CN108108447B

CN108108447B - Electronic thumbnail generation method, electronic device and computer storage medium

Info

Publication number: CN108108447B
Application number: CN201711447391.1A
Authority: CN
Inventors: 郑志伟; 车红茜; 张倩; 孔鹏; 杨喜娜; 索珊珊
Original assignee: Ireader Technology Co Ltd
Current assignee: Shenzhen Zhangyue Animation Technology Co ltd
Priority date: 2017-12-27
Filing date: 2017-12-27
Publication date: 2020-12-08
Anticipated expiration: 2037-12-27
Also published as: CN108108447A

Abstract

The invention discloses an electronic thumbnail generation method, electronic equipment and a computer storage medium. The method comprises the following steps: determining each word contained in the electronic book and the part of speech of each word; determining a target abbreviation rule according to user operation; and deleting the words contained in the electronic book according to the part of speech of the words contained in the electronic book by adopting the target abbreviation rule to obtain the abbreviation book. The method has the advantages that the thumbnail generation mode of automatically deleting words is realized without influencing the original text understanding, the original text information quantity and the reading smoothness or little influence, the later manual intervention is not needed, the labor cost investment is saved, and the thumbnail generation efficiency is improved; meanwhile, different users can select the thumbnail with proper length at fine granularity according to time arrangement in different scenes, and the electronic thumbnail meeting the user requirements is generated at any time and any place according to the selection for reading, so that the reading experience of the users is improved.

Description

Electronic thumbnail generation method, electronic device and computer storage medium

Technical Field

The invention relates to the technical field of computers, in particular to an electronic thumbnail generation method, electronic equipment and a computer storage medium.

Background

With the pace of modern life acceleration, more and more people cannot spend a lot of time reading hundreds of thousands of words of electronic books, and choose to read valuable information extracted from the books in a short time.

Currently, the refinement of the content of the electronic book includes two ways: one is that the speaker finishes speaking the content in a book in a short time, for example, ten minutes, by means of video or audio recording; the second is to concentrate the e-book into a thumbnail book that the user can read only in different time such as half an hour or an hour in the form of characters, such as known one-hour reading items, cheese reading, latte reading, and the like.

However, in the prior art, the contents in the books are summarized, summarized and refined in a later-stage artificial mode, so that the refined contents of the books are integrated with the thought of a refiner, the subjectivity is high, and the understanding of the user himself on the contents of the books is influenced. In addition, because the manual extraction mode has high time consumption and high labor cost, only one version of the extracted thumbnail book of one book is available, different users cannot select the thumbnail book with proper length at fine granularity according to the time arrangement in different scenes, and the reading experience of the users is reduced.

Disclosure of Invention

In view of the above, the present invention has been made to provide an electronic thumbnail generation method, an electronic device, and a computer storage medium that overcome or at least partially solve the above-mentioned problems.

According to an aspect of the present invention, there is provided an electronic thumbnail generating method for providing an electronic thumbnail meeting a user's demand to a user, the method including: determining each word contained in the electronic book and the part of speech of each word; determining a target abbreviation rule according to user operation; and deleting the words contained in the electronic book according to the part of speech of the words contained in the electronic book by adopting the target abbreviation rule to obtain the abbreviation book.

According to another aspect of the present invention, there is provided an electronic apparatus including: the processor, the memory and the communication interface complete mutual communication through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the following operations: determining each word contained in the electronic book and the part of speech of each word; determining a target abbreviation rule according to user operation; and deleting the words contained in the electronic book according to the part of speech of the words contained in the electronic book by adopting the target abbreviation rule to obtain the abbreviation book.

According to yet another aspect of the present invention, there is provided a computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to: determining each word contained in the electronic book and the part of speech of each word; determining a target abbreviation rule according to user operation; and deleting the words contained in the electronic book according to the part of speech of the words contained in the electronic book by adopting the target abbreviation rule to obtain the abbreviation book.

According to the electronic thumbnail generation method, the electronic equipment and the computer storage medium, an automatic electronic thumbnail generation mode is provided, and the thumbnail can be obtained by automatically deleting each word contained in the electronic book by adopting a specified target thumbnail rule according to each word and part of speech in the electronic book. The method has the advantages that the thumbnail generation mode of automatically deleting words is realized without influencing the original text understanding, the original text information quantity and the reading smoothness or little influence, the later manual intervention is not needed, the labor cost investment is saved, and the thumbnail generation efficiency is improved; meanwhile, different users can select the thumbnail with proper length at fine granularity according to time arrangement in different scenes, and the electronic thumbnail meeting the user requirements is generated at any time and any place according to the selection for reading, so that the reading experience of the users is improved.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 is a flow chart of a method for generating an electronic thumbnail according to an embodiment of the present invention;

FIG. 2 is a flow chart of an electronic thumbnail generation method provided by a second embodiment of the present invention;

FIG. 3 is a flowchart illustrating an example of determining ebook content to which a target thumbnail rule is applicable according to a third embodiment of the present invention;

fig. 4 shows a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Example one

Fig. 1 shows a flowchart of an electronic thumbnail generation method provided in an embodiment of the present invention, which is used for automatically generating an electronic thumbnail according to a user requirement. As shown in fig. 1, the method comprises the steps of:

step S101, determining each word contained in the electronic book and the part of speech of each word.

In the present invention, the electronic book refers to a publication that can be looked up from a reader integrating storage and display terminals, in which information contents such as digitized characters, pictures, sounds, images, etc. are implanted or downloaded, and digitize the information contents such as characters, pictures, sounds, images, etc. In this embodiment, the electronic book mainly refers to a digital publication that displays a book in the form of characters or pictures. Because an electronic book is a digitized publication corresponding to a paper book, and a digitized book published or issued on a network, and other word expressions, the electronic book is mainly composed of tens of thousands of words. Correspondingly, the first step of generating the electronic thumbnail book is to perform word segmentation on the content in the electronic book, divide the complete content of the electronic book into tens of thousands of words which independently exist, further obtain all the words in the electronic book, and perform part-of-speech analysis on each word.

