CN102479237A

CN102479237A - Word associated search and study method and system

Info

Publication number: CN102479237A
Application number: CN2010105753470A
Authority: CN
Inventors: 范培林; 赵彬; 熊麒麟; 汪凤兰; 唐昌群
Original assignee: CHENGDU ZHIYUAN NUOYAZHOU EDUCATION TECHNOLOGY Co Ltd
Current assignee: SHENZHEN YOUXUETIANXIA EDUCATION DEVELOPMENT CO., LTD.
Priority date: 2010-11-30
Filing date: 2010-11-30
Publication date: 2012-05-30
Anticipated expiration: 2030-11-30
Also published as: CN102479237B

Abstract

The invention discloses a word associated search and study method and system. The method comprises the following steps: a) receiving a word to be searched which is input by a user; b) matching the word to be searched in a word search and study resource library module which is composed of a center word module, a divergent word module, a picture information module, a picture content library module and a picture entry content module; c) calling the matched word entry content and calculating the KEY value of the divergent word which is relative to the word and needs to be displayed in a divergent attribute; and establishing and displaying a word associated network chart according to the KEY value, wherein the word associated network chart takes the word as the center word and takes the divergent word as a peripheral word. According to the method and the system, provided by the invention, the words input by the user can be matched and displayed, and the divergent words and the pictures which are associated with the matched words can be obtained; and then the vivid and visual word associated network chart is displayed to the user. Therefore, the study effect of the user can be improved.

Description

Method and system is searched in a kind of word association

Technical field

The present invention relates to the e-learning apparatus field, be specifically related to a kind of word association and search method and system, word association of the present invention is searched system and can be applied on the e-learning equipment, for example learning machine, electronic dictionary, early learning machine, learning pen etc.

Background technology

Generally store dictionary retrieval module and Duo Ben dictionary file in traditional hand-held study equipment; The method of its searching words mainly contains following two kinds of forms: one of which, for the traditional conventional dictionaries query method; Relevant information through certain word of inquiry in certain selected this dictionary file of the dictionary retrieval module in the hand-held study equipment; This mode is characterised in that: the user only in selected dictionary file inquiry the certain attributes (like lexical or textual analysis, phonetic symbol etc.) of the word of importing and this word; This kind method is owing to each word in the dictionary file is separate; Do not set up complete incidence relation between the word, thereby the user can only find the association attributes of institute's verification certificate speech in the inquiry lexicon file, can't roam to other all words in this lexicon file through its attribute; Also can't roam in other lexicon file; When the user need check the association attributeses such as lexical or textual analysis of certain word in an other dictionary, must withdraw from this dictionary earlier and get into other dictionary more again, operation is very complicated; Its two: the relevant information of certain word of inquiry in many selected dictionary files of the mode through striding dictionary search; Like the method for being put down in writing among the Chinese invention patent ZL200610157957.2, this method is characterised in that: the attributes such as lexical or textual analysis of certain word of inquiry in many selected dictionary files.The advantage of the method is in many dictionary files, to check the attributes such as lexical or textual analysis of certain word through a key switching way; Solved and to have withdrawed from the complicated operation problem that this dictionary file gets into other this word of dictionary file polling more again in the traditional conventional dictionaries query method earlier, but still can not roam to other word freely through institute's looking up words owing to do not set up complete incidence relation between the various words in the dictionary.

This shows; Traditional hand-held electronic facility for study word Search Results is comparatively single; After the user imports word to be searched, generally can only show some attributes (like lexical or textual analysis, word types, common-use words, example sentence etc.) of this word and this word, system can't show with the user and imports other words that word is associated; Make the user can't carry out the related study of word, contrast study, disperse study, be unfavorable for custom system ground study related words.Also there is search defective easily inadequately in traditional hand-held electronic facility for study: the user need word for word import word search; Because the word of current search can only be learnt in word of every input, the user is if want to learn the next word word search of then having to re-enter.

Summary of the invention

The technical matters that the present invention will solve is; Loaded down with trivial details to existing hand-held electronic facility for study word search procedure, Search Results is single, can't the association table word problem; Provide a kind of word association to search method and system, make the user when word of input is searched for, system can show this word and other words and the picture that are associated with this word; Make things convenient for the user to carry out the related study of word, contrast study, disperse study, improve learning efficiency and results of learning.

The present invention discloses a kind of word association and searches method, and said method comprises:

Steps A: the word to be searched that receives user's input;

Step B: comprise the centre word module, disperse the speech module, the word of pictorial information module, image content library module and picture entry content module searches and learns the said word to be searched of coupling in the resources bank module;

Step C: read the entry content of the word that matches, each disperses the KEY value of speech in the attribute to calculate dispersing that the corresponding needs of this word show, and is centre word and disperses the word related network figure that speech is peripheral speech with this word according to KEY value structure and demonstration.

Said step B also comprises: if search when learning in the resources bank module coupling less than said word to be searched at said word, then obtain the entry content with the immediate word of the said word meaning of a word to be searched.

Method is searched in word association according to the present invention; After step B matches said word to be searched; Read the entry content of the word that matches; Add up the corresponding number of dispersing attribute of this word, each is dispersed, and all disperse the sum of speech under the attribute, obtain all and disperse that all disperse the sum of speech under the attribute; Judge that then whether ultra all disperse under the attribute all sums of dispersing speech word number of showing of allowing to single page; If surpass and then to confirm several and corresponding with the said word that matches disperse attribute and this disperses the speech of dispersing under the attribute, be used for showing at said word related network figure.

Method is searched in word association according to the present invention, among the said step C after making up said word related network figure, structure and demonstration and the related pictures of said word to be searched.

Method is searched in word association according to the present invention, and it is afterwards further comprising the steps of to have made up said word related network figure and pictures:

When the centre word object among the said word related network figure changes, search to learn in the resources bank module at said word and mate new centre word again;

Judge whether to match and the said new identical word of centre word, successfully then to make up and show with said new centre word be word related network figure, structure and the demonstration pictures related with new centre word that speech is peripheral speech of dispersing of centre word and needs thereof demonstration if mate;

If the KEY value of said new centre word is then resolved in coupling failure, judge its whether be in the said pictures a certain picture correspondence disperse speech, if then do not carry out any operation; Otherwise show the word related network figure that said new centre word and old centre word constitute.

