CN112800341A - Education resource transmission system based on big data - Google Patents
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Abstract
The invention discloses an educational resource transmission system based on big data, which comprises a library book scheduling management module, an intelligent recommendation module, a user information pickup module, a data comparison module, an interest degree time judgment module, an interference factor insertion module, a content relevance recommendation module, a standard correction module, a book folding degree determination module, an electronic book transmission module, an authority level online identification module, a partial interface remote sharing module, an electronic book forwarding authority module, a non-vpn channel sharing module, an electronic book chapter purchasing module and an authority permission authentication module, wherein the library book scheduling management module is used for judging whether a book is in a common library or a collection library, judging whether the residual quantity of the books selected by a user is smaller than a preset quantity, and recommending similar books when the quantity of the books selected by the user is small, and judging the preference degree of the user for the selected book through the interestingness time judging module, and recommending the book to the user.
Description
Technical Field
The invention relates to the technical field of big data education, in particular to an education resource transmission system based on big data.
Background
At present, the development and education of the country are more and more inseparable, higher social status, wages and experiences can be obtained through good education, which is valuable wealth for everyone in the society, but education is still unbalanced in different areas, so most people select areas with concentrated education to receive education, which can cause the unbalanced educational development in the areas;
at present, books borrowed by students in a library are learning materials, reference answer auxiliary books and the like in class, books borrowed by students in different specialties are concentrated among a plurality of books, so that other books in the library are idle, most of the books become background walls of the library, and therefore the residual quantity of the books borrowed by students in the colleges is small, and the residual books in the library can be fully utilized; meanwhile, electronic resources bought by precious books or schools exist in all large libraries, so that the resources can be shared by other non-native school students properly, but in order to ensure that the non-native school students can borrow resources from the school change seriously, part of the contents of the books are usually set as contents for paying borrowing, so that the non-native school students can pay attention to the borrowed resources, and therefore, an education resource transmission system giving big data is needed to solve the problems.
Disclosure of Invention
The present invention is directed to a big data-based educational resource delivery system to solve the above-mentioned problems of the background art.
In order to solve the technical problems, the invention provides the following technical scheme: an educational resource transmission system based on big data comprises a library book scheduling management module, an intelligent recommendation module, a user information pickup module, a data comparison module, an interestingness time judgment module, an interference factor insertion module, a content relevancy recommendation module, a standard correction module, a book folding degree determination module, an electronic book transmission module, an authority level online identification module, a partial interface remote sharing module, an electronic book forwarding authority module, a non-vpn channel sharing module, an electronic book chapter purchase module and an authority permission authentication module, wherein the library book scheduling management module is used for judging the specific position of a book required by a user and the residual quantity of the books borrowed by the user according to the search record of the user in a library so that the user can borrow the books required by the user, the intelligent recommendation module is used for inquiring that the quantity of the books required by the user is not enough to borrow the user, recommending books to a user so that the user can timely look up knowledge points of the books and fully utilize resources of the remaining books in a library, wherein the user information pickup module is used for picking up the professional and grade information of a user borrowing the books, the data comparison module is used for comparing the knowledge points of the books selected by the user with the knowledge points in the recommended books and judging whether the books are similar, the interest degree time judgment module is used for judging the interest degree of the user on the current books according to the book reading behavior of the user so as to recommend the related books to the user, the interference factor insertion module is used for recommending interference books irrelevant to the knowledge points in the books selected by the user to the user and judging whether the user is interfered by the interfered knowledge points of the books so as to analyze the interest degree of the user on the current books, and the content relevance recommending module is used for recommending the similar books according to the content of the knowledge points in the books selected by the user, the book recommendation method comprises the steps of enabling books recommended by users to contain the same knowledge point content, recommending the books to the users again when the knowledge point content in the recommended books is not larger than the knowledge point content in the books selected by the users, and accordingly ensuring that the users can learn more knowledge points in the recommended books, judging the folding degree of the surfaces of the books when the books searched by the users exist in a treasure book base to prevent the users from damaging the books with larger folding degree, supplying the books selected by the users to the users for borrowing in an electronic book mode when the folding degree of the books is detected to be higher, enabling the users to browse the contents of the electronic books without damaging the precursors of the books, and judging whether the users are students in the current school or not when the users browse the books through the electronic books through the online permission level recognition module, the electronic book reading system comprises a remote sharing module with partial interfaces, a non-vpn channel sharing module and an electronic book chapter purchasing module, wherein the remote sharing module with partial interfaces is used for checking the identity of a user and providing the user with remote online reference of electronic book data when the user is not in school, the electronic book forwarding permission module is used for checking the identity of the user and limiting the forwarding times of the electronic book when the user forwards the borrowed electronic book to other users, so as to ensure the electronic book to be effectively shared, the non-vpn channel sharing module is used for forbidding the non-school user to acquire the electronic book in a library through a vpn channel, so that the school user can effectively acquire the resource of the electronic book, the electronic book chapter purchasing module is used for looking up the contents of the electronic book through the purchasing of the electronic chapter when the school user is detected that the school user gives the electronic shared book to the non-school user, thereby referring to the contents of the electronic book.