Specifically, the part of speech refers to the characteristic of a word as a basis for dividing the part of speech. Modern chinese words can be divided into two classes of 14 parts of speech. From the perspective of combinatorial and aggregate relationships, a part of speech refers to: in a language, a plurality of words having the same syntactic function that can appear in the same combined position are grouped together to form a category. The part-of-speech classification of modern chinese words includes two classes, real words and imaginary words. A real word is a word that contains actual meaning in the word and can be used alone as a sentence component, i.e., a word with lexical and grammatical meaning. The term "null" is used broadly to mean a word that has no complete meaning, but is a word that has grammatical meaning or function, and must be attached to a real word or sentence to express grammatical meaning, but cannot be formulated alone and cannot be formulated alone as a grammatical component. Wherein the real words further include: the noun, verb, adjective, distinguishment word, pronoun, number word and quantifier are seven kinds of real word parts of speech, and the virtual word further comprises: paraphrases, prepositions, conjunctions, auxiliary words, moods, words, pseudonyms and sighs are seven kinds of fictional characters. For example, adverbs refer to words representing behavior or state characteristics in a sentence, and are used to modify verbs, adjectives, other adverbs, or the whole sentence, to represent concepts such as time, place, degree, manner, and so on, so that the adverbs can be divided into: degree adverb, range adverb, time/frequency adverb, positive adverb, negative adverb, emotional/style adverb, tone adverb, place adverb, and the like.

In this step, a part-of-speech tagging method may be adopted to identify and tag the part of speech of each word in the electronic book. Part-of-speech tagging, also known as part-of-speech tagging or tagging for short, refers to a procedure for tagging each word in the segmentation result with a correct part-of-speech, i.e., a process for determining the specific part-of-speech of each word. For example, a hidden markov model may be used to train a part-of-speech tagging model, so as to automatically identify and tag the part-of-speech of each word in the electronic book.

Illustratively, for a complete sentence "teaching a natural language processing course" the words and parts of speech of the words are determined. Firstly, the sentence is subjected to word segmentation, and the word segmentation result is obtained as follows: "professor", "on", "professor", "natural language", "process", and "lesson" are six words. Secondly, part-of-speech tagging is carried out on the word segmentation result, and the tagging result can be obtained as follows: the first word "teach" is a noun, the word "being" is an adverb, the second word "teach" is a verb, the word "natural language" is a noun, the word "processing" is a noun, and the word "course" is a noun.

Step S102, determining a target abbreviating rule according to user operation.

In the invention, the user can operate the e-book interface according to the requirements of own time arrangement, preference and the like, for example, the length of the space is the proportional value of the original text, the reduction level of the space, the reduction range, the specific reduction degree of a certain part of content is designated, and the full text or part of content is designated to restore the original text. The user can set the degree of deletion by manually inputting parameters in a specified dialog box of the interface, and can also adjust the degree of deletion by dragging a number axis, such as a proportion axis, on the interface, so as to specifically define the presentation form of the electronic book according to the specific requirements of the user.

In this step, the importance of each word in the text can be determined according to the part of speech of each word in the electronic book. According to the importance degree of each word, unimportant words in the book are removed, and the purpose of shortening the word number of the book is achieved. The unimportant words refer to words which do not influence the original text understanding or have little influence on the original text understanding after being eliminated, do not influence the reading smoothness or have little influence on the smoothness after being eliminated, and do not lose the original text information quantity or have little information quantity loss after being eliminated. In addition, the types and numbers of words selected for culling may vary for different length thumbnails. Theoretically, the shorter the length of the text, the larger the types and the number of the words removed from the thumbnail, the larger the loss of the original text semantics. This semantic loss is inevitable when looking at the reduction of the number of text levels. Therefore, when the electronic book is reduced, a trade-off should be made between the original electronic book reduction degree and the reading time of the user corresponding to the thumbnail book according to the user's requirement, so as to provide the user with the electronic thumbnail book that conforms to the original meaning as much as possible under the condition of completing the space reduction.

Specifically, after the words with different parts of speech are removed, the degree of semantic loss of the original text is different. For example, the effect of adjective rejection is less than the effect of pronouns being kicked away, which is less than the effect of conjunctions being kicked away. Therefore, different word reduction rules can be formulated for different degrees of abbreviation and parts of speech of each word, so as to clarify the target abbreviation rules of the whole or part of the target content of the electronic book.

Illustratively, thumbnails of different length versions are made for the e-book. For example, if the length of the thumbnail book is four levels of 90%, 70%, 60% and 40% of the length of the original text, the reading time of the thumbnail book is about 9 hours, 7 hours, 6 hours and 4 hours, assuming that about 10 hours are required for reading the original text. When a user reads the electronic book of the book, an Application program (APP) displays options of four levels through a selection interface, and gives reading time length and character number corresponding to each level for the user to refer and select. Assuming that the thumbnail with the space length of 90% of the original text length is generated, since the reserved space length is long, only the word corresponding to the part of speech with the least influence on the entire text may be deleted, for example, it may be formulated to delete only the adjective in the electronic book, so as to clarify the thumbnail rule for the thumbnail with the space length of 90% of the original text length.

Step S103, deleting each word contained in the electronic book according to the part of speech of each word contained in the electronic book by adopting the target abbreviation rule to obtain an abbreviation.

In this step, according to the word segmentation result of the electronic book, the part of speech of each word and the determined target abbreviation rule in the above steps, the word contained in the electronic book can be deleted according to the abbreviation rule to obtain the abbreviation book.

Specifically, a designated abbreviation rule can be adopted to perform uniform deletion processing on the full text; in the deletion result obtained by performing the deletion process once on the full text, the deletion process may be performed twice on the specified paragraph or chapter. Since the beginning chapter and the ending chapter of a book are often of great importance in terms of plot, the beginning chapter and the ending chapter are not deleted as much as possible in order to reduce the influence of the deletion processing on the electronic book. After the front chapters and the end chapters are avoided, continuous chapters can be randomly selected from all the chapters to carry out secondary deletion processing, and the influence on the fluency of reading the electronic book caused by frequent change of the reduction degree in the whole text is avoided. In addition, statistics can be carried out according to information such as times of publishing ideas, comments, leaving messages and sharing of the users in the whole network, the hot sections of the book are determined, the sections are used as key sections, original information of the sections is reserved as much as possible, and further secondary deletion processing is not carried out. Therefore, it is possible to select a plurality of chapters from among the non-top chapters that avoid the top chapters and perform the second deletion process. Although this approach does not guarantee that the selected chapters are consecutive, it is permissible to perform secondary deletion processing on non-consecutive chapters that do not contain key information in order to make a concession as to retain key information as much as possible. It should be noted that the first and second subtraction processes preferably select the contraction rules of adjacent contraction degrees, so as to avoid that the difference of contraction degrees is too large, so that the user feels that the contents of some chapters are relatively detailed, and the contents of some chapters are too omitted, thereby affecting the reading feeling of the user.

