Question and answer matching process and deviceTechnical field
The present invention relates to intelligent answer technical fields, more particularly, to a kind of question and answer matching process and device.
Background technique
With the development of science and technology, conveniently question answering system also gradually appears in people's daily life, question and answer systemSystem can be according to providing corresponding answer automatically the problem of user, and then realizes human-computer interaction.
Question answering system it is substantially a kind of find to put question to user in existing " problem-answer " set matchQuestion text, and its corresponding answer is presented to the user.The core concept of the system is the question sentence for proposing user and problemThe problem of recording in library carries out similarity calculation.The TF-IDF question sentence based on spatial model is mostly used in existing question answering system greatlySimilarity calculating method, however, the putd question to sentence of user is mostly shorter in human-computer interaction, and this method is closed when question sentence is shorterThe accuracy rate that keyword extracts is not high, and match time is long, after user's proposition problem, needs the long period that can just receive matchingAnswer, user experience be not high.
The lower and used time longer problem for the matched mode accuracy rate of the above-mentioned question and answer used in the prior art, at presentNot yet put forward effective solutions.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of question and answer matching process and device, to alleviate in the prior artThe matched mode of question and answer existing for accuracy rate is lower and used time longer problem.
To achieve the goals above, technical solution used in the embodiment of the present invention is as follows:
In a first aspect, the embodiment of the invention provides a kind of question and answer matching process, comprising: extract in input question sentence textKeyword；According to the keyword, object matching question sentence text is determined from library the problem of pre-establishing by the way of index filteringThis；Based on Lay Weinstein distance algorithm, determined from object matching question sentence text highest with the similarity of input question sentence textBest match question sentence text；According to the best match question sentence text, output answer text corresponding with input question sentence text.
With reference to first aspect, the embodiment of the invention provides the first possible embodiments of first aspect, wherein onStating the keyword extracted in input question sentence text includes: to segment to input question sentence text, generates word sequence；Remove word sequenceIn stop words, obtain entry；Using improved comentropy formula, the corresponding weight of each entry is calculated；After improvementComentropy formula are as follows:
Wherein, H (t) is the corresponding weight of entry t；ftkThe frequency in text k, n are appeared in for entry ttFor entry t appearanceFrequency in all text collections, N are the sum of text in text collection；By all entries according to obtaining after calculatingThe size of weight is ranked up, and obtains weight sequencing table；According to pre-set withdrawal ratio, extracts and close from weight sequencing tableKeyword.
With reference to first aspect, the embodiment of the invention provides second of possible embodiments of first aspect, wherein onIt states according to keyword, determines that object matching question sentence text includes: from library the problem of pre-establishing by the way of index filteringPredetermined keyword and default question sentence text according to the keyword in input question sentence text, and the problem of pre-establish in library itBetween index relative, obtain default question sentence text matching value corresponding with input question sentence text；Matching value is greater than preset matchingThe default question sentence text of threshold value is determined as object matching question sentence text.
The possible embodiment of second with reference to first aspect, the embodiment of the invention provides the third of first aspectPossible embodiment, wherein the above-mentioned keyword according in input question sentence text, and the problem of pre-establish it is pre- in libraryIf the index relative between keyword and default question sentence text, the matching corresponding with question sentence text is inputted of default question sentence text is obtainedValue include: using the problem of pre-establishing in library with input question sentence text in the identical predetermined keyword of keyword as match passKeyword；It is default in Traversal Problem library according to the predetermined keyword in problem base and the index relative between default question sentence textQuestion sentence text, to determine the number for the matching keywords for including in default question sentence text；That will include in default question sentence textNumber with keyword is as default question sentence text matching value corresponding with input question sentence text.
Second with reference to first aspect or the third possible embodiment, the embodiment of the invention provides first aspectsThe 4th kind of possible embodiment, wherein the foundation in above problem library includes: to preset default question sentence text, Yi JiyuThe default corresponding model answer text of question sentence text, and default question sentence text and model answer text are stored in problem base；Number-mark is established for each default question sentence text；Extract the corresponding predetermined keyword of each default question sentence text；It establishes defaultIndex relative between keyword and default question sentence text；Wherein, in index relative, predetermined keyword with include default keyThe number-mark that the one or more of word presets question sentence text is corresponding.
With reference to first aspect, the embodiment of the invention provides the 5th kind of possible embodiments of first aspect, wherein onIt states according to best match question sentence text, output answer text corresponding with input question sentence text includes: to judge best match question sentenceWhether the similarity of text reaches default similarity threshold；If so, it is corresponding to search best match question sentence text from problem baseModel answer text, using model answer text as the corresponding answer text output of input question sentence text；If not, from interconnectionNet searches the corresponding network answers text of input question sentence text, using network answers text as the corresponding answer of input question sentence textText output.
Second aspect, the embodiment of the present invention also provide a kind of question and answer coalignment, comprising: extraction module, it is defeated for extractingEnter the keyword in question sentence text；First determining module, for according to keyword, from pre-establishing by the way of index filteringThe problem of library in determine object matching question sentence text；Second determining module, for being based on Lay Weinstein distance algorithm, from targetWith the highest best match question sentence text of similarity determined in question sentence text with input question sentence text；Answer output module is usedAccording to best match question sentence text, output answer text corresponding with input question sentence text.
In conjunction with second aspect, the embodiment of the invention provides the first possible embodiments of second aspect, wherein onStating extraction module includes: participle unit, for segmenting to input question sentence text, generates word sequence；Stop words removal unit,For removing the stop words in word sequence, entry is obtained；Weight calculation unit, for utilizing improved comentropy formula, meterCalculation obtains the corresponding weight of each entry；Improved comentropy formula are as follows:
Wherein, H (t) is the corresponding weight of entry t；ftkThe frequency in text k, n are appeared in for entry ttFor entry t appearanceFrequency in all text collections, N are the sum of text in text collection；Sequencing unit, for pressing all entriesIt is ranked up according to the size of the weight obtained after calculating, obtains weight sequencing table；Keyword extracting unit is set in advance for basisThe withdrawal ratio set extracts keyword from weight sequencing table.
In conjunction with second aspect, the embodiment of the invention provides second of possible embodiments of second aspect, wherein onStating the first determining module includes: matching value acquiring unit, for and pre-establishing according to the keyword in input question sentence textThe problem of library in predetermined keyword and default question sentence text between index relative, obtain default question sentence text and input question sentenceThe corresponding matching value of text；First determination unit, the default question sentence text for matching value to be greater than to preset matching threshold value determineFor object matching question sentence text.
In conjunction with second aspect, the embodiment of the invention provides the third possible embodiments of second aspect, wherein onStating answer output module includes: judging unit, for judge the similarity of best match question sentence text whether reach preset it is similarSpend threshold value；Model answer output unit, for judging that the similarity of best match question sentence text reaches default similarity thresholdWhen, the corresponding model answer text of best match question sentence text is searched from problem base, is asked model answer text as inputThe corresponding answer text output of sentence text；Network answers output unit, in the similarity for judging best match question sentence textWhen not up to presetting similarity threshold, the corresponding network answers text of input question sentence text is searched from internet, by network answersText is as the corresponding answer text output of input question sentence text.
The embodiment of the invention provides a kind of question and answer matching process and devices, are extracting the keyword in input question sentence textAfterwards, index filtering by way of from problem base determine object matching question sentence text, with reduce in problem base with input question sentenceThe question sentence range that text matches, then it is determining highest most with the similarity of input question sentence text based on Lay Weinstein distance algorithmGood matching question sentence text, finally output answer text corresponding with input question sentence text.With the question and answer used in the prior artThe mode accuracy rate matched is lower and used time longer problem is compared, and method and device provided in an embodiment of the present invention can be shorterTime in corresponding with the question sentence answer of output, can not only shorten question and answer and match duration, but also accuracy rate can be promoted.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specificationIt obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention are in specification, claimsAnd specifically noted structure is achieved and obtained in attached drawing.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperateAppended attached drawing, is described in detail below.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior artEmbodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described belowAttached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative laborIt puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 shows a kind of question and answer matching process flow chart provided by the embodiment of the present invention；
Fig. 2 shows a kind of specific flow charts of question and answer matching process provided by the embodiment of the present invention；
Fig. 3 shows a kind of method for building up flow chart of problem base provided by the embodiment of the present invention；
Fig. 4 shows a kind of structural block diagram of question and answer coalignment provided by the embodiment of the present invention；
Fig. 5 shows a kind of specific block diagram of question and answer coalignment provided by the embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present inventionTechnical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather thanWhole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premiseUnder every other embodiment obtained, shall fall within the protection scope of the present invention.
Human-computer interaction gradually incorporates people's lives at present, from the equipment of primary response or can answer aiming at the problem that userIt is commonplace with software, realize that question and answer are matched by recording the question answering system for thering is " problem-answer " to gather substantially；SoAnd question and answer matching way in the prior art mostly uses greatly the TF-IDF Question sentence parsing calculation method based on spatial model to obtainFamily is taken, the accuracy rate of which is lower and the used time is longer, is based on this, a kind of question and answer matching process provided in an embodiment of the present inventionAnd device, the matched accuracy rate of question and answer can be improved, while shortening matching duration.It is situated between in detail to the embodiment of the present invention belowIt continues.
Embodiment one:
A kind of question and answer matching process flow chart shown in Figure 1, comprising the following steps:
Step S102 extracts the keyword in input question sentence text；The input question sentence text is that user passes through human-computer interactionThe question sentence text that mode inputs；When user uses voice input mode, then need to be converted to the phonetic problem of user into text textThis, then using the writing text as input question sentence text；
Step S104 determines target by the way of index filtering according to keyword from library the problem of pre-establishingWith question sentence text；The object matching question sentence text includes multiple texts, it is therefore intended that can reduce in advance in problem base with userThe pre-set text range that matches of input question sentence text, be conducive to promote subsequent question and answer matching speed；
Step S106 is based on Lay Weinstein distance algorithm, determines from object matching question sentence text and input question sentence textThe highest best match question sentence text of similarity；Lay Weinstein distance algorithm are as follows: grasped by editors such as insertion, deletion, replacementsMake, calculates from a character string and be transformed into the editor's number of minimum required for another character string, to measure two character stringsBetween similarity；Based on the algorithm, can fast and accurately be found from the object matching question sentence text screened in advance withThe highest matching question sentence of similarity for inputting question sentence text, using the matching question sentence as best match question sentence text；
Step S108, according to best match question sentence text, output answer text corresponding with input question sentence text.
In the above method of the present embodiment, after extracting the keyword in input question sentence text, pass through the side of index filteringFormula determines object matching question sentence text from problem base, to reduce the question sentence model to match in problem base with input question sentence textIt encloses, then the highest best match question sentence text of similarity with input question sentence text is determined based on Lay Weinstein distance algorithm, mostOutput answer text corresponding with input question sentence text afterwards.This method can export answer corresponding with question sentence in a relatively short period of timeCase can not only shorten question and answer matching duration, but also can promote accuracy rate.
Specifically, in the prior art mostly using the TF-IDF Question sentence parsing calculation method based on spatial model,This method is primarily adapted for use in the similarity for calculating longer sentence or document, and the accuracy rate of keyword extraction is carried out for short question sentenceIt is not high；But the question sentence that user is mentioned in human-computer interaction is usually shorter, therefore spatial model is based on used by the prior artTF-IDF Question sentence parsing calculation method cannot preferably reach the expected of user and answer；In addition, the TF- based on spatial modelIDF Question sentence parsing calculation method also needs to establish vector space model, and process is complex and the used time is longer, thus finally fromIt is longer to find the answer time to match with the input question sentence of user in problem base (or question answering system), in conjunction with speech recognition withAn important factor for particularity of man-machine answer, question and answer matching speed is also association user Experience Degree, in conclusion the prior art causesKeep user experience not high, and the process that the above method provided in an embodiment of the present invention obtains input question sentence text is simple, matchingUsed time is shorter, and is not limited by question sentence length, is suitable for short sentence, can effectively improve the matched accuracy rate of question and answer, gives userBring good experience.
In order to facilitate understanding with implementation, reference can be made to a kind of specific flow chart of question and answer matching process shown in Fig. 2, including withLower step:
Step S202 segments input question sentence text, generates word sequence；It is one that question sentence text dividing, which will be inputted,Input question sentence text after cutting can be known as word sequence by one individual word；
Step S204 removes the stop words in word sequence, obtains entry；To save memory space and improving search efficiency,Search engine can ignore certain words or word in index pages or processing searching request automatically, these words or word, which are referred to as, to be deactivatedWord, such as auxiliary words of mood etc. usually itself have no the word of meaning, can remove word according to the deactivated vocabulary pre-establishedStop words in sequence.
The corresponding weight of each entry is calculated using improved comentropy formula in step S206；Wherein, it improvesComentropy formula afterwards are as follows:
Wherein, H (t) is the corresponding weight of entry t；ftkThe frequency in text k, n are appeared in for entry ttFor entry t appearanceFrequency in all text collections, N are the sum of text in text collection；
The corresponding weight of each entry is calculated by above-mentioned improved comentropy formula, is facilitated subsequent based on eachThe corresponding weight of entry differentiates keyword, can preferably promote the accuracy rate for extracting keyword, and use comentropy formulaCalculating process it is relatively simple, the used time for obtaining result is shorter, helps to improve question and answer matching speed.
All entries are ranked up according to the size of the weight obtained after calculating, obtain weight sequencing table by step S208；It can sort, can also sort from small to large from large to small, according to the actual situation flexibly setting.
Step S210 extracts keyword from weight sequencing table according to pre-set withdrawal ratio；For example, setting mentionsTaking ratio is 30 percent, then highest preceding 30 percent keyword of weight, such as weight are extracted from weight sequencing tableSequencing table is that ranking, total record have 100 keywords, then extract preceding 30 keywords from large to small according to weight.This modeIt can effectively reduce the scope, help to promote subsequent question and answer matching efficiency.
In order to make it easy to understand, the embodiment of the invention provides the specific example of applying step S202 to step S210 a kind of,For example, input question sentence text is " Chinese four great classical masterpieces ", the word sequence of " China/tetra-/big/masterpiece " is obtained after participle, soAfter remove stop words, and the weight of each entry is calculated using average information entropy (i.e. above-mentioned improved comentropy formula), mostObtaining keyword eventually is { China, masterpiece }.
Step S212, according to the keyword in input question sentence text, and default key the problem of pre-establish in libraryIndex relative between word and default question sentence text obtains default question sentence text matching value corresponding with question sentence text is inputted.
Following present a kind of concrete implementation modes:
(1) using the problem of pre-establishing in library with the identical predetermined keyword of keyword in input question sentence text asWith keyword；
(2) according to the predetermined keyword in problem base and the index relative between default question sentence text, in Traversal Problem libraryDefault question sentence text, to determine the number for the matching keywords for including in default question sentence text；It will be wrapped in default question sentence textThe number of the matching keywords contained is as default question sentence text matching value corresponding with input question sentence text.
In addition, in order to make it easy to understand, the present embodiment gives a kind of example using above-mentioned implementation: assuming that inputQuestion sentence text has m keyword, then can be used and is initialized as 0, length is the one-dimension array of N to record each text in problem baseThe number k value for the designated key word for including, the index chain for m keyword for then including in traversal input question sentence are every to occur oneThe corresponding position of array is just added 1 by a text, after the completion of traversal, just obtains the k value of full text, which is matching value.
The default question sentence text that matching value is greater than preset matching threshold value is determined as object matching question sentence text by step S214This；
Default question sentence text is measured by above-mentioned matching value and inputs the similarity between question sentence text, it is as a result more quasi-Really reliably, and according to matching value the default question sentence text in problem base is screened in advance, can effectively reduce energy in problem baseEnough question sentence ranges with input question matching, facilitate the efficiency for promoting subsequent determining matched text, shorten match time.
Step S216 is based on Lay Weinstein distance algorithm, determines from object matching question sentence text and input question sentence textThe highest best match question sentence text of similarity；It, can be fast and accurately from the object matching screened in advance based on the algorithmFound in question sentence text with input question sentence text similarity it is highest match question sentence (same keyword for including is most),Using the matching question sentence as best match question sentence text.
Step S218, judges whether the similarity of best match question sentence text reaches default similarity threshold；If so, holdingRow step S220；If not, executing step S222；After determining best match question sentence text in problem base, this step can be withFinally examine the best text if appropriate for as matching result, without as the prior art finally find it is most suitableAnswer is blindly exported after the matching result of conjunction, causes to give an irrelevant answer, causes user experience not high.
Step S220 searches the corresponding model answer text of best match question sentence text, by model answer from problem baseText is as the corresponding answer text output of input question sentence text；Wherein, each default question sentence text is previously stored in problem baseSheet and corresponding model answer text.
Step S222 searches the corresponding network answers text of input question sentence text from internet, network answers text is madeFor the corresponding answer text output of input question sentence text.It can be directly defeated by the input question sentence of user by modes such as rustling sound enginesEnter into internet with Network Search answer text, when not finding the text to match with user's question sentence in problem base,Meet user demand by network answers text, promotes user experience.
Wherein, it is step S102 in Fig. 1 that the step S202 in Fig. 2 is corresponding to step S210；Step S212 in Fig. 2Corresponding with step S214 is the step S104 in Fig. 1；Step S216 in Fig. 2 is corresponding with the step S106 in Fig. 1；Fig. 2In step S218 it is corresponding to step S222 be step S108 in Fig. 1.
By executing the above-mentioned steps in Fig. 2, can fast and accurately obtain corresponding with the input question sentence text of userAnswer text, and then promoted user experience.
Further, a kind of establishment process of problem base is given in the present embodiment, specifically, shown in Figure 3A kind of method for building up flow chart of problem base, the foundation of problem base are referred to following step:
Step S302 presets default question sentence text, and model answer text corresponding with default question sentence text, andDefault question sentence text and model answer text are stored in problem base；
Step S304 establishes number-mark for each default question sentence text；
Step S306 extracts the corresponding predetermined keyword of each default question sentence text；Wherein, the tool of predetermined keyword is extractedBody implementation is referred to the step S202 in Fig. 2 to step S210.
Step S308 establishes the index relative between predetermined keyword and default question sentence text；Wherein, in index relativeIn, predetermined keyword is corresponding with the default number-mark of question sentence text of the one or more comprising predetermined keyword.
Problem base provided by the embodiment of the present invention, not just for the conjunction of the question answering system " problem-answer " of the prior artCollection, but also profound processing has been carried out to the intersection of " problem-answer ", such as keyword is extracted in advance to each question sentence, andKeyword and the question sentence comprising the keyword are established into index, and facilitate to reduce memory space by way of number,Search speed is improved simultaneously, further shortens the used time for applying the problem library lookup text in question and answer matching process.
In conclusion above-mentioned question and answer matching process provided in an embodiment of the present invention, can export in a relatively short period of time withThe corresponding answer of input question sentence of user can achieve and export answer in 1s, preferably shorten question and answer matching duration, but alsoImprove accuracy rate, comprehensive the user experience is improved degree.
Embodiment two:
For question and answer matching process provided in embodiment one, the embodiment of the invention provides a kind of matchings of question and answer to fillIt sets, shown in Figure 4, which comprises the following modules:
Extraction module 402, for extracting the keyword in input question sentence text；
First determining module 404 is used for according to keyword, by the way of index filtering from library the problem of pre-establishingDetermine object matching question sentence text；
Second determining module 406, for be based on Lay Weinstein distance algorithm, from object matching question sentence text determine with it is defeatedEnter the highest best match question sentence text of similarity of question sentence text；
Answer output module 408, for according to best match question sentence text, output answer corresponding with input question sentence textText.
In the above-mentioned apparatus of the present embodiment, after the keyword that input question sentence text is extracted by extraction module 402, by theOne determining module 404 determines object matching question sentence text by the way of index filtering from problem base, to reduce in problem baseThe question sentence range to match with input question sentence text, then determined by the second determining module 406 based on Lay Weinstein distance algorithmWith the highest best match question sentence text of similarity of input question sentence text, is finally exported and inputted by answer output module 408The corresponding answer text of question sentence text.The device can export answer corresponding with question sentence in a relatively short period of time, can both shortenQuestion and answer match duration, and can promote accuracy rate.
In order to facilitate understanding with implementation, on the basis of fig. 4, reference can be made to a kind of tool of question and answer coalignment shown in fig. 5Body structural block diagram, in which:
Extraction module 402 includes: participle unit 4021, for segmenting to input question sentence text, generates word sequence；StopWord removal unit 4022 obtains entry for removing the stop words in word sequence；Weight calculation unit 4023, for utilizingThe corresponding weight of each entry is calculated in improved comentropy formula；Improved comentropy formula are as follows:
Wherein, H (t) is the corresponding weight of entry t；ftkThe frequency in text k, n are appeared in for entry ttFor entry t appearanceFrequency in all text collections, N are the sum of text in text collection；
It further include sequencing unit 4024, for all entries to be ranked up according to the size of the weight obtained after calculating,Obtain weight sequencing table；Keyword extracting unit 4025, for being mentioned from weight sequencing table according to pre-set withdrawal ratioTake keyword.
First determining module 404 includes: matching value acquiring unit 4041, for according to the key in input question sentence textWord, and predetermined keyword the problem of pre-establish in library and the index relative between default question sentence text, obtain pre- rhetoric questionSentence text matching value corresponding with input question sentence text；Specifically, matching value acquiring unit 4041 may include matching keywordsDetermine subelement, default key identical with the keyword in the input question sentence text in library the problem of for that will pre-establishWord is as matching keywords；And matching value determines subelement, for according to predetermined keyword in described problem library and defaultIndex relative between question sentence text traverses the default question sentence text in described problem library, with the determination default question sentence textIn include the matching keywords number；The number for the matching keywords for including in the default question sentence text is madeFor default question sentence text matching value corresponding with the input question sentence text.The above subelement is not shown in FIG. 5.
First determining module 404 further includes the first determination unit 4042, for matching value to be greater than preset matching threshold valueDefault question sentence text is determined as object matching question sentence text.
Answer output module 408 includes: judging unit 4081, for judge best match question sentence text similarity whetherReach default similarity threshold；Model answer output unit 4082, for judging that the similarity of best match question sentence text reachesWhen to default similarity threshold, the corresponding model answer text of best match question sentence text is searched from problem base, standard is answeredCase text is as the corresponding answer text output of input question sentence text；Network answers output unit 4083, for best in judgementWhen the similarity of matching question sentence text not up to presets similarity threshold, the corresponding network of input question sentence text is searched from internetAnswer text, using network answers text as the corresponding answer text output of input question sentence text.
The technical effect of device provided by the present embodiment, realization principle and generation is identical with previous embodiment, for letterIt describes, Installation practice part does not refer to place, can refer to corresponding contents in preceding method embodiment.
In conclusion question and answer matching process provided in an embodiment of the present invention and device, in extracting input question sentence textAfter keyword, index filtering by way of from problem base determine object matching question sentence text, with reduce in problem base with it is defeatedEnter the question sentence range that question sentence text matches, then determines based on Lay Weinstein distance algorithm and input the similarity of question sentence text mostHigh best match question sentence text, finally output answer text corresponding with input question sentence text.With in the prior art useThe matched mode accuracy rate of question and answer is lower and used time longer problem is compared, and method and device provided in an embodiment of the present invention can be withAnswer corresponding with question sentence is exported in a relatively short period of time, can not only shorten question and answer matching duration, but also can promote accuracy rate.
The computer program product of question and answer matching process and device provided by the embodiment of the present invention, including store programThe computer readable storage medium of code, the instruction that said program code includes can be used for executing described in previous methods embodimentMethod, specific implementation can be found in embodiment of the method, details are not described herein.
In addition, in the description of the embodiment of the present invention unless specifically defined or limited otherwise, term " installation ", " phaseEven ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It canTo be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also can be indirectly connected through an intermediaryConnection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood at this with concrete conditionConcrete meaning in invention.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent productIt is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other wordsThe part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meterCalculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be aPeople's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.And storage medium above-mentioned includes: that USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are depositedThe various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic or disk.
In the description of the present invention, it should be noted that term " center ", "upper", "lower", "left", "right", "vertical",The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely toConvenient for description the present invention and simplify description, rather than the device or element of indication or suggestion meaning must have a particular orientation,It is constructed and operated in a specific orientation, therefore is not considered as limiting the invention.In addition, term " first ", " second "," third " is used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance.
Finally, it should be noted that embodiment described above, only a specific embodiment of the invention, to illustrate the present inventionTechnical solution, rather than its limitations, scope of protection of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hairIt is bright to be described in detail, those skilled in the art should understand that: anyone skilled in the artIn the technical scope disclosed by the present invention, it can still modify to technical solution documented by previous embodiment or can be lightIt is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not makeThe essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover in protection of the inventionWithin the scope of.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.