CN116796039A - Intelligent library system - Google Patents

Abstract

The application relates to the technical field of intelligent book management, and discloses an intelligent library system, which comprises: the system comprises an acquisition module, a retrieval module, a query module and a recommendation module, wherein the acquisition module is used for determining book index words according to book retrieval instructions input by a user, generating internal index conditions according to the book index words, the retrieval module is used for retrieving in a book database according to the internal index conditions, sending retrieval results to a user side, the query module is used for receiving selection instructions returned by the user and inquiring books according to the selection instructions, the recommendation module is used for determining recommendation values of the book index words according to characteristic data of the user, and recommending books to the user based on the recommendation values when the book retrieval instructions input by the same user are received next time.

Description

Intelligent library system

Technical Field

The application relates to the technical field of intelligent book management, in particular to an intelligent library system.

Background

The society is an information explosion age today, and the desire for knowledge is also increasing, so libraries play an important role in this process. With the development of the times, books in libraries are more and more abundant, and books which can be selected by people according to the hobbies of people are more and more. However, problems have arisen. On the one hand, with the increase of library books, the efficiency of people searching for books becomes very low; on the other hand, the library is also subjected to huge pressure on the management of a large number of books in the library, and the existing book equipment cannot meet the demands of the masses.

The books are classified by classification numbers in the current libraries, readers can find books conveniently through a retrieval system, but after the books are more, the readers can find the retrieved books only by finding a plurality of bookshelf even if knowing the book searching numbers of the books, and the retrieval accuracy of the system is lower. And the current book search is conventional search of specified keywords, or a small-range search is performed according to guidance, so that the search speed is low, the range is small, and the library search efficiency is reduced.

Therefore, how to provide an intelligent library system capable of quickly searching a target book is a technical problem to be solved at present.

Disclosure of Invention

The embodiment of the application provides an intelligent library system, which is used for solving the technical problems that in the prior art, a target book cannot be quickly searched and the efficiency of searching the target book by a user cannot be improved.

To achieve the above object, the present application provides an intelligent library system comprising:

the acquisition module is used for acquiring a book retrieval instruction input by a user, obtaining book index words input by the user and generating internal index conditions according to the book index words;

the searching module is used for searching in the book database according to the internal index condition, generating a searching result and sending the searching result to the user side;

the inquiry module is used for receiving a selection instruction returned by a user and inquiring books according to the selection instruction;

and the recommending module is used for determining the recommending value of the book index word according to the characteristic data of the user, and recommending the book to the user based on the recommending value when the book index command input by the same user is received next time.

In one embodiment, the acquiring module is specifically configured to:

the acquisition module is used for carrying out text analysis on the book index words based on a preset text analysis rule and extracting key index words;

the acquisition module is used for cutting out a plurality of segmentation words from the key index words and generating internal retrieval conditions according to the plurality of segmentation words.

In one embodiment, the method further comprises:

and the filtering module is used for filtering the garbage words of the segmented words before the acquisition module generates the internal retrieval conditions according to the segmented words.

In one embodiment, the filtering module is specifically configured to:

the filtering module is used for traversing each word in a pre-constructed garbage word database, judging whether each word exists in the pre-constructed garbage word database,

if yes, deleting and filtering the corresponding segmented words;

if not, reserving the corresponding word segmentation.

In one embodiment, the retrieving module is specifically configured to:

the retrieval module is used for obtaining a first retrieval result corresponding to the key index word when retrieving in the book database according to the internal index condition;

the retrieval module is used for obtaining a plurality of keywords with similar meanings to the key index words and generating a second retrieval result according to the keywords with similar meanings to the key index words;

the search module is used for carrying out search display on the first search result and the second search result.

In one embodiment, the query module is specifically configured to:

the inquiry module is used for searching books in the library according to the selection instruction and judging whether the corresponding books exist in the library,

if yes, the storage position of the corresponding book is sent to a user side, and the user borrows the book based on the storage position;

if not, the relevant prompt is sent to the user side.