According to the electronic thumbnail generation method provided by the embodiment, the electronic thumbnail can be automatically generated according to the requirements of the user. Firstly, determining all words and parts of speech of each word in the electronic book according to the content in the electronic book; secondly, determining a target abbreviation rule for deleting each word in the electronic book according to the requirement of a user; finally, a designated target abbreviation rule is adopted, all words and parts of speech of all words in the electronic book are used, and corresponding deletion processing is automatically carried out on all words contained in the electronic book, so that the electronic abbreviation book meeting the requirements of users is obtained. The electronic thumbnail generation method can be used for automatically generating the electronic thumbnail according to the user requirement and providing the electronic thumbnail meeting the user requirement for the user. The method has the advantages that the thumbnail generation mode of automatically deleting words is realized without influencing the original text understanding, the original text information quantity and the reading smoothness or little influence, the later manual intervention is not needed, the labor cost investment is saved, and the thumbnail generation efficiency is improved; meanwhile, different users can select the thumbnail with proper length at fine granularity according to time arrangement in different scenes, and the electronic thumbnail meeting the user requirements is generated at any time and any place according to the selection for reading, so that the reading experience of the users is improved.

Example two

Fig. 2 shows a flowchart of an electronic thumbnail generation method provided by the second embodiment of the present invention. The embodiment is applied to a scene for automatically generating an electronic thumbnail according to the requirement of a user, and as shown in fig. 2, the method includes:

step S201, performing word segmentation on the electronic book to obtain words contained in the electronic book.

In this step, word segmentation means that a Chinese character sequence is segmented into a single word. The complete e-book content is divided into tens of thousands of independent words, so that all the words in the e-book are obtained, and each word is analyzed. For example, for a complete sentence "teaching a natural language processing course", performing word segmentation processing on the sentence, the word segmentation result may be: "professor", "on", "professor", "natural language", "process", and "lesson" are six words. Although words that are literally the same are included, their specific meanings may be completely different, and thus it is necessary to analyze the parts of speech of the respective words in the word segmentation result.

Step S202, performing part-of-speech tagging on each word contained in the electronic book according to a part-of-speech tagging model generated in advance based on hidden Markov model training.

In this step, part-of-speech tagging refers to a procedure for tagging each word in the word segmentation result with a correct part-of-speech, i.e., a process for determining a specific part-of-speech of each word. In this embodiment, a hidden markov model may be used to train the part-of-speech tagging model based on the corpus, the part-of-speech set, and the part-of-speech frequency statistics. A corpus can be created by collecting a large number of articles and books, or a corpus summarized by predecessors can be adopted, for example, the corpus is segmented in the 2014 daily newspaper; the part of speech set can be selected from part of speech sets such as 'ICTPOS 3.0 Chinese part of speech tagging set' or 'modern Chinese language material bank processing specification-word segmentation and part of speech tagging', and each part of speech set can be directly adopted, or can be summarized and supplemented to obtain a more complete part of speech set; the core dictionary word frequency can be obtained by the word part-of-speech frequency dictionary. Finally, the part-of-speech tagging is carried out on each word contained in the electronic book by utilizing the trained part-of-speech tagging model.

Illustratively, in the above example, the word segmentation process is performed on a complete sentence "teaching a natural language processing course", and the word segmentation result is obtained as follows: "professor", "on", "professor", "natural language", "process", and "lesson" are six words. And performing part-of-speech tagging on each word in the segmentation result by using a part-of-speech tagging model generated based on hidden Markov model training to obtain part-of-speech tagging results such as 'professor/nnt, now/d, professor/v, natural language/gm, process/vn and course/n'. According to the labels of various types of words in part of speech sets, a first teaching word can be determined as a professional title or a noun, a second teaching word can be determined as an adverb, a second teaching word can be determined as a verb, a natural language word can be determined as a mathematically related word or a noun, a processing word can be determined as a noun or a verb, and a course word can be determined as a noun.

In step S203, a target thumbnail level is determined according to a user operation.

In the invention, different levels can be formulated for the abbreviation of the electronic book, so that a user can intuitively select the abbreviation level corresponding to the abbreviation degree meeting the self requirement. The present embodiment may make four candidate thumbnail levels for the thumbnail of the electronic book, where the first candidate thumbnail level has the lowest degree of reduction and the fourth candidate thumbnail level has the highest degree of reduction. For example, from the first candidate thumbnail level to the fourth candidate thumbnail level, the length of the electronic book is reduced to about 90%, about 70%, in the interval of 50% to 60% and in the interval of 20% to 30% of the length of the original text, respectively, and the user can make a rough selection according to the thumbnail degree corresponding to each thumbnail level. And determining the candidate thumbnail level selected by the user as the target thumbnail level according to the operation of the user.

Optionally, a target thumbnail level selected by the user from at least one preset candidate thumbnail level is obtained.

In this step, since the user can intuitively select the thumbnail degree, a plurality of candidate thumbnail grades are prepared in advance for the user. Therefore, the user can directly select at least one of the candidate thumbnail levels as a target thumbnail level, and perform a deletion process for the electronic book in accordance with the target thumbnail level. For example, in the above example, when the user selects the fourth candidate thumbnail level as the target thumbnail level, the e-book is pruned to a length of the space of 20% to 30% of the length of the original text. For example, in the above example, when the user selects the third candidate thumbnail level and the fourth candidate thumbnail level as the target thumbnail levels, the third candidate thumbnail level may be used to perform the first time of deleting processing on the full text, and the fourth candidate thumbnail level may be used to perform the second time of deleting processing on the partial text, so as to obtain the electronic thumbnail with the length of 30% to 50% of the original text.

Optionally, acquiring a target retention ratio value set by a user; one of the candidate thumbnail levels having a retention ratio value larger than the target retention ratio value is selected as a first target thumbnail level, and one of the candidate thumbnail levels having a retention ratio value smaller than the target retention ratio value is selected as a second target thumbnail level.

In addition, in this step, the user may set the degree of deletion of the specific numerical value by himself, but the degree of deletion does not necessarily coincide with the predetermined candidate level of contraction, and may be between the two candidate levels of contraction. Thus, the user may be provided with a range of retention ratios, for example ranging from the proportion of the original to the retention ratio using the fourth level contraction rule for the entire original, for example in the above example the retention ratio may range from 20% to 100%. Therefore, the user can freely set the retention ratio in the interval, and the APP acquires the target retention ratio value set by the user, then selects one of the candidate thumbnail levels with the retention ratio value larger than the target retention ratio value as a first target thumbnail level, and selects one of the candidate thumbnail levels with the retention ratio value smaller than the target retention ratio value as a second target thumbnail level. And performing first deletion processing on the whole book by adopting a first target abbreviation rule associated with the first target abbreviation level, and performing second deletion processing on the selected part of content by adopting a second target abbreviation rule associated with the second target abbreviation level.