Further, the interestingness time judging module recommends the borrowing time of a professional book selected by the user and the borrowing time of other types of books and the weighted value for judging that the user prefers the book in a short term, and records the book as yc, wherein the other types of books recommend the recommended book which is irrelevant to the content of the knowledge point of the book being read by the user;
according to the formula:
;
wherein: yc is the weight value of the book preferred by the user in a short term, c1 and c2 are the number of books borrowed by the user and the number of books recommended to the user respectively,
meaning the degree of influence a user borrows a book based on recommending the book to the user,
the influence degree of the user on book borrowing after the user recommends the book at a certain time is referred to, and n is the total number of times the book is consulted;
when the fact that the weight value of the book borrowed by the user is larger than the weight value of the book recommended to the user is detected, the fact that the preference degree of the user to the book in short time is high is shown; when detecting that the weight value of the book borrowed by the user is smaller than the weight value of the book recommended to the user, calculating the time for the user to see the book, and when detecting that yi-yk < ri-rk and repeatedly reading the user and selecting a professional book, indicating that the time for the user to check the recommended book is smaller than the time for the user to check the professional book and the short-term time of the user is influenced by other kinds of books; when the yi-yk > ri-rk is detected and the user does not select the professional book repeatedly by reading, the time for the user to view the recommended book is larger than the time for the user to view the professional book, and the preference degree of the user to select the professional book in the short-term time is low, wherein yi refers to the time period for the user to view the recommended book, yk refers to the time period for the user to view the recommended book, ri refers to the time period for the user to view the professional book, and rk refers to the time period for the user to view the professional book.
Further, the user information pickup module is used for judging the correlation between the professional book selected by the user and the specialty learned by the user, when correlation is detected, the interest value S is reduced, and when the fact that the professional book selected by the user is not correlated with the specialty learned by the user is detected, the interest value S is increased;
when the fact that the professional book selected by the user is not related to the professional book learned by the user is detected, the set of book borrowing times in the first student set and the same time period is W = { W1, W2, w3... wn }, wherein n refers to students, and when the judgment is made, the students pick up the professional book, the set of book borrowing times in the first student set and the same time period is
When the number of the average book addresses read by the students in the first student set is larger than the standard number, the interest value S of the current user in the professional books in a long time is reduced; when judging
When the number of the average book reading times of the students in the first student set is smaller than the standard number, the interest value S of the current user in the professional books in a long time is increased, and the professional books selected by the second student set are recommended to the user;
wherein S = S0+ Si, S0 is the initial interest value, Si is the variation interest value, i is the first student, wi is the number of times any student borrows the book,
refers to the number of standard average borrowings;
the second student set refers to students with the same interest value range of the borrowed books as the user, and the first student set refers to students with the same class or the same repair specialty as the user.
Furthermore, when the user browses, the content relevance recommending module marks the knowledge point related to the content browsed by the user as W, marks the knowledge point contained in the recommended book as Y, and collects the similar parts of the knowledge point W and the knowledge point Y to compare, wherein sim is the similarity of the comparison between the knowledge point W contained in the first k pages browsed by the user and the whole knowledge point of the recommended book, and sim is calculated by adopting the following formula;
wherein, wiIs the word of the knowledge point in the page turned by the user, yiMeans that the recommended book turns over the knowledge point vocabulary in the i page, wjRefers to the word of the knowledge point in the page j turned by the user, yjThe method refers to that the recommended book reads knowledge point words in j pages and sets the page number y of the recommended bookj-yzContaining knowledge point vocabulary and the number of pages read by the useri-wkThe contained knowledge points are compared, yzMeans that when it is detected that sim is larger than sim, the whole book contains vocabulary of knowledge pointsiWhen the user browses the content, the similarity between the knowledge point vocabulary related to the user browsing content and the knowledge point vocabulary in the recommended book is high; recommending books to users when the knowledge points in the recommended books are larger than or equal to the knowledge points in the books turned over by the current users, and not recommending books, sim, to the users when detecting that the knowledge points in the recommended books are smaller than the knowledge points in the books turned over by the usersiThe standard similarity is the comparison of the knowledge points W contained in the top k pages browsed by the user and the knowledge points of all recommended books.