In one embodiment, the recommendation module is specifically configured to:

the recommendation module is used for acquiring historical retrieval times A of the user on the book index words;

the recommending module is used for setting the recommending value of the book index word according to the historical searching times A of the book index word.

In one embodiment, the recommendation module is specifically configured to:

the recommendation module is used for presetting a history retrieval frequency matrix B and setting B (B1, B2, B3 and B4), wherein B1 is first preset history retrieval frequency, B2 is second preset history retrieval frequency, B3 is third preset history retrieval frequency, B4 is fourth preset history retrieval frequency, and B1 is more than B2 and less than B3 and less than B4;

the recommendation module is used for presetting a recommendation value matrix C of book index words, and setting C (C1, C2, C3, C4 and C5), wherein C1 is a first preset recommendation value, C2 is a second preset recommendation value, C3 is a third preset recommendation value, C4 is a fourth preset recommendation value, C5 is a fifth preset recommendation value, and C1 is more than C2 and less than C3 and less than C4 and less than C5;

the recommendation module is further configured to set a recommendation value of the book index word according to a relationship between the historical search times a and each preset historical search time:

when A is smaller than B1, selecting the first preset recommended value C1 as the recommended value of the book index word;

when B1 is less than or equal to A and less than B2, selecting the second preset recommended value C2 as the recommended value of the book index word;

when B2 is less than or equal to A and less than B3, selecting the third preset recommended value C3 as the recommended value of the book index word;

when B3 is less than or equal to A and less than B4, selecting the fourth preset recommended value C4 as the recommended value of the book index word;

and when B4 is less than or equal to A, selecting the fifth preset recommended value C5 as the recommended value of the book index word.

In one embodiment, the recommendation module is specifically configured to:

the recommending module is used for acquiring historical borrowing times E of the book index words of the user;

the recommending module is used for correcting the recommended value of the book index word according to the historical borrowing times E of the book index word.

In one embodiment, the recommendation module is specifically configured to:

the recommendation module is used for presetting a history borrowing frequency matrix G and setting G (G1, G2, G3 and G4), wherein G1 is a first preset history borrowing frequency, G2 is a second preset history borrowing frequency, G3 is a third preset history borrowing frequency, G4 is a fourth preset history borrowing frequency, and G1 is more than G2 and less than G3 and less than G4;

the recommendation module is used for presetting a recommendation value correction coefficient matrix h of book index words, setting h (h 1, h2, h3, h4 and h 5), wherein h1 is a first preset recommendation value correction coefficient, h2 is a second preset recommendation value correction coefficient, h3 is a third preset recommendation value correction coefficient, h4 is a fourth preset recommendation value correction coefficient, h5 is a fifth preset recommendation value correction coefficient, and h1 is more than 0.8 and less than h2, h3 is more than h4 and less than h5 and less than 1.2;

the recommendation module is further configured to, when setting the recommendation value of the book index word as an i-th preset recommendation value Ci, correct the recommendation value Ci of the book index word according to the relation between the history borrowing times E and each preset history borrowing time, wherein i=1, 2,3,4, 5:

when E is smaller than G1, the first preset recommended value correction coefficient h1 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h1;

when G1 is less than or equal to E and less than G2, selecting the second preset recommended value correction coefficient h2 to correct the ith preset recommended value Ci, wherein the corrected recommended value of the book index word is Ci x h2;

when G2 is less than or equal to E and less than G3, selecting the third preset recommended value correction coefficient h3 to correct the ith preset recommended value Ci, wherein the recommended value of the corrected book index word is Ci x h3;

when G3 is less than or equal to E and less than G4, the fourth preset recommended value correction coefficient h4 is selected to correct the ith preset recommended value Ci, and the recommended value of the corrected book index word is Ci x h4;

when G4 is less than or equal to E, the fifth preset recommended value correction coefficient h5 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h5.

The application provides an intelligent library system, which has the following beneficial effects compared with the prior art:

the application discloses an intelligent library system, which comprises: the system comprises an acquisition module, a retrieval module, a query module and a recommendation module, wherein the acquisition module is used for determining book index words according to book retrieval instructions input by a user, generating internal index conditions according to the book index words, the retrieval module is used for retrieving in a book database according to the internal index conditions, sending retrieval results to a user side, the query module is used for receiving selection instructions returned by the user and inquiring books according to the selection instructions, the recommendation module is used for determining recommendation values of the book index words according to characteristic data of the user, and recommending books to the user based on the recommendation values when the book retrieval instructions input by the same user are received next time.

Drawings

FIG. 1 shows a schematic diagram of a smart library system in accordance with an embodiment of the present application.

Detailed Description

The following describes in further detail the embodiments of the present application with reference to the drawings and examples. The following examples are illustrative of the application and are not intended to limit the scope of the application.

In the description of the present application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.

The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.

In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.

The following is a description of preferred embodiments of the application, taken in conjunction with the accompanying drawings.

As shown in fig. 1, an embodiment of the present application discloses an intelligent library system, comprising:

the acquisition module is used for acquiring a book retrieval instruction input by a user, obtaining book index words input by the user and generating internal index conditions according to the book index words;

the searching module is used for searching in the book database according to the internal index condition, generating a searching result and sending the searching result to the user side;

the inquiry module is used for receiving a selection instruction returned by a user and inquiring books according to the selection instruction;

and the recommending module is used for determining the recommending value of the book index word according to the characteristic data of the user, and recommending the book to the user based on the recommending value when the book index command input by the same user is received next time.

In the embodiment, the method and the device solve the technical problem that the target books cannot be quickly searched, and can improve the target book inquiring efficiency when the user searches the books next time by determining the recommended value of the book index words.

In some embodiments of the present application, the obtaining module is specifically configured to:

the acquisition module is used for carrying out text analysis on the book index words based on a preset text analysis rule and extracting key index words;

the acquisition module is used for cutting out a plurality of segmentation words from the key index words and generating internal retrieval conditions according to the plurality of segmentation words.

In this embodiment, when a book index word is obtained, text analysis is performed on the book index word, a key index word is extracted, for example, a user inputs "how to improve cooking level", the key word is "cooking" and "level", a plurality of segmentation words are cut out from the key index word, for example, "cooking" and "meal" are cut out, and search conditions are generated according to the segmentation words.

In some embodiments of the application, further comprising:

and the filtering module is used for filtering the garbage words of the segmented words before the acquisition module generates the internal retrieval conditions according to the segmented words.

The filter module is specifically used for:

the filtering module is used for traversing each word in a pre-constructed garbage word database, judging whether each word exists in the pre-constructed garbage word database,

if yes, deleting and filtering the corresponding segmented words;

if not, reserving the corresponding word segmentation.

In this embodiment, when generating a plurality of word segments, some garbage words may exist, such as "yellow-related", "administrative-related", "riot-related", etc., and these word segments are deleted and filtered, so as to avoid that these word segments affect the normal search result.

In some embodiments of the present application, the retrieval module is specifically configured to:

the retrieval module is used for obtaining a first retrieval result corresponding to the key index word when retrieving in the book database according to the internal index condition;

the retrieval module is used for obtaining a plurality of keywords with similar meanings to the key index words and generating a second retrieval result according to the keywords with similar meanings to the key index words;

the search module is used for carrying out search display on the first search result and the second search result.

In this embodiment, when searching is performed in the book database according to the internal index condition, a first search result corresponding to the key index word is obtained, for example, a related book is obtained according to "cooking", for example, how the book improves its own cooking skill ", a plurality of keywords having similar meanings to the key index word are placed in a group, a similar threshold is set between the keywords, when one keyword in a group is searched, each keyword in the group is searched, for example, a plurality of keywords having similar meanings are obtained according to" cooking ", for example," cooking "," cooking soup "," recipe "and the like, and the book corresponding to the plurality of keywords is used as a second search result, for example," Chinese recipe "and the like.

In some embodiments of the present application, the query module is specifically configured to:

the inquiry module is used for searching books in the library according to the selection instruction and judging whether the corresponding books exist in the library,

if yes, the storage position of the corresponding book is sent to a user side, and the user borrows the book based on the storage position;

if not, the relevant prompt is sent to the user side.