Preferably, the first target thumbnail level and the second target thumbnail level are adjacent candidate thumbnail levels.

In this step, in order to avoid that the distance between the thumbnail degrees is too large, the user feels that some chapter contents are relatively detailed, some chapter contents are too omitted, the jumping feeling of the characters is too strong, and the reading feeling of the user is affected, so that the thumbnail level corresponding to the first deletion processing and the thumbnail level corresponding to the second deletion processing are preferably adjacent candidate thumbnail levels.

Preferably, the target retention proportion value set by the user is determined according to the number input by the user; or, according to the dragging operation of the scale axis by the user, the target retention proportion value set by the user is determined.

In this step, the user may manually input parameters in a designated dialog box of the interface to set the target retention ratio value, or may drag a ratio axis on the interface to adjust the target retention ratio value, so as to specifically define the thumbnail form of the electronic book according to the specific requirements of the user.

Step S204, determining the target abbreviating rule related to the target abbreviating grade according to the association relation between the predetermined candidate abbreviating grade and the candidate abbreviating rule.

In the invention, specific abbreviation rules are established and associated for each candidate abbreviation level according to the part of speech of the words. Optionally, if the target abbreviation level is a first candidate abbreviation level, determining that the target abbreviation rule is to delete a term belonging to an adjective; if the target abbreviation level is a second candidate abbreviation level, determining that the target abbreviation rule is to delete the words belonging to adjectives, numerators, quantifiers and pronouns; if the target abbreviation level is a third candidate abbreviation level, determining that the target abbreviation rule is to delete words belonging to adjectives, numerators, quantifiers, pronouns, adverbs, prepositions, auxiliary words, sighs and vocabularies; and if the target abbreviation level is a fourth candidate abbreviation level, deleting other words except the main and predicate objects in each sentence in the electronic book.

In this step, the higher the candidate abbreviation level is, the greater the degree of reduction of the electronic book is, and the more parts of speech of the word to be deleted is. However, in order to retain key information in the electronic book, for the deletion process of words of certain parts of speech, some words in the next level refinement category of the parts of speech cannot be deleted. Preferably, in the process of deleting the words belonging to the adverb in the electronic book, the words belonging to the negative adverb, the time adverb or the frequency adverb are retained. Finally, connecting the rest words according to the sequence, and simultaneously removing unnecessary punctuation marks to obtain the thumbnail book with the corresponding level.

Step S205, determining the chapter and/or paragraph to which the target thumbnail rule applies according to a user operation.

In the step, the user can set a uniform abbreviative rule for the full text; different abbreviative rules may also be set for specified chapters and/or paragraphs, with some chapters and/or paragraphs not being abbreviated; different thumbnail rules may also be automatically set for portions of chapters and/or paragraphs without user specification. Therefore, each chapter and/or paragraph to which each target abbreviating rule is applicable is determined, and only the reserved proportion set by the user can be reached or approximately reached after the whole electronic book is abbreviated. The selection granularity of the length of the thumbnail space is further refined by selecting the use or non-use of the thumbnail rules and the level of the thumbnail rules for different object contents (such as chapters and paragraphs) in the text.

Preferably, each word included in the other part of the electronic book except the directory is deleted.

In this step, the original text is retained without any deletion processing for the directory. The reason is that: on one hand, because the information in the catalog is important, the method has the function of reading guidance for the user, and the deletion easily causes that the user cannot quickly find the chapters and/or paragraphs to be read; on the other hand, directories are fewer words relative to full text, and even if they are truncated, they do not contribute much to full text contraction. Therefore, the words contained in the parts of the electronic book other than the directory are deleted.

Step S206, for each target abbreviation rule, according to the part of speech of each term contained in the electronic book, deleting each term contained in the chapter and/or paragraph to which the target abbreviation rule applies.

In this step, the terms in the electronic book, the parts of speech of the terms, the candidate abbreviation levels, the abbreviation rules associated with the candidate abbreviation levels, and the abbreviated chapters and/or paragraphs specified by the user operation are clarified, i.e., the terms contained in the chapters and/or paragraphs to which the target abbreviation rules apply can be subtracted according to the corresponding relationships.

The following is illustrated as an example:

for a segment of a sentence: "o! Flying snow wanders to see glittering snow flakes, one flake, two flakes and three flakes fall on shoulders of people. The snow flakes are stepped on in the su, so that the snow flakes will melt when people look at the snow flakes, and the snow flakes are not cut in the heart. "wherein the original text comprises 58 characters in total.

Performing word segmentation processing on the sentence, and performing part-of-speech tagging on each word in the word segmentation result to obtain a processing result: o (sigh)! The method comprises the following steps of walking (verbs) in snow days (nouns) in a flying manner, seeing (verbs) glittering (adjective) snowflakes (nouns), one (digital) sheet (quantifier), two (digital) sheet (quantifier), three (digital) sheet (quantifier), and falling (verbs) on (auxiliary words) shoulders (nouns) of (prepositions) people (nouns) (prepositions). The su (pseudo-word) treads (verb) the hair (verb) and snowflakes (noun), looks (verb) the hair (pronoun) melt (verb) the hair (time adverb), and the heart (noun) has a little (adverb) and does not (negative adverb) give up (verb).

After word segmentation and part-of-speech tagging, the sentence is subjected to abbreviation processing:

when the first candidate abbreviation level is selected, the words in the sentence with the allegedness belonging to the adjective are deleted, and the abbreviation result of the sentence is as follows: o! Walking in snowy days, people can see snowflakes, one, two and three, and the snowflakes fall on the shoulders of people. The snow flakes are stepped on in the su, so that the snow flakes will melt when people look at the snow flakes, and the snow flakes are not cut in the heart. Wherein a total of 50 characters remain after the first candidate level of abbreviation, and the contracted sentence occupies 86% of the length of the original text space.

When the second candidate abbreviation level is selected, the words with the lexical characters belonging to the adjectives, the numerators, the quantifiers and the pronouns in the sentence are deleted, and the abbreviation result of the sentence is as follows: o! Walking in snowy days, seeing snowflakes and falling on the shoulders of people. The snow flakes are stepped on in the su, and the snow flakes are melted after being seen, so that the snow flakes are not used in the heart. Wherein a total of 40 characters remain after the second candidate level of abbreviation, and the contracted sentence occupies 68% of the length of the original text space.

When the third candidate abbreviation level is selected, words in the sentence, the word of which the word property belongs to adjective, digraph, quantifier, pronoun, adverb, preposition, auxiliary word, sigh and vocalisation are deleted, and the abbreviation result of the sentence is as follows: walk astray in snow, see snowflakes and fall on the shoulders of people. When the user steps on snowflakes, the snowflakes will melt, and the user does not feel happy. Since "will" is a time adverb and "not" is a negative adverb, it is not deleted. Wherein, a total of 28 characters remain after the third candidate abbreviation level abbreviation, and the contracted sentence occupies 48% of the length of the original text space.