Furthermore, through the book folding degree determining module, the book borrowed by the user enters the drawingThe library gallery time is tiThe time when the borrowed book is borrowed is t0When t is detected0-ti>tkDuring the process, the folding degree of the current book is calculated, the folding degree is set to be Q, and the current book is subjected to photographing analysis:
according to the formula:
；
wherein:
refers to the smoothness of the surface of each page of the book,
refers to the degree of mildew on the surface of the book, F refers to the total number of pages of the book, m refers to the first page of the book, x refers to the total number of pages of the book, and FmRefers to any page in the book, QiThe standard folding degree of the book is referred to;
when Q is detected<QiWhen the book is checked, the book is checked to be out of the book;
when Q is detected>QiAnd when the book is not borrowed, the electronic file of the borrowed book is sent to the user through the electronic book transmission module.
Through the electronic book forwarding authority module, when a borrowed book is forwarded to other users, the information of the user is called through the user information pickup module, when the fact that the user is a first non-native school user and the borrowed book is a professional book set by a non-native school student is detected, when the fact that the non-native school student clicks the electronic book is detected, the number of times k and the stay time length are L, L = ak + b, a and b refer to function coefficients, and when L is detected, the fact that the borrowed book is clicked by the non-native school student is judged to be a professional book set by>LiThen, a fee D, D = D is collected for the electronic book contents to the first non-proof user0+r*d1,d0Refer to a trialFee charged by the content, d1The fee charged per page for the remaining contents, D the total fee, r the number of pages of the electronic book, LiWhich means the standard time for a non-native student staying in an electronic book.
Furthermore, the sharing times of the electronic books borrowed by the first non-native school user are limited through the electronic book forwarding permission module, and the number of pages read on the electronic books by the first non-native school user is detected in real time;
when detecting that the number of pages of the electronic book clicked by the first non-proof school user is the last number of pages of the book and detecting that the first non-proof school user stays at the last number of pages of the electronic book, the duration zi>zkWhen z iskThe electronic book sharing method includes that a first non-native school user stays on a book at ordinary times for the average of the time length, the electronic book is shared with a second non-native school user to read, when the first non-native school user stops reading midway, the electronic book can be shared with the second non-native school user until the first non-native school user logs in again to read the electronic book, and the second non-native school user is interrupted to read the electronic book.
The system comprises the following steps:
z01, through the library book scheduling management module, the user searches the specific positions of the books in the library, judges whether the books are in the common library or the treasure library, simultaneously judges whether the number of the residual books of the books selected by the user is less than the preset number, and recommends similar books when the number of the books selected by the user is small;
z02: determining the interest degree of the user for the selected books when the number of the books of the user is less than the preset number through an interest degree time judging module, judging the preference degree of the user for the selected books, and recommending the books to the user;
z03: sending the book to a user for looking up through the electronic book or directly obtaining knowledge points through looking up the book by a book wrinkle degree determining module according to the wrinkle degree of the book;
z04: whether the current user is a student of the primary school or not is judged through the electronic book forwarding authority module and the electronic book chapter purchasing module, and when a non-primary school user is detected, the non-primary school user needs to purchase chapters so that the user can conveniently look up books.
Compared with the prior art, the invention has the following beneficial effects:
1. the method comprises the steps that through a library book scheduling management module, the storage positions of books are judged through various retrieval modes, the number of the stored books selected by a user is collected, and when the number of the stored books is detected to be less than the preset number, the preference degree of the user on the selected books is judged, so that the books are recommended to the user, the remaining stored books in the library are scheduled, the book resources in the library are fully utilized, the user can obtain more knowledge points from various books of the same kind, and the knowledge plane of the user is enriched;
2. through the interestingness time judging module, recommending books to the user, judging whether the weighted values of other kinds of books of the user are higher than the weighted values of the books selected by the user or not, so that whether the selected books are short-term interesting or not can be analyzed, when the situation that the user is not short-term interesting is detected, further analyzing whether the user is long-term interesting or not, recommending the books to the user, recommending professional books suitable for the user to the student condition, and gradually increasing the knowledge area of the user instead of randomly recommending the books to the user, so that the interestingness of the user to the books is reduced;
3. through books fold degree confirming module, judge whether the book of borrowing is the student of this school at present, when fold degree is less than preset default, send the electronic file of books for the user and read, guarantee the importance of knowledge point transmission, when detecting that the user of long-range books of borrowing is the user of this school, carry out partial chapter content to the student of this school and charge, guarantee that the user can be to the attention of resource to acquire more knowledge points and richen oneself.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic flow diagram of a big data based educational resource delivery system of the present invention;
fig. 2 is a schematic view showing the block composition of a big data-based educational resource delivery system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution:
an educational resource transmission system based on big data comprises a library book scheduling management module, an intelligent recommendation module, a user information pickup module, a data comparison module, an interestingness time judgment module, an interference factor insertion module, a content relevancy recommendation module, a standard correction module, a book folding degree determination module, an electronic book transmission module, an authority level online identification module, a partial interface remote sharing module, an electronic book forwarding authority module, a non-vpn channel sharing module, an electronic book chapter purchase module and an authority permission authentication module, wherein the library book scheduling management module is used for judging the specific position of a book required by a user and the residual quantity of the books borrowed by the user according to the search record of the user in a library so that the user can borrow the books required by the user, the intelligent recommendation module is used for inquiring that the quantity of the books required by the user is not enough to borrow the user, recommending books to a user so that the user can timely look up knowledge points of the books and fully utilize resources of the remaining books in a library, wherein the user information pickup module is used for picking up the professional and grade information of a user borrowing the books, the data comparison module is used for comparing the knowledge points of the books selected by the user with the knowledge points in the recommended books and judging whether the books are similar, the interest degree time judgment module is used for judging the interest degree of the user on the current books according to the book reading behavior of the user so as to recommend the related books to the user, the interference factor insertion module is used for recommending interference books irrelevant to the knowledge points in the books selected by the user to the user and judging whether the user is interfered by the interfered knowledge points of the books so as to analyze the interest degree of the user on the current books, and the content relevance recommending module is used for recommending the similar books according to the content of the knowledge points in the books selected by the user, the book recommendation method comprises the steps of enabling books recommended by users to contain the same knowledge point content, recommending the books to the users again when the knowledge point content in the recommended books is not larger than the knowledge point content in the books selected by the users, and accordingly ensuring that the users can learn more knowledge points in the recommended books, judging the folding degree of the surfaces of the books when the books searched by the users exist in a treasure book base to prevent the users from damaging the books with larger folding degree, supplying the books selected by the users to the users for borrowing in an electronic book mode when the folding degree of the books is detected to be higher, enabling the users to browse the contents of the electronic books without damaging the precursors of the books, and judging whether the users are students in the current school or not when the users browse the books through the electronic books through the online permission level recognition module, the electronic book reading system comprises a remote sharing module with partial interfaces, a non-vpn channel sharing module and an electronic book chapter purchasing module, wherein the remote sharing module with partial interfaces is used for checking the identity of a user and providing the user with remote online reference of electronic book data when the user is not in school, the electronic book forwarding permission module is used for checking the identity of the user and limiting the forwarding times of the electronic book when the user forwards the borrowed electronic book to other users, so as to ensure the electronic book to be effectively shared, the non-vpn channel sharing module is used for forbidding the non-school user to acquire the electronic book in a library through a vpn channel, so that the school user can effectively acquire the resource of the electronic book, the electronic book chapter purchasing module is used for looking up the contents of the electronic book through the purchasing of the electronic chapter when the school user is detected that the school user gives the electronic shared book to the non-school user, thereby referring to the contents of the electronic book;
at present, universities are provided with VPN channels for students in colleges to remotely borrow, but the non-college students are given opportunities to borrow educational resources, but the non-college students do not pay attention to resources after acquiring the resources, and are willingly forwarded and sold on various large network stations, so that the resources borrowed by the non-college students are charged, the non-college students can pay attention to the educational resources, the VPN channels are a private network commonly used for large-scale enterprises or groups, the data content of the enterprises cannot be uploaded, and the safety effect of data encryption is achieved.
Further, the interestingness time judging module recommends the borrowing time of a professional book selected by the user and the borrowing time of other types of books and the weighted value for judging that the user prefers the book in a short term, and records the book as yc, wherein the other types of books recommend the recommended book which is irrelevant to the content of the knowledge point of the book being read by the user;
according to the formula:
;
wherein: yc is the weight value of the book preferred by the user in short term, c1 and c2 are the book borrowed by the user and the book recommended to the user respectively,
meaning the degree of influence a user borrows a book based on recommending the book to the user,
the influence degree of the user on borrowing the book after the user recommends the book at a certain time is referred to;
when the fact that the weight value of the book borrowed by the user is larger than the weight value of the book recommended to the user is detected, the fact that the preference degree of the user to the book in short time is high is shown; when detecting that the weight value of the book borrowed by the user is smaller than the weight value of the book recommended to the user, calculating the time for the user to see the book, and when detecting that yi-yk < ri-rk and repeatedly reading the user and selecting a professional book, indicating that the time for the user to check the recommended book is smaller than the time for the user to check the professional book and the short-term time of the user is influenced by other kinds of books; when detecting that yi-yk > ri-rk and the user does not select the professional book repeatedly by reading, the time for the user to view the recommended book is longer than the time for the user to view the professional book, and the preference degree of the user to select the professional book within the short-term time is lower, wherein yi refers to the starting time period for the user to view the recommended book, yk refers to the ending time period for the user to view the recommended book, ri refers to the starting time period for the user to view the professional book, and rk refers to the ending time period for the user to view the professional book;
whether the attaching degree of the borrowed book by the user is higher than the book recommended to the user or not can be known through setting the weight, the interest degree of the borrowed book by the user is known, the set weight is obtained, the influence degree of each book when the book is borrowed is judged, the book is recommended according to the influence degree of each book, meanwhile, the time of reading the book by the user is needed to be judged, and the preference degree of the user is expressed.