Making up word related network figure among the said step C specifically may further comprise the steps:

Step C0: obtain the pairing number of dispersing attribute of the word that matches, each disperses under the attribute all sums of dispersing speech, all disperse the sum of dispersing speech that all need show under the attribute, judge said dispersing the speech sum and whether surpassing single page and allow the word number that shows of needing to show;

Step C1: calculating needs the number of pages of paging when surpassing the word number of single page permission demonstration, not paging when being no more than the word number of single page permission demonstration;

Step C2: a certain mark of dispersing attribute that needs in the attribute to show of dispersing of the word that matches is changed to current mark;

Step C3: the speech sum of dispersing that dispersing under the current mark shown in the attribute is changed to 0, all that have shown is dispersed under the attribute all disperse the speech sum and be changed to 0;

Step C4: all that will show are dispersed under the attribute all and are dispersed the speech sum and disperse the sum comparison of dispersing speech that all need show under the attribute with all; Judgement need to show all disperse speech and whether read and finish; If then finish the entire process process, then get into step C5 if not;

Step C5: judge that current page shows that whether the word number has reached the word number that single page allows demonstration, if then jump to down one page and change step C4 over to, then gets into step C6 if not;

Step C6: the sum of dispersing speech that dispersing under the current mark shown in the attribute and this are dispersed all need show under the attribute the sum of dispersing speech relatively; Judge that under the current mark all disperse speech and whether read and finish; Represent next to disperse next mark of attribute and jump to step C4 if then current mark is revised as to point to, then to get into step C7 if not;

Step C7: obtain under the current mark one of not showing and disperse speech and calculate its KEY value; This disperses speech and KEY value thereof through an object storage then, and this object corresponding entries content is joined as a node among the word related network figure of current page and show;

Step C8: the speech sum of dispersing that dispersing under the current mark shown in the attribute adds up 1, and all that will show are simultaneously dispersed under the attribute all and dispersed the speech sum and add up 1;

Step C9: current mark is revised as to point to changing step C4 over to after representing next next mark of dispersing attribute.

Said word association of the present invention is searched in the method; Said computing method of dispersing speech KEY value are: with saidly disperse the index of speech in dispersing speech module or pictorial information module, this disperses corresponding relation mark of dispersing attribute of speech number; After reaching index combination of this centre word of dispersing the speech correspondence in the centre word module, an integer numerical value that obtains after the basic displacement computing through computing machine.

Said word association of the present invention is searched in the method, and said word related network figure and pictures are selected study, specifically comprise:

Select the speech object of dispersing among the word related network figure to learn, system analysis is dispersed the KEY value of speech, and the relation of explanation or phonetic symbol or itself and the centre word of speech is dispersed in demonstration;

Select the picture in the pictures to learn, the KEY value of system-computed picture shows with the picture to be centre word, and the entry related with picture is the word network chart of peripheral speech;

Change a certain position of dispersing the speech object in the corresponding word network chart of word related network figure and/or picture, making it be in the centre word coordinate position becomes new centre word, proceeds study.

Method is searched in said word association of the present invention, and the speech sum of dispersing that shows as required when among the said step C7 object being joined word related network figure is arranged and write down the display position of each object on screen.

The present invention also discloses a kind of word association and searches system, and said system comprises:

Receiver module is used to receive the word to be searched that the user imports;

Search module is used to search for the word that is complementary with user's input;

Read module is used for when searching the word that is complementary with user's input, reading the word entry content that this matches;

Resolve the entry module, be used to resolve the word entry content that reads;

Interface display module is used for the entry content of having resolved is shown to the user;

Voice module is used for the pronunciation according to the corresponding audio files of the word entry content that reads;

Word is searched and is learned the resources bank module; Comprise the centre word module, disperse module; The said module of dispersing comprises and disperses speech module, pictorial information module, image content library module and picture entry content module; Said word is searched and is learned the content that the resources bank module is used for all words of stocking system, comprise entry, phonetic symbol, explanation, audio files and each word of each word corresponding disperse attribute;

KEY value computing module is used to calculate the pairing KEY value of dispersing speech of the keyword that matches;

KEY value parsing module; The KEY value that is used for storing according to object is confirmed the node that the user is clicked, then to said word search learn the resources bank module transfer with this node corresponding entries, phonetic symbol, explanation or with the relation on attributes mark of centre word and structure by said word and disperse the word related network figure that speech is formed.

Said centre word module comprises centre word index area module and centre word content regions module; Said centre word content regions module comprises entry module, phonetic symbol module, explanation module, audio files name module; And disperse attribute module; The entry content that said centre word module is used for storing one or several existing all words of dictionary comprise entry, phonetic symbol, explanation, audio files name and this word of each word corresponding disperse attribute; Saidly disperse that attribute refers to association, similar, near justice, antisense, variation, sound is near, shape is near, one or several attribute in derivation, collocation, phrase and the picture; Said each disperse the corresponding unique relation mark of attribute number; Said centre word index area module stores the index address of each word entry content of storing in the centre word content regions module, each index address points to the word entry content of unique correspondence in centre word content regions module.

The said speech module of dispersing comprises and disperses glossarial index district module and disperse speech content regions module; The said speech content regions module of dispersing has stored in the said centre word module the corresponding entry content of dispersing speech of all words and comprises each and disperse the entry of speech, phonetic symbol, explanation; Corresponding this of each word dispersed and dispersed the total number of speech entry under the attribute and disperse each that store in the speech content regions module and disperse the index address of speech entry content in the said said centre word module of having dispersed glossarial index district module stores, and what each index address pointed to unique correspondence of dispersing speech content regions module disperses speech entry content.

Said pictorial information module comprises pictorial information index area module and pictorial information content regions module; Said pictorial information content regions module has stored in the said centre word module index of each corresponding entry content of the corresponding entry number of index address, picture that the corresponding pictorial information of all words comprises each picture and picture; Corresponding entries content in the said index picture entry content module; Said pictorial information index area module stores the index address of each pictorial information of storing in the total number of picture that each word is corresponding in the said centre word module and the pictorial information content regions module, the pictorial information of unique correspondence of each index address sensing pictorial information content regions module.

Said image content library module has stored the corresponding concrete image content of each word in the said centre word module.

Said picture entry content module has stored each corresponding entry content of dispersing speech of each picture and has comprised each and disperse the entry of speech, phonetic symbol, explanation, audio files name.

Disperse attribute module in the said centre word module and comprise that corresponding each of each word dispersed the relation mark number of attribute, this is dispersed properties point and disperses index address corresponding in glossarial index district module or the pictorial information index area module; The index address of picture points to picture stored content in the said image content library module in the said pictorial information content regions module; The said picture entry of picture corresponding entries index content module in the said pictorial information content regions module, the word audio files name module in the said centre word module is pointed to sound-content corresponding in the voice module.

Said interface display module comprises that figure releases district's module, speech barrier module, correlogram section module and word explanation district module.

Said figure releases district's module and is used to show the mark of dispersing the attribute correspondence that word had that searches; Comprise association, similar, near justice, antisense, variation, sound is near, shape is near, in the derivation, collocation, phrase one or more; Institute's predicate barrier module is used to show by word and corresponding disperses word related network figure that speech constitutes and disperses the corresponding word network chart of picture that speech constitutes by picture and corresponding; Said correlogram section module is used to show the image content that is associated with the word that searches, and said word explanation district module is used to show phonetic symbol, explanation and the pronunciation button of the word that searches.