When the fourth candidate abbreviation level is selected, then for each sentence, deleting the other words in the sentence except the main and predicate objects, and the abbreviation result of the sentence is: see the snowflakes falling on the shoulders. When the snowflakes are treaded, the snowflakes need to be melted without being cut. Similarly, "about to" and "not" are not deleted. Wherein, after the fourth candidate abbreviation level, 17 characters are remained in total, and the abbreviated sentence occupies 29 percent of the length of the original text space.

Step S207, performing shading processing on the deleted characters, and performing highlighting processing on the rest characters.

In this step, the thumbnail after the deletion processing may be displayed in a display mode by displaying only the thumbnail content, and the thumbnail may be visually displayed; on the basis of displaying the full text, the deleted characters can be subjected to graying processing, and the rest characters can be subjected to highlighting processing, so that the user can see the comparison before and after the abbreviation, and can intuitively feel the content concentrated after the abbreviation.

And step S208, acquiring and counting a reduction request reported by a user side, wherein the reduction request comprises a position to be reduced marked by the user in the process of reading the thumbnail.

In this step, considering that the user may feel that the content at some position may affect the understanding of the original text after the content is abbreviated when reading the abbreviated content, the present invention can provide the user with the opportunity to report the restore request, and the user can report the restore request for the specific content that the user wants to restore. Specifically, the restoring request may be implemented in a labeling manner, that is, labeling is performed on the content to be restored, a position of the thumbnail marked by the user is a position desired to be restored by the user, and the thumbnail content included in the position is the content to be restored. And when the user finishes marking on the specific position, the user is considered to report a restoration request. After a recovery request reported by a user is acquired, the labeling information of the user is uploaded to a network side, and the labeling information of the thumbnail book of the book at the position is counted in all users of the whole network.

Step S209, if it is determined according to the statistical result that any one of the positions to be restored satisfies the preset restoring condition, adding the deleted characters before and after the position to be restored to the thumbnail.

In this step, since the annotation of the user is the restoration request of the representative user, statistics can be performed on the users who read the thumbnails of the same books and the users who label the positions to be restored in the thumbnails in the whole network. For example, the total number of users reading thumbnails of the same book and the number of users in which the positions to be restored are labeled in the whole network can be counted according to the whole network data. When most users mark the same position to be restored of the same thumbnail book, it can be understood that the ratio of the number of users marking the same position to be restored to the total number of users reading the thumbnail book of the same book exceeds a certain threshold, for example, 50%, it is determined that the thumbnail content on the position to be restored needs to be restored, and then the deleted characters before and after the position to be restored are added to the thumbnail book, so as to achieve the purpose of restoring the character face.

According to the electronic thumbnail generation method provided by the embodiment, the electronic thumbnail can be automatically generated according to the requirements of the user. Firstly, performing word segmentation processing on the electronic book according to the content in the electronic book; secondly, performing part-of-speech tagging on each word in the segmentation result by adopting a part-of-speech tagging model generated based on hidden Markov model training; then according to the requirements of users, determining the thumbnail level of the electronic book and the associated thumbnail rules thereof, deleting each word of the designated content in the electronic book by adopting the designated target thumbnail rule according to the part of speech of each word, displaying the deleted characters in a dark mode, and displaying the reserved characters in a highlight mode to obtain the electronic thumbnail book meeting the requirements of the users; and finally, according to the requirements of the user in the reading process, the user is supported to restore the thumbnail in a marking mode. The electronic thumbnail generation method can be used for automatically generating the electronic thumbnail according to the user requirement and providing the electronic thumbnail meeting the user requirement for the user. The method has the advantages that the thumbnail generation mode of automatically deleting words is realized without influencing the original text understanding, the original text information quantity and the reading smoothness or little influence, manual intervention is not needed, the labor cost investment is saved, and the thumbnail generation efficiency is improved; meanwhile, different users can select the thumbnail with proper length at fine granularity according to time arrangement in different scenes, and the electronic thumbnail meeting the user requirements is generated at any time and any place according to the selection for reading, so that the reading experience of the users is improved.

EXAMPLE III

Fig. 3 is a flowchart illustrating an electronic book content to which a target thumbnail rule is determined according to a third embodiment of the present invention, where the present embodiment is applied to determine a scene of the electronic book content to which the target thumbnail rule is applied. As shown in fig. 3, the method comprises the steps of:

step S301, a target retention ratio value set by the user is acquired.

Step S302, selecting one of the candidate abbreviative grades with the retention ratio value larger than the target retention ratio value as a first target abbreviative grade, and selecting one of the candidate abbreviative grades with the retention ratio value smaller than the target retention ratio value as a second target abbreviative grade.

Step S303, a first target abbreviating rule associated with the first target abbreviating level is adopted to delete the whole book.

Step S304, selecting N chapters from the electronic book, and adopting a second target abbreviating rule associated with the second target abbreviating level to delete the selected N chapters.

In the step, when the reserved proportion value set by the user is between the proportion values corresponding to two candidate abbreviated grades, selecting the candidate abbreviated grade with the reserved proportion value larger than the reserved proportion value as a first target abbreviated grade, and adopting a first target abbreviated rule associated with the first target abbreviated grade to delete the full text; and selecting the candidate thumbnail level with the retention ratio value smaller than the retention ratio value as a second target thumbnail level, and performing deletion processing on the selected N chapters by adopting a second target thumbnail rule associated with the second target thumbnail level. For example, when the retention ratio set by the user is a certain ratio value between the retention ratios corresponding to the second candidate abbreviation level and the third candidate abbreviation level, the APP may perform the subtraction processing of the second level abbreviation rule associated with the second candidate abbreviation level on the whole book, and then select N chapters to perform the subtraction processing of the third level abbreviation rule associated with the third candidate abbreviation level.

Preferably, the number N of chapters selected from the electronic book is determined by the following formula: N-N_{General assembly}X (b1-b3)/(b2-b1), wherein N is_{General assembly}Is the total number of chapters of the electronic book, b₁Is a value of a reserved scale of said first target thumbnail level, b₂Is a value of a reserved scale of said second target thumbnail level, b₃Is the target retention fraction value.