In this embodiment, the book searching processing is performed in the library according to the selection instruction, for example, the user selects the book "Chinese recipe", and when the corresponding book exists in the library, the position of the book "Chinese recipe" is directly sent to the user, for example, the third row and the fourth row, and if not, the relevant prompt of insufficient inventory is sent to the user side, and other books are recommended to the user.

In some embodiments of the present application, the recommendation module is specifically configured to:

the recommendation module is used for acquiring historical retrieval times A of the user on the book index words;

the recommending module is used for setting the recommending value of the book index word according to the historical searching times A of the book index word.

In some embodiments of the present application, the recommendation module is specifically configured to:

the recommendation module is used for presetting a history retrieval frequency matrix B and setting B (B1, B2, B3 and B4), wherein B1 is first preset history retrieval frequency, B2 is second preset history retrieval frequency, B3 is third preset history retrieval frequency, B4 is fourth preset history retrieval frequency, and B1 is more than B2 and less than B3 and less than B4;

the recommendation module is used for presetting a recommendation value matrix C of book index words, and setting C (C1, C2, C3, C4 and C5), wherein C1 is a first preset recommendation value, C2 is a second preset recommendation value, C3 is a third preset recommendation value, C4 is a fourth preset recommendation value, C5 is a fifth preset recommendation value, and C1 is more than C2 and less than C3 and less than C4 and less than C5;

the recommendation module is further configured to set a recommendation value of the book index word according to a relationship between the historical search times a and each preset historical search time:

when A is smaller than B1, selecting the first preset recommended value C1 as the recommended value of the book index word;

when B1 is less than or equal to A and less than B2, selecting the second preset recommended value C2 as the recommended value of the book index word;

when B2 is less than or equal to A and less than B3, selecting the third preset recommended value C3 as the recommended value of the book index word;

when B3 is less than or equal to A and less than B4, selecting the fourth preset recommended value C4 as the recommended value of the book index word;

and when B4 is less than or equal to A, selecting the fifth preset recommended value C5 as the recommended value of the book index word.

In the embodiment, the historical search times A of the user for the book index words are obtained, and the recommended value of the book index words is set according to the relation between the historical search times A and each preset historical search time.

In some embodiments of the present application, the recommendation module is specifically configured to:

the recommending module is used for acquiring historical borrowing times E of the book index words of the user;

the recommending module is used for correcting the recommended value of the book index word according to the historical borrowing times E of the book index word.

The recommendation module is specifically configured to:

the recommendation module is used for presetting a history borrowing frequency matrix G and setting G (G1, G2, G3 and G4), wherein G1 is a first preset history borrowing frequency, G2 is a second preset history borrowing frequency, G3 is a third preset history borrowing frequency, G4 is a fourth preset history borrowing frequency, and G1 is more than G2 and less than G3 and less than G4;

the recommendation module is used for presetting a recommendation value correction coefficient matrix h of book index words, setting h (h 1, h2, h3, h4 and h 5), wherein h1 is a first preset recommendation value correction coefficient, h2 is a second preset recommendation value correction coefficient, h3 is a third preset recommendation value correction coefficient, h4 is a fourth preset recommendation value correction coefficient, h5 is a fifth preset recommendation value correction coefficient, and h1 is more than 0.8 and less than h2, h3 is more than h4 and less than h5 and less than 1.2;

the recommendation module is further configured to, when setting the recommendation value of the book index word as an i-th preset recommendation value Ci, correct the recommendation value Ci of the book index word according to the relation between the history borrowing times E and each preset history borrowing time, wherein i=1, 2,3,4, 5:

when E is smaller than G1, the first preset recommended value correction coefficient h1 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h1;

when G1 is less than or equal to E and less than G2, selecting the second preset recommended value correction coefficient h2 to correct the ith preset recommended value Ci, wherein the corrected recommended value of the book index word is Ci x h2;

when G2 is less than or equal to E and less than G3, selecting the third preset recommended value correction coefficient h3 to correct the ith preset recommended value Ci, wherein the recommended value of the corrected book index word is Ci x h3;

when G3 is less than or equal to E and less than G4, the fourth preset recommended value correction coefficient h4 is selected to correct the ith preset recommended value Ci, and the recommended value of the corrected book index word is Ci x h4;

when G4 is less than or equal to E, the fifth preset recommended value correction coefficient h5 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h5.