Compare with prior art; The present invention has following useful technique effect: 1, comprised resource huge, can related word search and learn the resources bank module; Search through this word and to learn the word that the resources bank module not only can the match user input, can also obtain all relevant and disperse speech and select to learn with picture confession user with the word that matches; 2, owing to made up the corresponding word network chart of word related network figure and picture, clearly perception of user, learn each inquiry word had disperses speech and picture and the relation between them, strengthen the study impression; 3, the user through click in the network chart disperse speech, picture can be learnt association knowledge; Through dragging the also convertible centre word of the mode of dispersing speech and picture and further learning new centre word content easily; Realized the related study of word, contrast study, dispersed study, can improve learning efficiency and results of learning.

Description of drawings

Fig. 1 is the block diagram that system is searched in the word association of the embodiment of the invention;

Fig. 2 is that the process flow diagram of method is searched in the word association of the embodiment of the invention;

Fig. 3 is that the structural representation of learning the resources bank module searched in the word of the embodiment of the invention;

Fig. 4 searches the process flow diagram of learning the coupling dichotomy that word to be searched adopted in the resources bank module at said word;

Fig. 5 obtains dispersing speech, paging and making up the method flow diagram of word related network figure and pictures of need showing;

Fig. 6 is the structural representation of word related network figure of the present invention and pictures;

Fig. 7 is the process synoptic diagram of dispersing speech among the learning word related network figure;

Fig. 8 is the process synoptic diagram of the centre word among the learning word related network figure;

Fig. 9 is the structural representation of picture of the present invention as the corresponding word network chart of centre word;

Figure 10 is the process synoptic diagram of dispersing speech in the corresponding word network chart of study picture;

Figure 11 is the process synoptic diagram of the picture in the corresponding word network chart of study picture;

Figure 12 drags to disperse speech and make it become the process synoptic diagram of centre word;

Figure 13 is the structural representation of interface display module of the present invention.

Embodiment

In order to make the object of the invention, technical scheme and advantage clearer,, the present invention is further elaborated below in conjunction with accompanying drawing and embodiment.Should be appreciated that specific embodiment described herein only in order to explanation the present invention, and be not used in qualification the present invention.

As shown in Figure 1, word association of the present invention is searched system and is comprised that receiver module, search module, read module, word are searched and learn the resources bank module, resolve entry module, interface display module, KEY value computing module, KEY value parsing module and voice module.Said receiver module is connected with search module; Said search module, read module are searched resources bank module with word respectively and are connected; Said parsing entry module and voice module all with read module, interface display module is two-way is connected, said KEY value computing module, KEY value parsing module all are connected with read module and interface display module are two-way.

Below each module is made further explain:

Said receiver module is used to receive the word to be searched of user's input;

Said search module is used for the word to be searched according to user's input, searches to learn at word and searches for the word that is complementary with user's input in the resources bank module;

Said read module is used for when searching the word that is complementary with user's input, searches to learn in the resources bank module at word and reads the word entry content that this matches;

Said parsing entry module is used for resolving searching from word learns the entry content that the resources bank module reads, and comprises the attribute of dispersing of entry, phonetic symbol, explanation, audio files name and the word correspondence of resolving each word;

Said interface display module is shown in figure 13, is used for the entry content that searches and resolved is fed back to the user with modes such as word related network figure, the corresponding word network chart of picture, pictures, supplies the user to select related study.Said interface display module comprises that figure releases district's module, speech barrier module, correlogram section module and word explanation district module.Said figure releases district's module and is used to show the mark of dispersing the attribute correspondence that word had that searches; Saidly disperse that attribute comprises association, similar, near justice, antisense, variation, sound is near, shape is near, one or more relations in the derivation, collocation, phrase, picture etc., be used to react that a word has comprises the speech of dispersing of associational word, synonym, near synonym, antonym, variation speech (comparative degree, the superlative degree, plural number, past tense, past participle, gerund, third person odd number), the nearly speech of sound, the nearly speech of shape, derivative, collocation speech, phrase.Institute's predicate barrier module is used to show the corresponding word network chart (like Fig. 9) of word related network figure (like Fig. 7) and picture, and said word related network figure is used for the word that searches and its relation of dispersing between the speech are organized, and shows the user vividly.Said word related network is strivied for survival at several objects, and each object has been stored word (hereinafter to be referred as centre word) or the corresponding attributes such as KEY value of dispersing speech of centre word that matches respectively.Particularly, said word related network strive for survival a centre word object that is positioned at the center with disperse the speech object through what lines were connected with the centre word object around several are positioned at.Each object can be controlled; For example the user gets final product contents such as Direct Learning vocabulary, phonetic symbol, pronunciation, explanation through clicking the centre word object and/or dispersing the speech object; Can also make it become new centre word object through dragging modes such as dispersing speech, and then learn the corresponding word related network figure of this new centre word object.The structure of the corresponding word network chart of said picture is identical with word related network figure, is used for the relation of dispersing between the speech of picture and picture is organized into a network chart, shows user learning visually.Said correlogram section module is used to show several image contents that are associated with centre word.Said word explanation district module is used for phonetic symbol, explanation and pronounceable pronunciation button of display centre speech.

Said KEY value computing module is used to calculate the KEY value that each disperses speech (or picture) or centre word; This KEY value is an integer numerical value; Said computing method of dispersing speech KEY value are: with said disperse the index (0-9 position) of speech in dispersing speech module or pictorial information module, this disperse speech corresponding disperse attribute (promptly dispersing the relation of speech and centre word) corresponding relationship numeral (10-13 position); After reaching index (14-31 position) combination of this centre word of dispersing the speech correspondence in the centre word module, an integer numerical value that obtains after the basic displacement computing through computing machine.Need to prove that the KEY value calculating method of centre word is identical with the KEY value calculating method of dispersing speech, but the vocabulary content that so can obtain centre word or disperse speech through the KEY value is all filled in the 0-13 position of centre word with 1.Each object storage in the corresponding word network chart of said word related network figure and picture unique KEY value information.

Said KEY value parsing module is used for selecting or drag to disperse the user resolving this KEY value of dispersing speech and structure when speech is learnt by said word and disperse the word related network figure that speech is formed.

Said voice module is used for carrying out articulation according to the audio files name of the word entry content that reads, and makes the user better grasp pronunciation of words.