In this step, N is limited according to the retention ratio value corresponding to each candidate abbreviated level. For example, assuming that the retention ratio values of the first to fourth candidate abbreviated levels are 90%, 70%, 50% and 30% in this order, when the user sets the retention ratio value to 65%, the value of N is N ═ N_{General assembly}X (b 1-65%)/(b 2-b1), where b1 may select that the retention ratio value is greater than 65% of the retention ratio value set by the user, for example, may select 90% of the retention ratio value corresponding to the first candidate abbreviated level or may select 70% of the retention ratio value corresponding to the second candidate abbreviated level; b2 may select that the retention ratio value is less than 65% of the retention ratio value set by the user, for example, 50% of the retention ratio value corresponding to the third candidate abbreviated level may be selected, or 30% of the retention ratio value corresponding to the fourth candidate abbreviated level may be selected. Preferably, the effect of selecting the adjacent candidate abbreviated grades is better, so the embodiment selects the reserved ratio value 70% corresponding to the second candidate abbreviated grade as b1, and selects the reserved ratio value 50% corresponding to the third candidate abbreviated grade as b 2.

Assume that the entire electronic book has 96 chapters, each chapter including x words. It is assumed here that the number of words per chapter is approximately equal. The number of characters left after the full text is abbreviated with the second candidate abbreviated level, b1 × 96 × x, if the number of characters left after the full text is abbreviated with the user-set ratio is 65% × 96 × x, the difference between the two is b1 × 96 × x-65% × 96 × x, that is, if the full text is abbreviated with the second candidate abbreviated level, the difference is b1 × 96 × x-65% × 96 × xWith the contraction rule associated with the second candidate contraction level, b1 × 96 × x-65% × 96 × x words, i.e., (b 1-65%) × 96 × x words, need to be further reduced from the user-set retention ratio value. Similarly, (b2-b1) × 96 × x is the number of characters that can be reduced in total when the full text is abbreviated with the third abbreviation rule associated with the third candidate abbreviation level relative to when the full text is abbreviated with the second abbreviation rule associated with the second candidate abbreviation level. Thus, [ (b 1-65%). times.96 X.times.x]/[(b2-b1)×96×x]The number of words to be further reduced is a proportion of the total number of reduced words, i.e. (b 1-65%)/(b 2-b 1). On the basis of the above-mentioned formula, multiplying by N_{General assembly}And obtaining the N value. If the value of N is not an integer, rounding up or down.

In this step, after N is determined, it is further determined which chapters are further abbreviated. In one implementation, preferably, other chapters except for the beginning chapter and the end chapter in the electronic book are taken as candidate chapters; n chapters are selected from the candidate chapters. Since it is considered that the first chapter and the last chapter of a book are respectively laid and summarized for the story and are important in the plot, the first chapter and the last chapter of the electronic book are not excessively deleted as much as possible, and the first chapters and the last chapters can be avoided, and the N chapters can be selected from the middle chapters.

Specifically, the selection of the N chapters that need to be subjected to the second pruning process may be implemented in various ways, and this embodiment is described here in two more typical ways: in the first mode, N continuous chapters are randomly selected; in the second mode, N chapters are selected from the non-popular chapters.

In a first mode, one chapter is randomly selected from all the candidate chapters to serve as an initial chapter; and continuously selecting N chapters by taking the starting chapter as a starting chapter. The method has the advantage that influence on reading fluency of users in the process of reading each chapter due to frequent change of the thumbnail level in the whole text can be avoided. It should be noted that, when selecting the beginning section, it is necessary to ensure that at least N-1 consecutive sections are available after the beginning section and before the end section, and for this, one implementation includes:

after the chapter number N is determined, calculating the selection range of the initial chapter as a closed interval: [ (a +1), (N)_{General assembly}-b-N)]. Wherein a is the number of leading chapters and b is the number of trailing chapters. For example, if the whole book has 96 chapters in total, chapter 3 at the beginning and chapter 2 at the end are not selected, and 4 consecutive chapters need to be abbreviated by the second candidate abbreviated level, the selection range of the beginning chapter is a closed interval [4,90 ]]Within this range, the start chapter can be randomly selected.

In another implementation, the need for having consecutive chapters of N-1 after the guarantee may be overridden in determining the starting chapter position, i.e., may be between [ (a +1), (N)_{General assembly}-b)]Randomly selects the starting section in the closed interval. After the beginning chapter is determined, chapter N-1 is selected from the beginning chapter, and if chapter N-1 is not enough, the remaining chapters are fetched after chapter is full backwards and then forwards. Or the operation of selecting chapters backwards can be cancelled, and the chapter N-1 is selected forwards from the initial chapter to complete the selection of the chapter N.

Selecting a non-popular chapter from each candidate chapter according to the reading behavior of the user on each candidate chapter; n chapters are selected from the selected non-popular chapters. Specifically, statistics can be performed according to information such as times of publishing ideas, comments, leaving messages and sharing of users over the network, popular chapters of the book are determined, the chapters are used as key chapters, original information of the chapters is kept as much as possible, and further secondary deletion processing is not performed. Therefore, it is possible to select a plurality of chapters from among the non-top chapters that avoid the top chapters and perform the second deletion process. Although this approach does not guarantee that the selected chapters are consecutive, it is permissible to perform secondary deletion processing on non-consecutive chapters that do not contain key information in order to make a concession as to retain key information as much as possible.

In step S305, if a fast reading instruction for the next chapter is received by the user, the words included in the next chapter are abbreviated.

In the invention, the fast reading instruction means that a user can expect to fast read the next chapter according to the plot development corresponding to the read content in the normal reading process, namely complete reading can be carried out on the basis of the abbreviated content, the reading time can be saved, an abbreviated reading mode is set when the next chapter is read, and the APP only carries out the deleting processing of the reserved proportion value selected by the user on the next chapter after receiving the fast reading instruction issued by the user. The quick reading instruction can be set in the process of normally reading the original electronic book by the user or in the process of reading the thumbnail book.

The implementation principle and the specific execution process of steps S301 to S304 can refer to the description of steps S203 to S206 in the embodiment corresponding to fig. 2, and are not described herein again.