Further, the user information pickup module is used for judging the correlation between the professional book selected by the user and the specialty learned by the user, when correlation is detected, the interest value S is reduced, and when the fact that the professional book selected by the user is not correlated with the specialty learned by the user is detected, the interest value S is increased;
when the fact that the professional book selected by the user is not related to the professional book learned by the user is detected, the set of book borrowing times in the first student set and the same time period is W = { W1, W2, w3... wn }, wherein n refers to students, and when the judgment is made, the students pick up the professional book, the set of book borrowing times in the first student set and the same time period is
When the number of the average book addresses read by the students in the first student set is larger than the standard number, the interest value S of the current user in the professional books in a long time is reduced; when judging
When the number of the average book reading times of the students in the first student set is less than the standard number, the interest value S of the current user in the professional books in a long time is increased,recommending the professional books selected by the second student set to the user;
wherein S = S0+ Si, S0 is the initial interest value, Si is the variation interest value, i is the first student, wi is the number of times any student borrows the book,
refers to the number of standard average borrowings;
the second student set refers to students with the same interest value range as that of the borrowed book by the user, and the first student set refers to students with the same class or the same repair specialty as the user;
analyzing the interest degree of the user for borrowing the books again, detecting the times of the user for borrowing the books by students in the same class, and analyzing that the user borrows the books along with the masses;
by S = S0+ Si, where set Si means that the user 'S interest in the selected book content changes, the user' S interest level in the book is high or low, and therefore, the way of recommending the book to the user is also different.
Furthermore, when the user browses, the content relevance recommending module marks the knowledge point related to the content browsed by the user as W, marks the knowledge point contained in the recommended book as Y, and collects the similar parts of the knowledge point W and the knowledge point Y to compare, wherein sim is the similarity of the comparison between the knowledge point W contained in the first k pages browsed by the user and the whole knowledge point of the recommended book, and sim is calculated by adopting the following formula;
wherein, wiIs the word of the knowledge point in the page turned by the user, yiMeans that the recommended book turns over the knowledge point vocabulary in the i page, wjRefers to the word of the knowledge point in the page j turned by the user, yjThe recommendation is set by the recommended books through the knowledge point vocabulary in the j pagesBook page number yj-yzContaining knowledge point vocabulary and the number of pages read by the useri-wkThe contained knowledge points are compared, yzMeans that when it is detected that sim is larger than sim, the whole book contains vocabulary of knowledge pointsiWhen the user browses the content, the similarity between the knowledge point vocabulary related to the user browsing content and the knowledge point vocabulary in the recommended book is high; recommending books to users when the knowledge points in the recommended books are larger than or equal to the knowledge points in the books turned over by the current users, and not recommending books, sim, to the users when detecting that the knowledge points in the recommended books are smaller than the knowledge points in the books turned over by the usersiThe standard similarity is the comparison of the knowledge points W contained in the front k pages read by the user and the whole knowledge points of the recommended books;
the two parts in the formula are grouped together to judge the content of the knowledge points, when books are recommended to a user, the similarity of judging whether the same knowledge point content is contained in the common pages needs to be calculated, the other part refers to the fact whether the knowledge point content contained in the recommended books in the same remaining pages is larger than the knowledge point content of the books selected by the user, and when the knowledge point content of the recommended book content is larger than the knowledge point content of the books selected by the user, the recommendation can be carried out.