Said word is searched and is learned the content that the resources bank module is used for all words of stocking system; Comprise entry, phonetic symbol, explanation, audio files and each word of each word corresponding disperse characteristics such as speech and picture; Its concrete structure is as shown in Figure 3; Comprise the centre word module, disperse module, the said module of dispersing comprises and disperses speech module, pictorial information module, image content library module and picture entry content module.Said centre word module comprises centre word index area module and centre word content regions module.Said centre word content regions module comprises entry module, phonetic symbol module, explanation module, audio files name module; And disperse attribute module; The entry content that said centre word module is used for storing one or several existing all words of dictionary comprise entry, phonetic symbol, explanation, audio files name and the word of each word corresponding disperse attribute, the said attribute of dispersing comprises that corresponding each of each word dispersed the relation mark number of attribute, this is dispersed properties point and disperses index address corresponding in glossarial index district module or the pictorial information index area module.The said relation mark of dispersing attribute number is used for each word of mark and it disperses the relation between speech or the picture, for example association, similar, near justice, antisense, variation, relations such as sound is near, shape is near, derivation, collocation, phrase.Said centre word index area module stores the index address of each word entry content of storing in the centre word content regions module, each index address points to unique word entry content of centre word content regions module.The said speech module of dispersing comprises and disperses glossarial index district module and disperse speech content regions module.The said speech content regions module of dispersing has stored in the said centre word module the corresponding entry content of dispersing speech of all words and comprises each and disperse the entry of speech, phonetic symbol, explanation, wherein phonetic symbol be interpreted as option.Each word is corresponding in the said said centre word module of having dispersed glossarial index district module stores disperses the total number of speech entry and disperses each that store in the speech content regions module and disperse the index address of speech entry content, and what each index address pointed to unique correspondence of dispersing speech content regions module disperses speech entry content.Said pictorial information module comprises pictorial information index area module and pictorial information content regions module.Said pictorial information content regions module has stored the corresponding pictorial information of all words in the said centre word module; Comprise the index address of each picture such as the entry index of little picture address and each entry content of big picture address, the corresponding entry number of picture and picture correspondence, corresponding entries content in the said entry index picture entry content module.Said pictorial information index area module stores the index address of each pictorial information of storing in the total number of picture that each word is corresponding in the said centre word module and the pictorial information content regions module, unique pictorial information of each index address sensing pictorial information content regions module.Said image content library module has stored the corresponding concrete image content (content that comprises big picture and little picture) of each word in the said centre word module.Said picture entry content module has stored the corresponding entry content of dispersing speech of each picture and has comprised each and disperse the entry of speech, phonetic symbol, explanation, audio files that this module concrete structure is identical with the said speech module of dispersing, repeat no more here.Comprise that corresponding each of each word disperse the relation mark number of attribute, disperse glossarial index and picture indices owing to disperse attribute in the said centre word module; Said glossarial index and the picture indices of dispersing pointed to respectively and dispersed index address corresponding in glossarial index district module and the pictorial information index area module; Thereby after in the centre word module, inquiring a word, can further from disperse speech module and pictorial information module, obtain be associated with this word disperse speech and pictorial information.Little picture address in the said pictorial information module and big picture address all point to picture stored content in the image content library module; To obtain little picture or big image content; Said little picture is used for showing that in the correlogram section said big picture shows in the speech barrier as centre word.The corresponding entry index of picture in said pictorial information module picture entry content module, be used for from picture entry content module take out picture corresponding disperse the speech content.

Fig. 2 is that the process flow diagram of method is searched in word association of the present invention.For the ease of describing, only show the part relevant here with the present invention.

Step S1: the word to be searched that receives user's input;

The receiver module of searching system through word association of the present invention can receive the word that the user imports, and after the user imports a word, is received by receiver module earlier, changes step S2 then over to the word that the user imports is mated.

Step S2: search the said word to be searched of coupling in the resources bank module at word;

Before address, said word is searched and is learned the resources bank module and stored the content of all words in the system, comprise entry, phonetic symbol, explanation, audio files and each word of each word corresponding disperse characteristics such as speech and picture.Preferably; Can be with one or several existing dictionaries (such as new class mark dictionary etc.) as basic dictionary; Adopt the characteristics such as entry, phonetic symbol, explanation of all words in it; And conclude corresponding the dispersing speech and/or increase the corresponding picture of each word of each word, deposit word then in the lump in and search in the resources bank module to form the comprehensive word resources bank of a system.

Because resources bank module stores searched in word word entry content abundant, can be related and the corresponding information such as speech entry content and image content of dispersing of each word; And all entries are all according to GBK ISN rank order from small to large, so step S2 specifically can adopt dichotomy to come the word to be searched of match user input.The processing procedure of said dichotomy is as shown in Figure 4; At first import according to the ordering rule process user; Confirm two subindex then, take out the corresponding word of index and also the word of this word and user's input is compared, if this word is identical with the word of user's input; Then take out the entry content of this word, then mate successfully; If this word is different with the word of user's input, confirm again that then two subindex continue coupling, till success or failure.Because dichotomy is a prior art, omits further specifying it here.

Step S3: judge whether to search to learn in the resources bank module to match said word to be searched, successfully then change step S4 over to, then obtain with the said immediate word of the word meaning of a word to be searched and change step S4 over to if mate to fail if mate at word; Said step S4 comprises:

Step S41: search to learn the resources bank module from word and read the word entry content that matches; And add up the corresponding number of dispersing attribute of this word, each is dispersed, and all disperse the sum of speech under the attribute, disperse that all disperse the sum of speech under the attribute thereby obtain all;

Step S42: judge that all disperse under the attribute that all sums of dispersing speech are whether ultra to allow the word number that shows to single page, then get into step S5, show that all disperse that all disperse speech under the attribute otherwise get into step S6 if surpass;

In order to raise the efficiency; Match the entry content that generally can from the centre word module, transfer word behind the word earlier; Be the attribute of dispersing of entry, phonetic symbol, explanation, audio files name and word correspondence, and then, read more detailed content according to user's needs.Disperse described in the step S41 attribute number, each disperses under the attribute all sums of dispersing speech and can obtain from dispersing the attribute module of centre word module stores, promptly through calculating disperse store in the attribute module can show centre word disperse with it relation mark number of speech relation, and this relation mark number under the index address number that comprises draw.Said relation mark number refers to each and disperses the corresponding digital code of attribute, disperses attribute in order to distinguish association, synonym, antisense etc.The dispersing in the attribute module structure of for example a certain centre word " a " exists disperses speech and is labeled as and comprises in " phrase " corresponding relationship numeral, the phrase attribute that 3 are dispersed glossarial index address (like the index address of " a lot of ", " a bike ", " a dog "); Also exist disperse speech be labeled as " similar " corresponding relationship numeral, with comprising in the generic attribute that 1 is dispersed glossarial index address (like the index address of " an "); Then the number of dispersing attribute of this word " a " is 2; Under the phrase attribute disperse speech add up to 3; The speech of dispersing with under the generic attribute adds up to 1, and all disperse the 3+1=4 that adds up to of speech under the attribute thereby all of this word " a " are dispersed.Allow the word number that shows if all of this word " a " are dispersed under the attribute the ultra single page that arrived of all sums of dispersing speech, then need get into step S5, show that all disperse that all disperse speech under the attribute otherwise get into step S6.