According to the electronic thumbnail generation method provided by the embodiment, the electronic thumbnail generation method can be used for determining the electronic book content to which the target thumbnail rule is applicable. Firstly, acquiring a target retention ratio value set by a user; secondly, selecting one of the candidate thumbnail grades with the retention ratio value larger than the target retention ratio value as a first target thumbnail grade, and adopting a first target thumbnail rule associated with the first target thumbnail grade to delete the whole book; and selecting one of the candidate thumbnail levels with the retention ratio value smaller than the target retention ratio value as a second target thumbnail level, and performing deletion processing on the selected N chapters by adopting a second target thumbnail rule associated with the second target thumbnail level. Preferably, N continuous chapters are randomly selected from other candidate chapters except for a beginning chapter and an end chapter in the electronic book or N chapters are selected from non-popular chapters; n is determined by the reservation ratio value corresponding to each candidate thumbnail grade related to the target reservation ratio value set by the user. The electronic thumbnail generation method of the embodiment can be used for determining the electronic book content to which the target thumbnail rule is applicable and providing the electronic thumbnail meeting the user requirement for the user. The thumbnail generation method for automatically deleting words according to the operation of a user under the condition of not influencing the understanding of the original text, the information content of the original text and the reading smoothness or having little influence is realized, manual whole-process intervention is not needed, the investment of labor cost is saved, and the generation efficiency of the thumbnail is improved; meanwhile, different users can select the thumbnail with proper length at fine granularity according to time arrangement in different scenes, and the electronic thumbnail meeting the user requirements is generated at any time and any place according to the selection for reading, so that the reading experience of the users is improved.

Example four

The fourth embodiment of the present invention further provides a nonvolatile computer storage medium, where the computer storage medium stores at least one executable instruction, and the computer executable instruction may execute the electronic thumbnail generation method in any of the above method embodiments.

The executable instructions may be specifically configured to cause the processor to:

determining each word contained in the electronic book and the part of speech of each word;

determining a target abbreviation rule according to user operation;

and deleting the words contained in the electronic book according to the part of speech of the words contained in the electronic book by adopting the target abbreviation rule to obtain the abbreviation book.

In an alternative, the executable instructions further cause the processor to:

performing word segmentation on the electronic book to obtain words contained in the electronic book;

and performing part-of-speech tagging on each word contained in the electronic book according to a part-of-speech tagging model generated in advance based on hidden Markov model training.

In an alternative, the executable instructions further cause the processor to:

determining a target thumbnail level according to user operation;

and determining the target abbreviating rule associated with the target abbreviating grade according to the association relation between the predetermined candidate abbreviating grade and the candidate abbreviating rule.

In an alternative, the executable instructions further cause the processor to:

and acquiring a target thumbnail level selected by a user from at least one preset candidate thumbnail level.

In an alternative, the executable instructions further cause the processor to:

acquiring a target retention ratio value set by a user;

one of the candidate thumbnail levels having a retention ratio value larger than the target retention ratio value is selected as a first target thumbnail level, and one of the candidate thumbnail levels having a retention ratio value smaller than the target retention ratio value is selected as a second target thumbnail level.

In an alternative, the executable instructions further cause the processor to:

determining a target retention ratio value set by a user according to the number input by the user; alternatively, the first and second electrodes may be,

and determining a target retention proportion value set by the user according to the dragging operation of the scale axis by the user.

In an optional manner, the first target thumbnail level and the second target thumbnail level are adjacent candidate thumbnail levels.

In an alternative, the executable instructions further cause the processor to:

deleting the whole book by adopting a first target abbreviating rule associated with the first target abbreviating grade;

and selecting N chapters from the electronic book, and deleting the selected N chapters by adopting a second target thumbnail rule associated with the second target thumbnail level.

In an alternative, the executable instructions further cause the processor to:

taking other chapters except the beginning chapters and the ending chapters in the electronic book as candidate chapters;

n chapters are selected from the candidate chapters.

In an alternative, the executable instructions further cause the processor to:

randomly selecting one chapter from the candidate chapters to serve as an initial chapter;

and continuously selecting N chapters by taking the starting chapter as a starting chapter.

In an alternative, the executable instructions further cause the processor to:

selecting a non-popular chapter from each candidate chapter according to the reading behavior of the user on each candidate chapter;

n chapters are selected from the selected non-popular chapters.

In an alternative manner, the number N of chapters selected from the electronic book is determined by the following formula:

N＝N_{general assembly}×(b1-b3)/(b2-b1)

Wherein N is_{General assembly}Is the total number of chapters of the electronic book, b1 is the retention scale value of the first target thumbnail level, b2 is the retention scale value of the second target thumbnail level, and b3 is the target retention scale value.

In an alternative, the executable instructions further cause the processor to:

if the target abbreviation level is a first candidate abbreviation level, determining that the target abbreviation rule is to delete the words belonging to the adjective;

if the target abbreviation level is a second candidate abbreviation level, determining that the target abbreviation rule is to delete the words belonging to adjectives, numerators, quantifiers and pronouns;

if the target abbreviation level is a third candidate abbreviation level, determining that the target abbreviation rule is to delete words belonging to adjectives, numerators, quantifiers, pronouns, adverbs, prepositions, auxiliary words, sighs and vocabularies;

and if the target abbreviation level is a fourth candidate abbreviation level, deleting other words except the main and predicate objects in each sentence in the electronic book.

In an alternative, the executable instructions further cause the processor to:

and in the process of deleting the words belonging to the adverbs in the electron, keeping the words belonging to the negative adverbs, the time adverbs or the frequency adverbs.

In an alternative, the executable instructions further cause the processor to:

determining chapters and/or paragraphs to which the target abbreviation rules are applicable according to user operation;

and for each target abbreviation rule, deleting the words contained in the chapters and/or paragraphs to which the target abbreviation rule applies according to the parts of speech of the words contained in the electronic book.

In an alternative, the executable instructions further cause the processor to:

and deleting words contained in other parts except the catalog in the electronic book.

In an alternative, the executable instructions further cause the processor to:

and if a quick reading instruction of the next chapter from the user is received, carrying out abbreviation processing on the words contained in the next chapter.

In an alternative, the executable instructions further cause the processor to:

and performing shading processing on the deleted characters, and performing highlighting processing on the rest characters.

In an alternative, the executable instructions further cause the processor to:

acquiring and counting a reduction request reported by a user side, wherein the reduction request comprises a position to be reduced marked by the user in the process of reading the thumbnail;

and if any position to be restored meets the preset restoring condition according to the statistical result, adding the deleted characters before and after the position to be restored into the thumbnail book.

EXAMPLE five

Fig. 4 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the electronic device.

As shown in fig. 4, the electronic device may include: a processor (processor)402, a Communications Interface 404, a memory 406, and a Communications bus 408.

Wherein:

the processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408.

A communication interface 404 for communicating with network elements of other devices, such as clients or other servers.

The processor 402 is configured to execute the program 410, and may specifically perform relevant steps in the above-described electronic book recommendation method embodiment.

In particular, program 410 may include program code comprising computer operating instructions.