In this embodiment, when the recommendation module sets the recommendation value of the book index word as the i-th preset recommendation value Ci, i=1, 2,3,4,5, and is further configured to correct the recommendation value Ci of the book index word according to the relationship between the history borrowing times E and each preset history borrowing times.

In summary, an embodiment of the present application includes: the system comprises an acquisition module, a retrieval module, a query module and a recommendation module, wherein the acquisition module is used for determining book index words according to book retrieval instructions input by a user, generating internal index conditions according to the book index words, the retrieval module is used for retrieving in a book database according to the internal index conditions, sending retrieval results to a user side, the query module is used for receiving selection instructions returned by the user and inquiring books according to the selection instructions, the recommendation module is used for determining recommendation values of the book index words according to characteristic data of the user, and recommending books to the user based on the recommendation values when the book retrieval instructions input by the same user are received next time.

In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.

Although the application has been described hereinabove with reference to embodiments, various modifications thereof may be made and equivalents may be substituted for elements thereof without departing from the scope of the application. In particular, the features of the disclosed embodiments may be combined with each other in any manner as long as there is no structural conflict, and the entire description of these combinations is not made in the present specification merely for the sake of omitting the descriptions and saving resources. Therefore, it is intended that the application not be limited to the particular embodiment disclosed, but that the application will include all embodiments falling within the scope of the appended claims.

Those of ordinary skill in the art will appreciate that: the above is only a preferred embodiment of the present application, and the present application is not limited thereto, but it is to be understood that the present application is described in detail with reference to the foregoing embodiments, and modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims (10)

1. An intelligent library system, comprising:

the acquisition module is used for acquiring a book retrieval instruction input by a user, obtaining book index words input by the user and generating internal index conditions according to the book index words;

the searching module is used for searching in the book database according to the internal index condition, generating a searching result and sending the searching result to the user side;

the inquiry module is used for receiving a selection instruction returned by a user and inquiring books according to the selection instruction;

and the recommending module is used for determining the recommending value of the book index word according to the characteristic data of the user, and recommending the book to the user based on the recommending value when the book index command input by the same user is received next time.

2. The intelligent library system according to claim 1, wherein the acquisition module is specifically configured to:

the acquisition module is used for carrying out text analysis on the book index words based on a preset text analysis rule and extracting key index words;

the acquisition module is used for cutting out a plurality of segmentation words from the key index words and generating internal retrieval conditions according to the plurality of segmentation words.

3. The intelligent library system according to claim 2, further comprising:

and the filtering module is used for filtering the garbage words of the segmented words before the acquisition module generates the internal retrieval conditions according to the segmented words.

4. The intelligent library system according to claim 3, wherein the filtering module is specifically configured to:

the filtering module is used for traversing each word in a pre-constructed garbage word database, judging whether each word exists in the pre-constructed garbage word database,

if yes, deleting and filtering the corresponding segmented words;

if not, reserving the corresponding word segmentation.

5. The intelligent library system according to claim 2, wherein the retrieval module is specifically configured to:

the retrieval module is used for obtaining a first retrieval result corresponding to the key index word when retrieving in the book database according to the internal index condition;

the retrieval module is used for obtaining a plurality of keywords with similar meanings to the key index words and generating a second retrieval result according to the keywords with similar meanings to the key index words;

the search module is used for carrying out search display on the first search result and the second search result.

6. The intelligent library system according to claim 1, wherein the query module is specifically configured to:

the inquiry module is used for searching books in the library according to the selection instruction and judging whether the corresponding books exist in the library,

if yes, the storage position of the corresponding book is sent to a user side, and the user borrows the book based on the storage position;

if not, the relevant prompt is sent to the user side.

7. The intelligent library system according to claim 1, wherein the recommendation module is specifically configured to:

the recommendation module is used for acquiring historical retrieval times A of the user on the book index words;

the recommending module is used for setting the recommending value of the book index word according to the historical searching times A of the book index word.

8. The intelligent library system according to claim 7, wherein the recommendation module is specifically configured to:

the recommendation module is used for presetting a history retrieval frequency matrix B and setting B (B1, B2, B3 and B4), wherein B1 is first preset history retrieval frequency, B2 is second preset history retrieval frequency, B3 is third preset history retrieval frequency, B4 is fourth preset history retrieval frequency, and B1 is more than B2 and less than B3 and less than B4;

the recommendation module is used for presetting a recommendation value matrix C of book index words, and setting C (C1, C2, C3, C4 and C5), wherein C1 is a first preset recommendation value, C2 is a second preset recommendation value, C3 is a third preset recommendation value, C4 is a fourth preset recommendation value, C5 is a fifth preset recommendation value, and C1 is more than C2 and less than C3 and less than C4 and less than C5;

the recommendation module is further configured to set a recommendation value of the book index word according to a relationship between the historical search times a and each preset historical search time:

when A is smaller than B1, selecting the first preset recommended value C1 as the recommended value of the book index word;

when B1 is less than or equal to A and less than B2, selecting the second preset recommended value C2 as the recommended value of the book index word;

when B2 is less than or equal to A and less than B3, selecting the third preset recommended value C3 as the recommended value of the book index word;

when B3 is less than or equal to A and less than B4, selecting the fourth preset recommended value C4 as the recommended value of the book index word;

and when B4 is less than or equal to A, selecting the fifth preset recommended value C5 as the recommended value of the book index word.

9. The intelligent library system according to claim 8, wherein the recommendation module is specifically configured to:

the recommending module is used for acquiring historical borrowing times E of the book index words of the user;

the recommending module is used for correcting the recommended value of the book index word according to the historical borrowing times E of the book index word.

10. The intelligent library system according to claim 9, wherein the recommendation module is specifically configured to:

the recommendation module is used for presetting a history borrowing frequency matrix G and setting G (G1, G2, G3 and G4), wherein G1 is a first preset history borrowing frequency, G2 is a second preset history borrowing frequency, G3 is a third preset history borrowing frequency, G4 is a fourth preset history borrowing frequency, and G1 is more than G2 and less than G3 and less than G4;

the recommendation module is used for presetting a recommendation value correction coefficient matrix h of book index words, setting h (h 1, h2, h3, h4 and h 5), wherein h1 is a first preset recommendation value correction coefficient, h2 is a second preset recommendation value correction coefficient, h3 is a third preset recommendation value correction coefficient, h4 is a fourth preset recommendation value correction coefficient, h5 is a fifth preset recommendation value correction coefficient, and h1 is more than 0.8 and less than h2, h3 is more than h4 and less than h5 and less than 1.2;

the recommendation module is further configured to, when setting the recommendation value of the book index word as an i-th preset recommendation value Ci, correct the recommendation value Ci of the book index word according to the relation between the history borrowing times E and each preset history borrowing time, wherein i=1, 2,3,4, 5:

when E is smaller than G1, the first preset recommended value correction coefficient h1 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h1;

when G1 is less than or equal to E and less than G2, selecting the second preset recommended value correction coefficient h2 to correct the ith preset recommended value Ci, wherein the corrected recommended value of the book index word is Ci x h2;

when G2 is less than or equal to E and less than G3, selecting the third preset recommended value correction coefficient h3 to correct the ith preset recommended value Ci, wherein the recommended value of the corrected book index word is Ci x h3;

when G3 is less than or equal to E and less than G4, the fourth preset recommended value correction coefficient h4 is selected to correct the ith preset recommended value Ci, and the recommended value of the corrected book index word is Ci x h4;

when G4 is less than or equal to E, the fifth preset recommended value correction coefficient h5 is selected to correct the ith preset recommended value Ci, and the corrected recommended value of the book index word is Ci x h5.