Step S5: confirm to need show disperse attribute and this disperses the speech of dispersing that needs demonstration attribute under;

Because the restriction on the embedded handhold equipment hardware; After in step S4, being deployed into the entry content of word; Whether all that judge this word are dispersed under the attribute all and are dispersed speech and can show at one page and finish; Then must selection need dispersing attribute and dispersing speech of demonstration if not, make the word and a plurality of speech of dispersing that are deployed into partly or entirely to be presented on the hand-held electronic facility for study according to the learning demand of individual subscriber.Said step S5 specifically comprises step:

S501: the relation mark that confirm to need shows number, thus confirm that this relation mark number needs the speech of dispersing that shows down;

The front is addressed; The dispersing of each word has this word in the attribute module structure and it disperses the relation between the speech; For example association, similar, near justice, antisense, variation, relations such as sound is near, shape is near, derivation, collocation, phrase, these relations can as be dispersed the speech mark through relation mark number and reflected.Therefore, can select only to show that one or more relation marks number corresponding down all disperse speech, to improve system handles speed.For example, can select only to show relation mark that a word has number for " nearly justice " and " antisense " disperse attribute under all disperse speech, promptly select all near synonym and all antonyms of demonstration word.To show under the default situations of the present invention underlined all down corresponding words, can certainly adopt other settings, be merely for example here, be not limited to the present invention.

Step S6: obtain to be shown dispersing speech and calculate its KEY value, structure is centre word, disperses word related network figure and the pictures (like Fig. 6) that speech is peripheral speech and be shown to the user with the word that matches;

Following elder generation describes structure and the effect of word related network figure of the present invention, and then the concrete processing procedure of step S6 is detailed.The present invention be not as traditional approach each page zero show word diffusingly and disperse speech, but, show the user through word related network figure the word and the relation of dispersing between the speech being organized on each page vividly.Said word related network is strivied for survival at several objects, object storage the word that matches (hereinafter to be referred as centre word) entry content and the attributes such as KEY value of dispersing speech.Particularly, said word related network strive for survival a centre word object that is positioned at the center with disperse the speech object through what lines were connected with the centre word object around several are positioned at.Each object can be controlled; For example the user gets final product contents such as Direct Learning vocabulary, phonetic symbol, pronunciation, explanation through clicking the centre word object and/or dispersing the speech object; Can also make it become new centre word object through dragging the mode of dispersing the speech object; And then forming new word related network figure, this new word related network figure has reacted new centre word and the corresponding relation between the speech of dispersing thereof, and supplies the user further to select study.

The KEY value of storing in the object of said word related network figure has been reacted said and has been dispersed the index of speech in dispersing speech module or pictorial information module, this disperses the corresponding relation mark of dispersing attribute number (promptly this disperses the relation of speech and centre word) of speech; Reach this and disperse the corresponding index address of centre word in the centre word module of speech, be used to discern the object of user's operation.The prototype structure of KEY value is as shown in table 1; The KEY value can be used 4 byte positive integers; I.e. 32 binary digits; The 0-9 position is used for depositing disperses speech in the memory address of dispersing glossarial index district module or pictorial information index area module, and the 10-13 position is used for depositing relation mark number, the 14-31 position of dispersing speech and centre word and is used to deposit the memory address of centre word in said centre word module.For example hypothesis has individual centre word " desert "; The index address that it is searched in the centre word module of learning in the resources bank module at word is 500 (not converting scale-of-two into); And it has disperses speech mark " association " and association and disperses speech " forest " under the attribute; " forest " index address in dispersing the speech module is 4 (not converting scale-of-two into); Suppose association, similar, near justice, antisense, variation, sound is near, shape is near, the numbering of derivation, collocation, ten kinds of relations of phrase is respectively 0-9; Then the KEY value of this forest can be filled like this: (need be converted into the scale-of-two filling that computing machine can be discerned, the index address of expression Forest in dispersing the speech module is 4) filled with 4 in the 0-9 position in 4 bytes, and (expression association attribute) filled with 0 in the 10-13 position; (need be converted into the scale-of-two filling that computing machine can be discerned, the corresponding index address of centre word desert in the centre word module of expression Forest is 500) filled with 500 in the 14-31 position.From a KEY value, can resolve the following information that obtains: the reaction of this KEY value disperse index address, this relation of dispersing speech and centre word and centre word the index address in centre word module of speech in dispersing the speech module.For example; When the user clicks " forest " this object; System will receive with the KEY value to be the signal of content; Just can learn " forest " index address in dispersing the speech module and " desert " index address in the centre word module through resolving the KEY value, thereby the vocabulary content of taking out " forest " supplies user learning.Said parsing KEY value refers to need not to give unnecessary details through the readjustment of the function under the signal under the QT language and mechanism slot or other Languages mode here.Each object storage unique KEY value information.

Need to prove that the KEY value calculating method of centre word is basic identical with the KEY value calculating method of dispersing speech, but in the KEY value prototype structure of centre word, fill with " 1 " all its 0-13 position.

Table 1KEY value structure

Step S6 disperses the speech sum to what need to show, need to judge whether paging, if desired paging Pagination Display then; And each page or leaf is through making up word related network figure display centre speech and dispersing word information; When making up word related network figure, need to calculate the KEY value of dispersing speech, and it is saved on the object; Then object corresponding entries content is joined among the word related network figure, make object can be operated (click or drag) by the user.Below step S6 is elaborated, as shown in Figure 5, said step S6 specifically comprises:

Step S600: obtain the pairing number of dispersing attribute of the word that matches, each disperse under the attribute all disperse the speech sum, all disperse that all need show under the attribute disperse the speech sum, judgement needs to show disperses the speech sum and whether surpasses single page and allow the word number that shows;

Step S601: calculating needs the number of pages of paging when surpassing the word number of single page permission demonstration, not paging when being no more than the word number of single page permission demonstration;

Step S602: a certain mark of dispersing attribute that needs in the attribute to show of dispersing of the word that matches is changed to current mark;

Step S603: the speech sum of dispersing that dispersing under the current mark shown in the attribute is changed to 0, all that have shown is dispersed under the attribute all disperse the speech sum and be changed to 0;

Step S604: all that will show are dispersed under the attribute all and are dispersed the speech sum and disperse the comparison of speech sum with all disperse that all need show under the attribute; Judgement need to show all disperse speech and whether read and finish; If then finish the entire process process, then get into step S605 if not;

The present invention is provided with all that shown and disperses under the attribute all to disperse speech sum initial value be 0; Every shown one disperse speech then this value add 1; Therefore when all that have shown disperse under the attribute all disperse the speech sum greater than all disperse that all need show under the attribute disperse the speech sum time; Just can judge that all that need to show disperse speech and read and finish, finish the entire process process this moment.Should be understood that initial value can be provided with as required, the Rule of judgment that different initial value is corresponding (greater than, less than, non-greater than, non-less than, equal) also different.

Step S605: judge that current page shows that whether the word number has reached the word number that single page allows demonstration, if then jump to down one page and change step S604 over to, then gets into step S606 if not;

Step S606: the sum of dispersing speech that dispersing under the current mark shown in the attribute and this are dispersed all need show under the attribute the sum of dispersing speech relatively; Judge that under the current mark all disperse speech and whether read and finish; Represent next to disperse next mark of attribute and jump to step S604 if then current mark is revised as to point to, then to get into step S607 if not;

The present invention is provided with that dispersing under the current mark shown in the attribute, and to disperse speech sum initial value be 0; Every shown under the current mark disperse speech the time then this value add 1; Therefore if the speech sum of dispersing that has shown in the attribute of dispersing under the current mark is dispersed the sum of dispersing speech that all need show under the attribute greater than this; Just can judge that under the current mark all disperse speech and read and finish, this moment current mark is revised as to point to and represent next to disperse next mark of attribute and jump to step S604.Should be understood that initial value can be provided with as required, the Rule of judgment that different initial value is corresponding (greater than, less than, non-greater than, non-less than, equal) also different.

Step S607: obtain under the current mark one of not showing and disperse speech and calculate its KEY value; This disperses speech and KEY value thereof through an object storage then, and this object corresponding entries content is joined as a node among the word related network figure of current page and show;

Step S608: the speech sum of dispersing that dispersing under the current mark shown in the attribute adds up 1, and all that will show are simultaneously dispersed under the attribute all and dispersed the speech sum and add up 1;

Step S609: current mark is revised as to point to changing step S604 over to after representing next next mark of dispersing attribute.

For make word related network figure more symmetrically the display centre speech with disperse speech; Avoid dispersing the appearance that speech only is presented at the situation at random that word related network figure one side, opposite side do not show, the position of the object of can arranging when in step S607, object corresponding entries content being joined word related network figure.For example suppose that a word related network figure can show that at most 1 centre word object and 12 disperse the speech object; The position that can place comprise a preset centre coordinate and 1 to No. 12 totally 12 uniform sequentials be arranged in the coordinate of dispersing around the centre coordinate; Then the centre word object fixed is presented on the centre coordinate position when arranging the position of object; Dispersing the speech object then selects to be presented at 1 to No. 12 and disperses on the coordinate according to the speech number of dispersing that every page of needs show; For example suppose that every page of speech number of dispersing that needs to show is N, then

1) when N=1, gets 1 at random and disperse coordinate position and show and disperse speech object corresponding entries content;

2) when N=2, get earlier 1 coordinate position at random, more clockwise at interval 5 numbers get another coordinate position, disperse coordinate position for 2, No. 8 and show and disperse speech object corresponding entries content such as getting;

3) when N=3, get earlier 1 coordinate position at random, more clockwise at interval 3 numbers get a coordinate position, 3 numbers are got a coordinate position at interval counterclockwise, disperse coordinate position for 2,6, No. 10 and show and disperse speech object corresponding entries content such as getting;

4) when N=4, earlier get 1 coordinate position at random, clockwise more every interval 2 numbers are got a position, disperse coordinate position for 1,4,7, No. 10 and show and disperse speech object corresponding entries content such as getting;

5) when N=5, earlier get 1 coordinate position at random, clockwise more every interval 1 number is got a position, get two after every again interval 2 numbers get a position, disperse coordinate position for 1,3,5,8, No. 11 and show and disperse speech object corresponding entries content such as getting;

6) when N=6, earlier get 1 coordinate position at random, clockwise more every interval 1 number is got a position, disperses coordinate position for 1,3,5,7,9, No. 11 and shows and disperse speech object corresponding entries content such as getting;

7) when N=7; Get earlier 1 coordinate position at random; Clockwise more every interval 1 number is got a position, gets and gets 2 follow-up positions after 5 more continuously, disperses coordinate position for 1,3,5,7,9,10, No. 11 and shows and disperse speech object corresponding entries content such as getting;

8) when N=8, object is opposite when arranging just with N=4, disperses coordinate position for 2,3,5,6,8,9,11, No. 12 and shows and disperse speech object corresponding entries content such as getting;

9) when N=9, object is opposite when arranging just with N=3, disperses coordinate position for 1,3,4,5,7,8,9,11, No. 12 and shows and disperse speech object corresponding entries content such as getting;

10) when N=10, object is opposite when arranging just with N=2, disperses coordinate position for 1,3,4,5,6,7,9,10,11, No. 12 and shows and disperse speech object corresponding entries content such as getting;

11) when N=11, object is opposite when arranging just with N=1, disperses coordinate position for 2,3,4,5,6,7,8,9,10,11, No. 12 and shows and disperse speech object corresponding entries content such as getting;

12) when N=12, get promptly to get for 1-12 number and all disperse coordinate position and show and disperse speech object corresponding entries content.

Should be understood that, if can make disperse the speech object be presented at symmetrically word related network figure the centre word object around, the scheme of the object of arranging described herein only is used for giving an example, and is not limited to the present invention.

Step S6 is when showing word related network figure; The pictures that can also have at picture concerned module display centre speech; Concrete grammar is: the picture relation mark of dispersing in the attribute module structure number through centre word points to the pictorial information module with picture indices; Then according to the little picture address in the image content structure of pictorial information module stores; Point to the image content module, and then obtain the corresponding little image content of centre word, obtain behind all little image contents little picture branch apportion is shown to the user.Need to prove; The little picture of storing in image content module branch's apportion in the module of correlogram section shows (like the correlogram section module among Fig. 6-Figure 11), and then module shows (like the speech barrier module among Figure 11) to big picture in the speech barrier as the centre word object in the word network chart of picture correspondence.

The user can carry out three kinds of operations after step S6 has shown word related network figure and the pictures in the module of correlogram section in the module of speech barrier:

Operation one: select to disperse the speech object among the word related network figure, system resolves the KEY value of dispersing speech through modes such as signal and mechanism slot or function readjustments, and the relation (like Fig. 7 and Fig. 8) of explanation or itself and the centre word of speech is dispersed in demonstration.

Because dispersing the speech object storage has the KEY value of dispersing speech; The KEY value is with dispersing the index of speech in dispersing speech module or pictorial information module, the corresponding relation mark of dispersing attribute number; And this disperses index combination back integer numerical value that through the basic displacement computing of computing machine gets of the corresponding centre word of speech in the centre word module; Therefore system's KEY value of dispersing speech through parsing can be learnt and disperse the index address of speech in dispersing the speech module, thereby can from disperse the speech module, take out the entry content of dispersing speech.Disperse in the KEY value of speech and also have the relation of dispersing speech and centre word, so system also can feed back to the user with the relation of dispersing speech and centre word such as near synonym relation, antonym relation etc. through resolving the KEY value.

Operation two: select the picture in the pictures; The KEY value of system analysis picture; Obtain the index address (this index address points to corresponding little image content in the image content library module) that little picture is stored in the pictorial information content module; Can know by the storage organization of pictorial information content module the little picture of storing in the pictorial information content module index address previous bytes store be the index address (this index address points to the big image content in image content library module) of big picture; What several bytes were thereafter stored respectively is this picture corresponding entries sum, the index address of each entry in picture entry content module, shows that after having resolved above-mentioned information with big picture be the corresponding word network chart (like Fig. 9) of centre word.

The method of the KEY value of said calculating picture is similar with the KEY value method that speech is dispersed in calculating; Be about to picture index (0-9 position), this picture in said pictorial information index area module corresponding disperse the corresponding numeral (10-13 position) of attribute (being picture and the relation of centre word); And after index (14-31 position) combination of the centre word of this picture correspondence in the centre word module, obtain an integer numerical value after the basic displacement computing through computing machine.The structure of the corresponding word network chart of said picture is identical with word related network figure, is used for the relation of dispersing between the speech of picture and picture is organized into a network chart, shows user learning (like Figure 10) visually.The building process of the corresponding word network chart of said picture is similar with word related network figure; It promptly at first is centre word with the picture; From picture entry content module, obtain the speech of dispersing of picture correspondence then; The KEY value of speech is dispersed in calculating, will disperse speech and KEY value thereof then and be saved in the object, afterwards the object corresponding entries is joined respectively in the corresponding word network chart of picture as a node.Wherein also can arrange and disperse the display position of speech object, method is with the above.

Operation three: change a certain position of dispersing the speech object in the corresponding word network of word related network figure and/or the picture speech, make it be in the centre word coordinate position and become new centre word (like Figure 11 and 12);

In operation three, change the position disperse the speech object and be embodied in the behavior of dragging, drag promptly that wherein some other is dispersed lexeme and puts fixedly when dispersing speech, its original process of dispersing the coordinate fixed position got back in the trailing speech of dispersing.The node that the position of speech object is dispersed in said change drags the slip implementation method and can adopt following two kinds of methods:

1) two displacement component methods: when disperse the speech object dragged leave that it is fixed original disperse coordinate position (promptly this disperses the original fixed position that speech is arranged) and arrive new disperse coordinate position after, it will get back to its original coordinate position of dispersing with the speed of v.V=disperses the centre coordinate and original distance/2 of dispersing between the regional centre coordinate position of coordinate position in zone, the current position of speech object; Because the original centre coordinate of dispersing coordinate position zone is constant; Therefore v constantly changes according to the variation of dispersing speech object current location; It is far away more to disperse the original coordinate position position of dispersing of speech object current location distance, and the v value is big more, and it is fast more promptly to disperse the speed that the speech object moves; Dispersing speech object current location distance, original to disperse coordinate position near more, and the v value is more little, and it is slow more promptly to disperse the speed that the speech object moves.Finally, disperse the speech object and get back to its original dispersing on the coordinate position position.

2) physical mechanics method: there is repulsive interaction in each adjacent dispersing between the speech object on the one hand, and what suppose repulsive interaction is F1 with joint efforts, disperses on the other hand between speech object and the centre word object to connect through lines, therefore the tension force F2 of existence stretching.Disperse the speech object for each, it is static in the time of F1=F2, to disperse the speech object, moves along the resultant direction of F1 and F2 otherwise disperse the speech object.Calculate the F1 that each disperses the speech object, then disperse the speech object and move along the resultant direction of F1 and F2 if F1 is not equal to F2, up to each disperse the speech object static till.What need explanation is; This method is owing to disperse lexeme and also put and change dragging when dispersing speech centre word position and other thereupon; The equilibrium position of each node is depended on the position relation of each node fully; Automatically calculate and making a concerted effort of receiving be 0 up to all nodes and promptly reach equilibrium state, the resource that so consumes is more, and processing speed is caused certain influence.

Because the resource-constrained of CPU in the hand-held electronic facility for study, so the above-mentioned two displacement component methods of normal employing are handled.

In above-mentioned two displacement component methods; Set the coordinate position of centre word and fix, wherein some when dispersing speech when dragging, only trailingly disperse the speech motion; To disperse speech all static and centre word is with other; When this is dispersed speech (dragging speech) and is dragged in the centre word zone (central area of centre word is dragging in the speech scope or dragging the speech central area in the centre word scope), then this is dispersed speech and switches to centre word, gets into step S7;

Step S7: when the centre word object among the word related network figure changes, search to learn in the resources bank module at word and mate new centre word again;

Step S8: judge whether to match the word identical with new centre word; Successfully then be transferred to step S4 if mate, promptly making up and showing with said new centre word is that the speech of dispersing that centre word and needs thereof show is word related network figure, structure and the demonstration pictures related with new centre word that peripheral speech constitutes;

Step S9: among the step S8 if the KEY value of new centre word is then resolved in coupling failure, judge its whether be in the pictures a certain picture correspondence disperse speech, if then do not carry out any operation; Then show the word related network figure that centre word that this is new and old centre word constitute if not, demonstration is exchanged in new, the old centre word position that is about among the word related network figure of step S7 centre word object before changing, and changes step S6 over to.

Explanation about step S7-S9 is following: for example; When the user drag be a certain centre word object " a " corresponding disperse speech object " a lot of "; Then this disperses speech object " a lot of " becomes new centre word object; System searched to learn in the resources bank module at word and mated new centre word " a lot of " again this moment, if coupling failure then resolve the KEY value of " a lot of " judges that whether " a lot of " be the speech of dispersing of old centre word object " a " correspondence; Judged result is for being; Then show " a lot of " with " a " and word related network figure, (" a lot of " is centre word, and " a " is the speech of dispersing of " a lot of ") exchanged in " a " and " a 1ot of " position that among the word related network figure of original " a ".

Need to prove; Releasing representative in the district at figure disperses the icon of attribute and can be included in the zone of a square frame or a circle or other shape; Shading can be filled in this zone; And different icons is filled the shading of different colours, same centre word in the module of speech barrier with disperse speech and all can be contained in the zone of a square frame or circular or other shape, can also fill the shading of different colours.For ease of discerning the different attributes of dispersing, identically disperse under the attribute all and comprise the color of each shading of dispersing the speech zone and disperse speech all to adopt with the color of centre word line and scheme to release and comprise the regional shade color that corresponding figures releases in the district and be consistent.

Need to prove; When the centre word in speech barrier is dragged; The same described identical to dispersing two displacement component methods of speech, after centre word is dragged to new coordinates regional, according to its speed that moves of distance calculation of the central point of the central point of centre word reposition and centre word original fixed position; Finally; Centre word is got back to its original fixed position, gets back in the process of original fixed position in process that drags centre word and centre word, according to centre word center position coordinates and the line of dispersing the center position coordinates real-time rendering of speech.

