comprising 40000th to 60000th most commonly used words,

a fifth database comprising 60000th to 80000th most commonly used words,

a sixth database comprising 80000th to 100000th most commonly used words,

a seventh database comprising 100000th to 130000th most commonly used words, and

an eighth database comprising first 13000th to 17000th most commonly used words.

13. The system as claimed in claim 1 wherein, the text analyzer comprises a third parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a regional colloquialism indicator for an e-book, and the computer processor is configured with rules concerning at least one of,

derivation of colloquialism used, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data and/or time-responsive data, and

derivation of type of language used, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data/time-responsive data.

14. The system as claimed in claim 1 wherein the text analyzer comprises a third parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a regional colloquialism indicator for an e-book, and wherein the colloquialism in any content is determined, correlative to defined geography-tagged databases, by:

determining phrases, words, and aphorisms, in correlation with a defined geography; and

defining databases, each database comprising a pre-defined bucket of determined phrases, words, and aphorisms, wherein the regional colloquialism indicator uses,

a ninth database comprises a first-geography based bucket of words,

a tenth database comprises a first-geography based bucket of phrases,

an eleventh database comprises a first-geography based bucket of aphorisms,

a twelfth database comprises a second-geography based bucket of words,

a thirteenth database comprises a second-geography based bucket of phrases, and

a fourteenth database comprises a second-geography based bucket of aphorisms.

15. The system as claimed in claim 1 wherein the text analyzer comprises a fourth parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a genre and sub-genre indicator for an e-book, wherein the genre and sub-genre of any content is determined correlative to pre-defined BISAC codes.

16. The system as claimed in claim 1 wherein, the text analyzer comprises a fourth parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a genre and sub-genre indicator for an e-book, and the computer processor is configured with rules concerning at least one of,

derivation of genre, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data/time-responsive data, and

term frequency using an inverse document frequency methodology to facilitate topic identification and genre identification.

17. The system as claimed in claim 1 wherein the text analyzer comprises,

a fourth parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to determine at least a genre and sub-genre indicator for an e-book, the computer processor is configured with a genre classifier configured to classify and record each e-book with a genre and feed the genre data, when the e-book is consumed by a reader, to the communicably coupled computer processor,

a fifth parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to extract and determine at least a time period for an e-book using Natural Language Processing, then putting into time based buckets, and associating with page numbers, and

a sixth parser configured to parse content data between a pre-defined start first signal and a pre-defined end first signal to extract and determine at least a geography for an e-book, using Natural Language Processing, then putting into geography based buckets, and associating with page numbers.

18. The system as claimed in claim 1 wherein the computer processor is configured with rules concerning at least one of,

derivation of length of sentences, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data and/or time-responsive data, and

derivation of syntactic constructions, for text items, between any two second signal-activated text items where the sensors trace and output time-engagement data and/or time-responsive data.

19. The system as claimed in claim 1 wherein, the system further comprises:

a first parameterizer configured to parameterize an e-book in terms of its readability index;

a second parameterizer configured to parameterize a reader in terms of their readability index correlative to clusters of reader profiles;

a mapper configured to map pre-defined parameters of the first parameterizing module with pre-defined parameters of the second parameterizing module of a reader, the mapping is done per e-book per reader, to obtain a mapped parameterized correlative coefficient; and

a feedback output signal provider configured to use mapped parameterized correlative coefficient to provide an improved output, the improved output is improved content with compliant text analyzed vectors, wherein the computer processor is configured with rules to record data from the first timer, data from the second timer, data from the text analyzer correlative to the text analyzed vectors, and/or data from the reader profiler correlative to the reader classification vectors; to process a variety of indices per unique reader, and correlate the plurality of indices with a corresponding e-book, served on an internet enabled device with sensors, to provide consumption-led data per e-book as a feedback signal.

20. A method of providing feed-back based updateable content, in terms of feedback output signals correlative to text items from content, served on an internet enabled device with sensors, the internet enabled device configured to serve an e-book having content and corresponding text items, with a computer processor communicably coupled with the internet enabled device, the method comprising:

defining and enforcing rules, concerning a reader profiler, to analyze and profile a reader in terms of the analyzed text vectors to obtain reader classification vectors, the reader classification vectors being selected from a group of vectors consisting of language proficiency vector, content affinity vector, frequency vector, usage parameter-based vector, and cluster vector;

dynamically forming clusters of readers based on at least a selected reader classification vector;

selecting two or more the dynamically formed clusters;

parsing the served content through the selected two or more dynamically formed clusters to obtain cluster-specific analyzed text vectors;

providing a first feedback output signal, by a feedback output signal provider, to be displayed in consonance with at least a first start signal text item and a first end signal text item, the text items being from the content, the first feedback output signal being in the form of tagging of text items starting from the at least a first start signal text item and ending with the at least a first end signal text item, the first feedback output signal being in correlation with a pre-defined cluster of readers in correlation with a specific analyzed text vector;

changing first feedback output signal tagged text items, causing changed content, to cause a change in the specific analyzed text vector;

serving the changed content vide changed text items to the two or more dynamically formed clusters;

parsing the changed content through the selected two or more dynamically formed clusters to obtain changed cluster-specific analyzed text vectors;

providing a next feedback output signal, by a feedback output signal provider, to be displayed in consonance with at least a first start signal text item and a first end signal text item, the text items being from the content, the next feedback output signal being in the form of tagging of text items starting from the at least a first start signal text item and ending with the at least a first end signal text item, the next feedback output signal being in correlation with the pre-defined cluster of readers in correlation with the specific analyzed text vector;

checking if the specific analyzed text vector fits within pre-defined ranges of values, provided by optimum text analyzed vectors, across the two or more dynamically formed clusters; and

serving the changed content, from the internet-enabled device to the e-book reader, only if the checked analyzed text vector conforms to the pre-defined ranges of values across the two or more dynamically formed clusters, wherein the method is performed with the computer processor.