Furthermore, through the book folding degree determining module, the time for the book borrowed by the user to enter the library is tiThe time when the borrowed book is borrowed is t0When t is detected0-ti>tkDuring the process, the folding degree of the current book is calculated, the folding degree is set to be Q, and the current book is subjected to photographing analysis:
according to the formula:
；
wherein:
refers to the smoothness of the surface of each page of the book,
refers to the degree of mildew on the surface of the book, F refers to the total number of pages of the book, m refers to the first page of the book, x refers to the total number of pages of the book, and FmRefers to any page in the book, QiThe standard folding degree of the book is referred to;
when Q is detected<QiWhen the book is checked, the book is checked to be out of the book;
when Q is detected>QiWhen the book is borrowed, the electronic book transmission module transmits the electronic file of the borrowed book to a user;
through formula Q, can judge the degree of mildening and rot of books, judge whether can outwards borrow books, wherein because books take place mildening and rot, because the time that books were preserved is longer, if borrow again many times can lead to books to produce the change.
Through the electronic book forwarding authority module, when a borrowed book is forwarded to other users, the information of the user is called through the user information pickup module, when the fact that the user is a first non-native school user and the borrowed book is a professional book set by a non-native school student is detected, when the fact that the non-native school student clicks the electronic book is detected, the number of times k and the stay time length are L, L = ak + b, a and b refer to function coefficients, and when L is detected, the fact that the borrowed book is clicked by the non-native school student is judged to be a professional book set by>LiThen, a fee D, D = D is collected for the electronic book contents to the first non-proof user0+r*d1,d0Is the fee charged for the trial content, d1The fee charged per page for the remaining contents, D the total fee, r the number of pages of the electronic book, LiWhich means the standard time for a non-native student staying in an electronic book.
Furthermore, the sharing times of the electronic books borrowed by the first non-native school user are limited through the electronic book forwarding permission module, and the number of pages read on the electronic books by the first non-native school user is detected in real time;
when detectingThe time length z for the first non-proof school user to click the number of pages of the electronic book is the last number of pages of the book and the first non-proof school user to stay at the last number of pages of the electronic book is detectedi>zkWhen z iskThe electronic book sharing method includes that a first non-native school user stays on a book at ordinary times for the average of the time length, the electronic book is shared with a second non-native school user to read, when the first non-native school user stops reading midway, the electronic book can be shared with the second non-native school user until the first non-native school user logs in again to read the electronic book, and the second non-native school user is interrupted to read the electronic book.
The system comprises the following steps:
z01, through the library book scheduling management module, the user searches the specific positions of the books in the library, judges whether the books are in the common library or the treasure library, simultaneously judges whether the number of the residual books of the books selected by the user is less than the preset number, and recommends similar books when the number of the books selected by the user is small;
z02: determining the interest degree of the user for the selected books when the number of the books of the user is less than the preset number through an interest degree time judging module, judging the preference degree of the user for the selected books, and recommending the books to the user;
z03: sending the book to a user for looking up through the electronic book or directly obtaining knowledge points through looking up the book by a book wrinkle degree determining module according to the wrinkle degree of the book;
z04: whether the current user is a student of the primary school or not is judged through the electronic book forwarding authority module and the electronic book chapter purchasing module, and when a non-primary school user is detected, the non-primary school user needs to purchase chapters so that the user can conveniently look up books.
Example 1: when a user borrows books in a library, the number of the remaining books can be displayed, when the number of the remaining books is detected to be less than the preset number, other books and related books of the books are recommended to the user, the content of the other books is different from the content of the books to be borrowed by the user, when the user is detected not to turn over the other books, the user is not influenced by the content of the interference books, the long-term interest value of the user is detected, the number of times that the books borrowed by the user are borrowed by a first student set is judged to be compared, whether the user borrows the data with class students is judged, when the matching is detected, the content of a knowledge point is recommended to the user to be larger than the content of a knowledge point of the books selected by the user, when the matching is detected, the user is interested in the second book for a long time, and the content of a second.
Example 2: the user search method can be classified into search by book name, search by professional book classification, and the like.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A big data based educational resource delivery system, characterized in that: the system comprises a library book scheduling management module, an intelligent recommendation module, a user information pickup module, a data comparison module, an interestingness time judgment module, an interference factor insertion module, a content relevance recommendation module, a standard correction module, a book folding degree determination module, an electronic book transmission module, an authority level online identification module, a partial interface remote sharing module, an electronic book forwarding authority module, a non-vpn channel sharing module, an electronic book chapter purchase module and an authority permission authentication module, wherein the library book scheduling management module is used for judging the specific position of a book required by a user and the residual quantity of books borrowed by the user according to the search record of the user in a library, the intelligent recommendation module is used for recommending the books to the user when the quantity of the books required by the user is not enough to borrow the user, and the resources of the residual books in the library are fully utilized, the system comprises a user information pickup module, a data comparison module, an interest degree time judgment module, an interference factor insertion module, a content relevance recommending module and a standard correction module, wherein the user information pickup module is used for picking up the professional and grade information of a book borrowing user, the data comparison module is used for comparing the knowledge points of books selected by the user with the knowledge points in recommended books to judge whether the books are similar books or not, the interest degree time judgment module is used for judging the interest degree of the user in the current books according to the book reading behavior of the user, the interference factor insertion module is used for recommending interference books irrelevant to the knowledge points in the books selected by the user to the user and judging whether the user is interfered by the interfered knowledge point books, the content relevance recommending module is used for recommending the similar books according to the knowledge point contents in the books selected by the user, and the standard correction module is used for recommending the books to the, the book folding degree determining module is used for judging the folding degree of the surface of a book when the book retrieved by a user exists in a treasure book base, the electronic book transmission module is used for lending the book selected by the user in an electronic book mode when the folding degree of the book is detected to be higher, the authority level online identifying module is used for judging whether the user is a student in the current school or not when the user browses the book through the electronic book, the partial interface remote sharing module is used for checking the identity of the user and providing the user with remote online reference of electronic book data, the electronic book forwarding authority module is used for checking the identity of the user and limiting the forwarding times of the electronic book when the user of the local school forwards the borrowed electronic book to other users, and the non-vpn channel sharing module is used for forbidding the non-user of the local school to obtain the electronic book of the book base through a vpn channel, the electronic book chapter purchasing module is used for looking up the contents of the book through purchasing the electronic chapters when the fact that the on-school users share the electronic book to the non-on-school users is detected.
2. A big data based educational resource delivery system according to claim 1, wherein: the interestingness time judging module is used for judging the time when the user selects a professional book to borrow and the time when other types of books recommend to borrow and the weight value for judging the short-term preference of the user for the book, and the time is recorded as yc, wherein the recommendation of other types of books is recommended books which are irrelevant to the content of a knowledge point of the book which is being read by the user;
according to the formula:
;
wherein: yc is the weight value of the book preferred by the user in a short term, c1 and c2 are the number of books borrowed by the user and the number of books recommended to the user respectively,
meaning the degree of influence a user borrows a book based on recommending the book to the user,
the influence degree of the user on book borrowing after the user recommends the book at a certain time is referred to, and n is the total number of times the book is consulted;
when the fact that the weight value of the book borrowed by the user is larger than the weight value of the book recommended to the user is detected, the fact that the preference degree of the user to the book in short time is high is shown; when detecting that the weight value of the book borrowed by the user is smaller than the weight value of the book recommended to the user, calculating the time for the user to see the book, and when detecting that yi-yk < ri-rk and repeatedly reading the user and selecting a professional book, indicating that the time for the user to check the recommended book is smaller than the time for the user to check the professional book and the short-term time of the user is influenced by other kinds of books; when the yi-yk > ri-rk is detected and the user does not select the professional book repeatedly by reading, the time for the user to view the recommended book is larger than the time for the user to view the professional book, and the preference degree of the user to select the professional book in the short-term time is low, wherein yi refers to the time period for the user to view the recommended book, yk refers to the time period for the user to view the recommended book, ri refers to the time period for the user to view the professional book, and rk refers to the time period for the user to view the professional book.
3. A big data based educational resource delivery system according to claim 1, wherein: judging the relevance between the professional book selected by the user and the professional learned by the user through a user information pickup module, wherein when the relevance is detected, the interest value S is reduced, and when the fact that the professional book selected by the user is not relevant to the professional learned by the user is detected, the interest value S is increased;
when the fact that the professional book selected by the user is not related to the professional book learned by the user is detected, the set of book borrowing times in the first student set and the same time period is W = { W1, W2, w3... wn }, wherein n refers to students, and when the judgment is made, the students pick up the professional book, the set of book borrowing times in the first student set and the same time period is
When the number of the average book addresses read by the students in the first student set is larger than the standard number, the interest value S of the current user in the professional books in a long time is reduced; when judging
When the number of the average book reading times of the students in the first student set is smaller than the standard number, the interest value S of the current user in the professional books in a long time is increased, and the professional books selected by the second student set are recommended to the user;
wherein S = S0+ Si, S0 denotes the initial interest value, Si denotes the fluctuating interest value, i denotes the first student, wi denotes any arbitraryThe number of times a book is borrowed by a student,
refers to the number of standard average borrowings;
the second student set refers to students with the same interest value range of the borrowed books as the user, and the first student set refers to students with the same class or the same repair specialty as the user.
4. A big data based educational resource delivery system according to claim 2, wherein: when a user reads the contents, the content relevancy recommending module takes the knowledge point related to the contents read by the user as W, takes the knowledge point contained in the recommended book as Y, collects the similar parts of the knowledge point W and the knowledge point Y and compares the similar parts, wherein sim is the similarity of the comparison between the knowledge point W contained in the front k pages read by the user and the whole knowledge point of the recommended book, and sim is calculated by adopting the following formula;
wherein, wiIs the word of the knowledge point in the page turned by the user, yiMeans that the recommended book turns over the knowledge point vocabulary in the i page, wjRefers to the word of the knowledge point in the page j turned by the user, yjThe method refers to that the recommended book reads knowledge point words in j pages and sets the page number y of the recommended bookj-yzContaining knowledge point vocabulary and the number of pages read by the useri-wkThe contained knowledge points are compared, yzMeans that when it is detected that sim is larger than sim, the whole book contains vocabulary of knowledge pointsiWhen the user browses the content, the similarity between the knowledge point vocabulary related to the user browsing content and the knowledge point vocabulary in the recommended book is high; recommending books to users when the knowledge points in the recommended books are more than or equal to the knowledge points in the books turned over by the current users, and not recommending the books to the users when detecting that the knowledge points in the recommended books are less than the knowledge points in the books turned over by the usersFamily recommends books, simiThe standard similarity is the comparison of the knowledge points W contained in the top k pages browsed by the user and the knowledge points of all recommended books.
5. A big data based educational resource delivery system according to claim 1, wherein: through the book folding degree determining module, the time for the book borrowed by the user to enter the library is tiThe time when the borrowed book is borrowed is t0When t is detected0-ti>tkDuring the process, the folding degree of the current book is calculated, the folding degree is set to be Q, and the current book is subjected to photographing analysis:
according to the formula:
；
wherein:
refers to the smoothness of the surface of each page of the book,
the mildew degree of the surface of the book is shown, and F is the total number of pages of the book;
when Q is detected<QiWhen the book is folded, the book can be borrowed, m is the first page of the book, x is the total number of pages of the book, fmRefers to any page in the book, QiThe standard folding degree of the book is referred to;
when Q is detected>QiAnd when the book is not borrowed, the electronic file of the borrowed book is sent to the user through the electronic book transmission module.
6. A big data based educational resource delivery system according to claim 5, wherein: through the electronic book forwarding authority module, when a borrowed book is forwarded to other users, the information of the user is called through the user information pickup module, when the fact that the user is a first non-native school user and the borrowed book is a professional book set by a non-native school student is detected, when the fact that the non-native school student clicks the electronic book is detected, the number of times k and the stay time length are L, L = ak + b, a and b refer to function coefficients, and when L is detected, the fact that the borrowed book is clicked by the non-native school student is judged to be a professional book set by>LiThen, a fee D, D = D is collected for the electronic book contents to the first non-proof user0+r*d1,d0Is the fee charged for the trial content, d1The fee charged per page for the remaining contents, D the total fee, r the number of pages of the electronic book, LiWhich means the standard time for a non-native student staying in an electronic book.
7. A big data based educational resource delivery system according to claim 6, wherein: the sharing times of the electronic books borrowed by the first non-native school user are limited through the electronic book forwarding permission module, and the number of pages read on the electronic books by the first non-native school user is detected in real time;
when detecting that the number of pages of the electronic book clicked by the first non-proof school user is the last number of pages of the book and detecting that the first non-proof school user stays at the last number of pages of the electronic book, the duration zi>zkWhen z iskThe electronic book sharing method includes that a first non-native school user stays on a book at ordinary times for the average of the time length, the electronic book is shared with a second non-native school user to read, when the first non-native school user stops reading midway, the electronic book can be shared with the second non-native school user until the first non-native school user logs in again to read the electronic book, and the second non-native school user is interrupted to read the electronic book.
8. A big data based educational resource delivery system according to claim 1, wherein: the system comprises the following steps:
z01, through the library book scheduling management module, the user searches the specific positions of the books in the library, judges whether the books are in the common library or the treasure library, simultaneously judges whether the number of the residual books of the books selected by the user is less than the preset number, and recommends similar books when the number of the books selected by the user is small;
z02: determining the interest degree of the user for the selected books when the number of the books of the user is less than the preset number through an interest degree time judging module, judging the preference degree of the user for the selected books, and recommending the books to the user;
z03: sending the book to a user for looking up through the electronic book or directly obtaining knowledge points through looking up the book by a book wrinkle degree determining module according to the wrinkle degree of the book;
z04: whether the current user is a student of the primary school or not is judged through the electronic book forwarding authority module and the electronic book chapter purchasing module, and when a non-primary school user is detected, the non-primary school user needs to purchase chapters so that the user can conveniently look up books.
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