In sum, word association of the present invention search method not only can match user the word of input, can also word that match and relevant conjunctive word and the picture of this word be fed back to the user, supply the user to select to learn.Owing to made up the corresponding word network chart of word related network figure and picture, thus clearly perception of user, learn each inquiry word had disperses speech and picture and the relation between them, strengthen learning impression.The user through click in the network chart disperse speech, picture can be learnt association knowledge, disperses speech and picture also can be learnt new centre word content with further facilitating through dragging.Can realize making things convenient for the user to carry out the related study of word, contrast study, disperse study like this, improve learning efficiency and results of learning.

The above is merely the preferred embodiments of the present invention, is not limited to the present invention, and for a person skilled in the art, the present invention can have various changes and variation.All any modifications of within spirit of the present invention and principle, being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims

1. method is searched in a word association, comprises the steps:

Steps A: the word to be searched that receives user's input;

It is characterized in that also comprising:

2. method is searched in word association according to claim 1; It is characterized in that; Said step B also comprises: if search when learning in the resources bank module coupling less than said word to be searched at said word, then obtain the entry content with the immediate word of the said word meaning of a word to be searched.

3. method is searched in word association according to claim 2, it is characterized in that:

After matching said word to be searched, read the entry content of the word that matches, add up the corresponding number of dispersing attribute of this word, each is dispersed, and all disperse the sum of speech under the attribute, obtain all and disperse that all disperse the sum of speech under the attribute;

Judge that whether ultra all disperse under the attribute all sums of dispersing speech word number of showing of allowing to single page; If surpass and then to confirm several and corresponding with the said word that matches disperse attribute and this disperses the speech of dispersing under the attribute, be used for showing at said word related network figure.

4. method is searched in word association according to claim 3, it is characterized in that: after making up said word related network figure, and structure and demonstration and the related pictures of said word to be searched.

5. method is searched in word association according to claim 4, it is characterized in that also comprising step:

If the KEY value of said new centre word is then resolved in coupling failure; Judge its whether be in the said pictures a certain picture corresponding disperse speech; If then do not carry out any operation, otherwise show the word related network figure that said new centre word and old centre word constitute.

6. method is searched in word association according to claim 5, it is characterized in that, said step C specifically comprises:

7. method is searched in word association according to claim 6; It is characterized in that; Said computing method of dispersing speech KEY value are: with saidly disperse the index of speech in dispersing speech module or pictorial information module, this disperses corresponding relation mark of dispersing attribute of speech number; After reaching index combination of this centre word of dispersing the speech correspondence in the centre word module, an integer numerical value that obtains after the basic displacement computing through computing machine.

8. method is searched in word association according to claim 7, it is characterized in that, said word related network figure and pictures are selected study, specifically comprise:

9. method is searched in each described word association according to claim 6 to 8, it is characterized in that: the speech sum of dispersing that shows as required when among the said step C7 object being joined word related network figure is arranged and is write down the display position of each object on screen;

10. system is searched in a word association, comprising:

Resolve the entry module, be used to resolve the word entry content that reads;

It is characterized in that also comprising:

11. system is searched in word association according to claim 10; It is characterized in that: said centre word module comprises centre word index area module and centre word content regions module; Said centre word content regions module comprises entry module, phonetic symbol module, explanation module, audio files name module; And disperse attribute module; The entry content that said centre word module is used for storing one or several existing all words of dictionary comprise entry, phonetic symbol, explanation, audio files name and this word of each word corresponding disperse attribute; Saidly disperse that attribute refers to association, similar, near justice, antisense, variation, sound is near, shape is near, one or several attribute in derivation, collocation, phrase and the picture; Said each disperse the corresponding unique relation mark of attribute number, said centre word index area module stores the index address of each word entry content of storing in the centre word content regions module, each index address points to the word entry content of unique correspondence in centre word content regions module.

12. system is searched in word association according to claim 11; It is characterized in that: the said speech module of dispersing comprises and disperses glossarial index district module and disperse speech content regions module; The said speech content regions module of dispersing has stored in the said centre word module the corresponding entry content of dispersing speech of all words and comprises each and disperse the entry of speech, phonetic symbol, explanation; Corresponding this of each word dispersed and dispersed the total number of speech entry under the attribute and disperse each that store in the speech content regions module and disperse the index address of speech entry content in the said said centre word module of having dispersed glossarial index district module stores, and what each index address pointed to unique correspondence of dispersing speech content regions module disperses speech entry content.

13. system is searched in word association according to claim 12; It is characterized in that: said pictorial information module comprises pictorial information index area module and pictorial information content regions module; Said pictorial information content regions module has stored in the said centre word module index of each corresponding entry content of the corresponding entry number of index address, picture that the corresponding pictorial information of all words comprises each picture and picture; Corresponding entries content in the said index picture entry content module; Said pictorial information index area module stores the index address of each pictorial information of storing in the total number of picture that each word is corresponding in the said centre word module and the pictorial information content regions module, the pictorial information of unique correspondence of each index address sensing pictorial information content regions module.

14. system is searched in word association according to claim 13, it is characterized in that: said image content library module has stored the corresponding concrete image content of each word in the said centre word module.

15. system is searched in word association according to claim 14, it is characterized in that: said picture entry content module has stored each corresponding entry content of dispersing speech of each picture and has comprised each and disperse the entry of speech, phonetic symbol, explanation, audio files name.

16. system is searched in word association according to claim 15; It is characterized in that: disperse attribute module in the said centre word module and comprise that corresponding each of each word dispersed the relation mark number of attribute, this is dispersed properties point and disperses index address corresponding in glossarial index district module or the pictorial information index area module; The index address of picture points to picture stored content in the said image content library module in the said pictorial information content regions module; The said picture entry of picture corresponding entries index content module in the said pictorial information content regions module, the word audio files name module in the said centre word module is pointed to sound-content corresponding in the voice module.

17. system is searched in word association according to claim 16, it is characterized in that: said interface display module comprises that figure releases district's module, speech barrier module, correlogram section module and word explanation district module.

18. system is searched in word association according to claim 17; It is characterized in that: said figure releases district's module and is used to show the mark of dispersing the attribute correspondence that word had that searches; Comprise association, similar, near justice, antisense, variation, sound is near, shape is near, in the derivation, collocation, phrase one or more; Institute's predicate barrier module is used to show by word and corresponding disperses word related network figure that speech constitutes and disperses the corresponding word network chart of picture that speech constitutes by picture and corresponding; Said correlogram section module is used to show the image content that is associated with the word that searches, and said word explanation district module is used to show phonetic symbol, explanation and the pronunciation button of the word that searches.