The processor 402 may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention. The electronic device comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

And a memory 406 for storing a program 410. Memory 406 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The program 410 may specifically be configured to cause the processor 402 to perform the following operations:

determining a target abbreviation rule according to user operation;

In an optional manner, the program 410 may be specifically further configured to cause the processor 402 to perform the following operations:

determining a target thumbnail level according to user operation;

acquiring a target retention ratio value set by a user;

In an alternative manner: the first target abbreviation level and the second target abbreviation level are adjacent candidate abbreviation levels.

n chapters are selected from the candidate chapters.

n chapters are selected from the selected non-popular chapters.

In an alternative manner: the number of chapters N selected from the electronic book is determined by the following formula:

N＝N_{general assembly}×(b1-b3)/(b2-b1)

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Claims

1. An electronic thumbnail generation method, comprising:

determining a target thumbnail level according to user operation;

determining a target abbreviating rule associated with the target abbreviating grade according to the association relation between the predetermined candidate abbreviating grade and the candidate abbreviating rule; the target abbreviation rules are determined by target abbreviation levels corresponding to the abbreviation degrees which are selected by a user and meet the requirements of the user, the abbreviation degrees of the candidate abbreviation levels determine the parts of speech of the words which need to be deleted, and the higher the candidate abbreviation level is, the more the parts of speech of the words which need to be deleted is; wherein the user operation comprises at least one of: setting the proportional value of the length reduction of the space to the original text, setting the reduction level of the space, setting the reduction range and setting the reduction degree of the content of the appointed part;

2. The method of claim 1, wherein determining words contained in the electronic book and parts of speech of the words comprises:

3. The method of claim 1, wherein determining a target thumbnail level in accordance with a user action comprises:

4. The method of claim 1, wherein determining a target thumbnail level in accordance with a user action comprises:

acquiring a target retention ratio value set by a user;

5. The method of claim 4, wherein obtaining the target reservation fraction value set by the user comprises:

6. The method of claim 4, wherein the first target abbreviated level and the second target abbreviated level are adjacent candidate abbreviated levels.

7. The method of claim 4, wherein the obtaining of the abbreviation by deleting each term included in the electronic book according to the part of speech of each term included in the electronic book by using the target abbreviation rule comprises:

8. The method of claim 7, wherein selecting N chapters from the electronic book comprises:

n chapters are selected from the candidate chapters.

9. The method of claim 8, wherein selecting N sections from the candidate sections comprises:

10. The method of claim 8, wherein selecting N sections from the candidate sections comprises:

n chapters are selected from the selected non-popular chapters.

11. The method of any of claims 7-10, wherein the number of chapters N selected from the electronic book is determined by the formula:

N＝N_{general assembly}×(b1-b3)/(b2-b1)

12. The method of claim 1, wherein determining the target abbreviation rule associated with the target abbreviation level according to a predetermined association between the candidate abbreviation level and the candidate abbreviation rule comprises:

13. The method of claim 12, comprising:

and in the process of deleting the words belonging to the adverbs in the electronic book, keeping the words belonging to the negative adverbs, the time adverbs or the frequency adverbs.

14. The method of claim 1, wherein the obtaining of the abbreviation by deleting each term included in the electronic book according to a part of speech of each term included in the electronic book by using the target abbreviation rule comprises:

15. The method of claim 1, wherein the deleting of the words contained in the electronic book to obtain an abbreviation includes:

16. The method of claim 1, further comprising:

17. The method of claim 1, wherein after the words included in the electronic book are deleted to obtain an abbreviation, the method further comprises:

18. The method of claim 1, wherein after the words included in the electronic book are deleted to obtain an abbreviation, the method further comprises:

19. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is configured to store at least one executable instruction that causes the processor to:

determining a target thumbnail level according to user operation;

20. The electronic device of claim 19, the executable instructions further cause the processor to:

21. The electronic device of claim 19, the executable instructions further cause the processor to:

22. The electronic device of claim 19, the executable instructions further cause the processor to:

acquiring a target retention ratio value set by a user;

23. The electronic device of claim 22, the executable instructions further cause the processor to:

24. The electronic device of claim 22, the first target abbreviated level and the second target abbreviated level being adjacent candidate abbreviated levels.

25. The electronic device of claim 22, the executable instructions further cause the processor to:

26. The electronic device of claim 25, the executable instructions further cause the processor to:

n chapters are selected from the candidate chapters.

27. The electronic device of claim 26, the executable instructions further cause the processor to:

28. The electronic device of claim 26, the executable instructions further cause the processor to:

n chapters are selected from the selected non-popular chapters.

29. The electronic device of any of claims 25-28, the number of chapters N selected from the electronic book is determined by the formula:

N＝N_{general assembly}×(b1-b3)/(b2-b1)

30. The electronic device of claim 19, the executable instructions further cause the processor to:

31. The electronic device of claim 30, the executable instructions further cause the processor to:

32. The electronic device of claim 19, the executable instructions further cause the processor to:

33. The electronic device of claim 19, the executable instructions further cause the processor to:

34. The electronic device of claim 19, the executable instructions further cause the processor to:

35. The electronic device of claim 19, the executable instructions further cause the processor to:

36. The electronic device of claim 19, the executable instructions further cause the processor to:

37. A computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to:

determining a target thumbnail level according to user operation;

38. The computer storage medium of claim 37, the executable instructions further causing the processor to:

39. The computer storage medium of claim 37, the executable instructions further causing the processor to:

40. The computer storage medium of claim 37, the executable instructions further causing the processor to:

acquiring a target retention ratio value set by a user;

41. The computer storage medium of claim 40, the executable instructions further causing the processor to:

42. The computer storage medium of claim 40, the first target abbreviated level and the second target abbreviated level being adjacent candidate abbreviated levels.

43. The computer storage medium of claim 40, the executable instructions further causing the processor to:

44. The computer storage medium of claim 43, the executable instructions further causing the processor to:

n chapters are selected from the candidate chapters.

45. The computer storage medium of claim 44, the executable instructions further causing the processor to:

46. The computer storage medium of claim 44, the executable instructions further causing the processor to:

n chapters are selected from the selected non-popular chapters.

47. The computer storage medium of any of claims 43-46, the number of chapters N selected from the electronic book determined by the formula:

N＝N_{general assembly}×(b1-b3)/(b2-b1)

48. The computer storage medium of claim 37, the executable instructions further causing the processor to:

49. The computer storage medium of claim 48, the executable instructions further causing the processor to:

50. The computer storage medium of claim 37, the executable instructions further causing the processor to:

51. The computer storage medium of claim 37, the executable instructions further causing the processor to:

52. The computer storage medium of claim 37, the executable instructions further causing the processor to:

53. The computer storage medium of claim 37, the executable instructions further causing the processor to:

54. The computer storage medium of claim 37, the executable instructions further causing the processor to: