CN102411665B - Analyze the method and apparatus of name - Google Patents

Abstract

The invention discloses a kind of method and apparatus analyzing name, belong to computer realm.Described method comprises: the name to be measured and the test index that receive user's input; According to described test index and default test order, described name to be measured is tested; According to test result, described name to be measured is analyzed.Described device comprises: receiver module, test module and analysis module.The present invention, by receiving name to be measured and the test index of user's input, according to test index and default test order, tests name to be measured, and analyzes name to be measured according to test result, ensure that objectivity and the accuracy of analysis.

Description

Analyze the method and apparatus of name

Technical field

The present invention relates to computer realm, particularly a kind of method and apparatus analyzing name.

Background technology

Name is everyone label in society, and good name has active influence to the work of a people and life.Therefore, the quality analyzing name extremely important objective and accurately.

At present, main judge the quality of name or whether suitable by people with subjective experience, but because different people has larger otherness in fields such as knowledge background, personality, kens, identical name is In the view of the people of different knowledge background, different characters, different ken, analysis result may differ widely, and is therefore difficult to the objectivity and the accuracy that ensure judgement.

Such as, judge whether the name of a people meets with the sex of this people, and analyst according to the knowledge background of oneself and ken, draw and substantially meet or substantially do not meet conclusion fuzzy like this, and neither one objectively can only analyze foundation.

Comprehensively above-mentioned, prior art can only analyze name according to the subjective experience of people, and analysis result because of people easily, is difficult to the objectivity and the accuracy that ensure analysis.

Summary of the invention

In order to the subjectivity problem existed when solving in prior art and analyze name, embodiments provide a kind of method and apparatus analyzing name.Described technical scheme is as follows:

Analyze a method for name, described method comprises:

Receive name to be measured and the test index of user's input;

According to described test index and default test order, described name to be measured is tested;

According to test result, described name to be measured is analyzed;

Wherein, described name to be measured comprises: name to be measured;

If described test index is the sex degree of conformity of name, described according to described test index and default test order, described name to be measured is tested, comprise: according to the number of the to be measured middle word of name to be measured, the frequency of occurrences of each middle word to be measured middle word of other name of homogeneity in corpus in name to be measured, the frequency of occurrences of each middle word to be measured other name end word of homogeneity in corpus, the frequency of occurrences of each end to be measured word middle word of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of each end to be measured word other name end word of homogeneity in corpus, calculate other tendency weight of described homogeneity of name to be measured, the sex degree of conformity of name to be measured according to the tendency weight calculation of different sexes,

If described index to be measured is the general degree of name, described according to described test index and default test order, described name to be measured is tested, comprise: according to the number of middle word to be measured in name to be measured, the frequency of each middle word to be measured appearance of word in the middle of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of end word other name end word of homogeneity in corpus in name to be measured, calculate the general degree of name to be measured;

If described index to be measured is the degree of conformity that name and user expect, described according to described test index and default test order, described name to be measured is tested, comprise: calculate each word frequency expecting word and reverse file word frequency, expect word for each, what calculate this expectation word and each word in name to be measured according to the word frequency of this expectation word and reverse file word frequency mates weight; The degree of conformity that weight calculation name to be measured and user expect is mated according to all expectation words and each word in name to be measured;

If described index to be measured is the cultural connotation of name, described according to described test index and default test order, described name to be measured is tested, comprising: according to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that name to be measured occurs at corpus _k; The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n); According to w _kand d _kn () calculates the cultural connotation of name to be measured.

If described test index is the sex degree of conformity of described name to be measured, according to described test index and default test order, described name to be measured is tested, specifically comprises:

According to

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{2l}\],$

The male sex calculating described name to be measured is inclined to weights W _m;

Wherein, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency;

According to

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\],$

The women calculating described name to be measured is inclined to weights W _f;

Wherein, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus;

According to

$W=g\×\log \left(\frac{W_m}{W_f}\right),$

Calculate the sex degree of conformity W of described name to be measured;

Wherein, g represents the value that the male sex is other or women is not corresponding that described user inputs.

If described test index is the general degree of described name to be measured, according to described test index and default test order, described name to be measured is tested, specifically comprises:

When the sex of described user is man, according to

$F_m={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\left(i\right)\right)\×(q\×A_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _mrepresent the general degree of the name described to be measured of the other user of the male sex, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, q represents the contribution weight of end to be measured word for the general degree of name;

When the sex of described user is female, according to

$F_f={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\left(i\right)\right)\×(q\×B_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _frepresent the general degree of the name described to be measured of the other user of women, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

If described test index is the degree of conformity that described name to be measured and user expect, according to described test index and default test order, described name to be measured is tested, specifically comprises:

According to calculate word frequency tf _ej;

Wherein, tf _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

According to calculate reverse document-frequency idf _e;

Wherein, idf _ethe logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, | d:e ∈ d| represents the number comprising the explanation document d expecting word e;

According to

w(e,j)＝tf _ej×idf _e，

Calculation expectation word e mates weight w (e, j) with the Chinese character j's in described name N to be measured;

According to

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∩D_j}{\Σ}w(e,j),$

Calculate the degree of conformity W that described name N to be measured and user expect E _e;

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

If described test index is the cultural connotation of described name to be measured, according to described test index and default test order, described name to be measured is tested, specifically comprises:

According to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that described name to be measured occurs at corpus _k;

The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n);

According to

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1},$

Calculate the cultural connotation W of described name to be measured _c.

Analyze a device for name, described device comprises:

Receiver module, for receiving name to be measured and the test index of user's input;

Test module, for according to described test index and default test order, tests described name to be measured;

Analysis module, for analyzing described name to be measured according to test result;

Wherein, described name to be measured comprises name to be measured;

Described test module specifically for,

If described test index is the sex degree of conformity of name, according to the number of the to be measured middle word of name to be measured, the frequency of occurrences of each middle word to be measured middle word of other name of homogeneity in corpus in name to be measured, the frequency of occurrences of each middle word to be measured other name end word of homogeneity in corpus, the frequency of occurrences of each end to be measured word middle word of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of each end to be measured word other name end word of homogeneity in corpus, calculate other tendency weight of described homogeneity of name to be measured, the sex degree of conformity of name to be measured according to the tendency weight calculation of different sexes,

If described index to be measured is the general degree of name, according to the number of middle word to be measured in name to be measured, the frequency of each middle word to be measured appearance of word in the middle of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of end word other name end word of homogeneity in corpus in name to be measured, calculate the general degree of name to be measured;

If described index to be measured is the degree of conformity that name and user expect, word is expected for each, calculates the frequency tf that this expectation word occurs in the explanation document of each word of name to be measured _ej, and the number of all explanation documents and the logarithm idf of business of number of explanation document comprising this expectation word in Dictionary of Computing _e; According to tf _ejwith institute idf _ewhat calculate this expectation word and each word in name to be measured mates weight; The degree of conformity that weight calculation name to be measured and user expect is mated according to all expectation words and each word in name to be measured;

If described index to be measured is the cultural connotation of name, according to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that name to be measured occurs at corpus _k; The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n); According to w _kand d _kn () calculates the cultural connotation of name to be measured.

If described test index is the sex degree of conformity of described name to be measured,

Described test module comprises sex degree of conformity unit, for basis

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{21}\],$

The male sex calculating described name to be measured is inclined to weights W _m;

Wherein, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency;

According to

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\],$

The women calculating described name to be measured is inclined to weights W _f;

Wherein, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus;

According to

$W=g\×log\left(\frac{W_m}{W_f}\right),$

Calculate the sex degree of conformity W of described name to be measured;

Wherein, g represents the value that the male sex is other or women is not corresponding that described user inputs.

If described test index is the general degree of described name to be measured;

Described test module comprises general degree unit, during for being man when the sex of described user, according to

$F_m={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\left(i\right)\right)\×(q\×A_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _mrepresent the general degree of the name described to be measured of the other user of the male sex, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, q represents the contribution weight of end to be measured word for the general degree of name;

When the sex of described user is female, according to

$F_f={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\left(i\right)\right)\×(q\×B_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _frepresent the general degree of the name described to be measured of the other user of women, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

If described test index is the degree of conformity that described name to be measured and user expect,

Described test module comprises expects degree of conformity unit, for

According to calculate word frequency tf _ej;

Wherein, word frequency tf _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

According to calculate reverse document-frequency idf _e;

Wherein, reverse document-frequency idf _ethe logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, | d:e ∈ d| represents the number comprising the explanation document d expecting word e;

According to

w(e,j)＝tf _ej×idf _e，

Calculation expectation word e mates weight w (e, j) with the Chinese character j's in described name N to be measured;

According to

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∩D_j}{\Σ}w(e,j),$

Calculate the degree of conformity W that described name N to be measured and user expect E _e;

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

If described test index is the cultural connotation of described name to be measured,

Described test module comprises cultural connotation unit, for the search rate according to well-known phrase in corpus, determines the weight w of the well-known phrase k that described name to be measured occurs at corpus _k;

The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n);

According to

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1},$

Calculate the cultural connotation W of described name to be measured _c.

The beneficial effect that the technical scheme that the embodiment of the present invention provides is brought is:

By receiving name to be measured and the test index of user's input, according to test index and default test order, name to be measured being tested, and according to test result, name to be measured is analyzed, ensure that objectivity and the accuracy of analysis.

Accompanying drawing explanation

Fig. 1 is the method flow diagram of the analysis name provided in the embodiment of the present invention 1;

Fig. 2 is the apparatus structure schematic diagram of the analysis name provided in the embodiment of the present invention 2;

Fig. 3 is another structural representation of device of the analysis name provided in the embodiment of the present invention 2.

Embodiment

For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, embodiment of the present invention is described further in detail.

Embodiment 1

See Fig. 1, present embodiments provide a kind of method analyzing name, comprising:

101: the name to be measured and the test index that receive user's input;

102: according to test index and default test order, name to be measured is tested;

103: according to test result, name to be measured is analyzed.

The method that the present embodiment provides, by receiving name to be measured and the test index of user's input, according to test index and default test order, name to be measured is tested, and according to test result, name to be measured is analyzed, ensure that objectivity and the accuracy of analysis.

In the present embodiment, name comprises: surname and name, and name to be measured comprises surname to be measured and name to be measured.Name comprises: end word and middle word.Wherein, end word is named the last character of word, and middle word is named other words in word except the word of end, can have 0 or multiple.Such as, " Wang little Yan ", " king " is surname, and " little Yan " is name, and " swallow " is end word, and " little " is middle word.

Test index comprises: whether the degree of conformity that the general degree of sex degree of conformity, name, name musical note, name and user expect, the cultural connotation of name and name comprise derogatory sense, introduce for different test indexs below respectively, analyzes the method for name.

(1) when test index is sex degree of conformity, analytical approach comprises:

S11: the male sex according to following formulae discovery name to be measured is inclined to weight;

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{2l}\]$

Wherein, W _mrepresent that the male sex of name to be measured is inclined to weight, name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency.Wherein, α, β, γ can indirect assignment, such as α=0.2 in advance, and β=0.8, γ=2.0, also can be trained corpus by the mode of machine learning, draw best value for different corpus.

S12: the women according to following formulae discovery name to be measured is inclined to weight;

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\]$

Wherein, W _frepresent that the women of name to be measured is inclined to weight, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

S13: according to the sex degree of conformity of following formulae discovery name to be measured;

$W=g\×log\left(\frac{W_m}{W_f}\right)$

Wherein, g represents the value that the gender of input is corresponding, such as, when being 1 for g during the male sex, when being-1 for g during women.

S14: sex degree of conformity is larger, name to be measured and sex more meet.

(2) when test index is the general degree of name, analytical approach comprises:

S21: when user's sex is man, according to the general degree of following formulae discovery name to be measured;

$F_m=\sqrt{\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\right(i\left)\right)\×(q\×A_{2l})}={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\right(i))\×(q\×A_{2l})\]}^{\frac{1}{n}}$

Wherein, n, i, A _1m(i), A _2lidentical with symbol implication in aforementioned (), repeat no more here.Q represents the contribution weight of end to be measured word for the general degree of name.Q can preset, when middle word to be measured and end to be measured word of equal importance for the general degree of name when q=1, the q > 1 when end to be measured word is more important for the general degree of name than middle word to be measured, as established q=2.

Convenience of calculation in the implementation, above formula can equivalently be got log and be expressed as:

$f_m={\mathrm{logF}}_m=\frac{1}{n}\[\underset{i=1}{\overset{n-1}{\Σ}}log\left(A_{1m}\left(i\right)\right)+log(q\×A_{2l})\]$

Wherein, F _mand f _mall represent the general degree of other name to be measured of the male sex.

S22: when user's sex is female, according to the general degree of following formulae discovery name to be measured;

$F_f=\sqrt[n]{\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\right(i\left)\right)\×(q\×B_{2l})}={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\left(i\right)\right)\×(q\×B_{2l})\]}^{\frac{1}{n}}$

Wherein, n, i, B _1m(i), B _2lidentical with aforementioned (one) symbol implication, repeat no more here.Q and the male sex not in implication identical.

Convenience of calculation in the implementation, above formula can equivalently be got log and be expressed as:

$f_f={\mathrm{logF}}_f=\frac{1}{n}\[\underset{i=1}{\overset{n-1}{\Σ}}log\left(B_{1m}\left(i\right)\right)+log(q\×B_{2l})\]$

Wherein, F _fand f _fall represent the general degree of other name to be measured of women.

On the whole, the general degree of name is the mean value of the general degree of each word in name to be measured.

S23: the general degree of name, name to be measured is more general.

(3) when test index is name musical note, name musical note is divided into two parts: tone and phonetic, and analytical approach comprises:

S31: the number of times determining the tone change of name to be measured, number of times is more, and tone scoring is higher;

Such as, " Ma Mama " tone is unchanged, then score 0, and " Liu Shusheng " tone change twice, then obtain 2 points.

S32: according to the difference of the initial consonant points of articulation, divides into groups initial consonant;

Such as, according to the difference of the initial consonant points of articulation, initial consonant can be divided into following four groups:

Labial: bpmf

Apical: dtnl

Velar: gkh

Lingual surface sound, blade-palatal, dental: jqxzhchshrzcs

S33: according to the difference of simple or compound vowel of a Chinese syllable pronunciation nozzle type, simple or compound vowel of a Chinese syllable is divided into groups;

Such as, according to the difference of simple or compound vowel of a Chinese syllable pronunciation nozzle type, simple or compound vowel of a Chinese syllable is divided into following five groups:

Start with " a ": aaiaoanang

Start with " e ": eereieneng

Start with " o ": oouong

Start with " i ": iiaieiaoiouianiniangingiongvueuanun

Start with " u ": uuauouaiueiuanuenuangueng

S34: determine the initial consonant place initial consonant grouping of two words of arbitrary neighborhood in name to be measured and the type of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable grouping, be that the grouping of initial consonant place initial consonant and the grouping of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable of two words of arbitrary neighborhood all belongs to same group, only has one to belong to same group, all do not belong to the order of same group according to type, phonetic is marked and is increased progressively successively;

Such as, if the initial consonant place initial consonant grouping of two words of arbitrary neighborhood and the grouping of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable all belong to same group, then not bonus point, if the initial consonant place initial consonant grouping of two words of arbitrary neighborhood and the grouping of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable only have (arbitrarily) one to belong to same group, then add default low point, as 1 point, if the initial consonant place initial consonant grouping of two words of arbitrary neighborhood and the grouping of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable all do not belong to same group, then add default high score, as 2 points.

S35: the summation of tone scoring and phonetic scoring is marked as musical note;

S36: musical note scoring is higher, and name is more pleasing to the ear, otherwise name is more unpleasant to hear.

(4) when test index be name and user expect degree of conformity time, analytical approach comprises:

S41: according to following formulae discovery word frequency tf _ejwith reverse document-frequency idf _e;

${\mathrm{tf}}_{ej}=\frac{n_{ej}}{|w\∈d_j|},$

Wherein, tf _ejfor word frequency, represent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

${\mathrm{idf}}_e=log\left(\frac{\left|D\right|}{|d:e\∈d|}\right),$

Wherein, idf _efor reverse document-frequency, the logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, also be the number of word in dictionary (not comprising the word explained in document), | d:e ∈ d| represents the number comprising the explanation document d expecting word e.Idf _efor making the word that frequency of utilization in dictionary is high, as " ", " " etc., the coupling weight for certain Chinese character j reduces, and makes word maximally related with the meaning of Chinese character j, as " intelligent " word for explain word " clever " coupling weight increase.

S42: expect that word e and the Chinese character j's in name N to be measured mates weight w (e, j) according to following formulae discovery;

w(e,j)＝tf _ej×idf _e，

Wherein, w (e, j) represents and expects that word e and the Chinese character j's in name N to be measured mates weight.

S43: the degree of conformity W expecting E according to following formulae discovery name N to be measured and user _e;

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∪D_j}{\Σ}w(e,j),$

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

S44: degree of conformity is higher, name to be measured and user expect more to meet.

(5) when test index is the cultural connotation of name, analytical approach comprises:

S51: according to the search rate of well-known phrase in corpus, determines the weight w of the well-known phrase k that name to be measured occurs at corpus _k;

Such as: " great Lin temple peach blossom " Pai Chu-yi

To the greatest extent, temple, mountain peach blossom begins in full bloom human world fragrance in April.(w _k＝0.81)

The long hatred spring returns without looking for place, does not know to proceed to this.(w _k＝0.75)

As can be seen here, the search rate of well-known phrase is higher, and weight is larger.

S52: the mean value of number of words of being separated by this well-known phrase k according to each word of name to be measured, determines the distance d of name to be measured in this well-known phrase k _k(n);

Concrete, when name to be measured is a word, this distance is a preset constant, and when name to be measured is multiple word, this distance is that each word is separated by the mean value of number of words in the well-known phrase of appearance.

Such as, " Wang Yuefei ", name to be measured is " moon is luxuriant and rich with fragrance ", appears in " to the greatest extent, temple, mountain peach blossom begins in full bloom human world fragrance in April ", d _k(n)=1.

S53: according to w _kand d _kn () calculates the cultural connotation W of name to be measured _c, concrete computing formula is as follows:

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1}$

Thus, when more, in well-known phrase the distances of name to be measured occurrence number in different well-known phrases are nearer, its cultural connotation is darker.

S54: cultural connotation W _cvalue larger, the cultural connotation of name is darker.

(6) when test index be name whether comprise derogatory sense time, analytical approach comprises:

S61: the relation table setting up derogatory term and its phonetic or partials;

Following table is an instantiation of relation table:

Phonetic/partials	Derogatory term
		Siwang (phonetic)	Dead
Shiwang (partials)	Dead
		Siwan (partials)	Dead
Shiwan (partials)	Dead
		Linse (phonetic)	Stingy
Lingse (partials)	Stingy
		......	......

S62: according to phonetic and the relation table of name to be measured, determines whether name to be measured comprises derogatory sense.

Concrete, when the phonetic in relation table or partials comprise the phonetic of name to be measured, name to be measured comprises derogatory sense, otherwise does not comprise derogatory sense.

Such as, " Chen Shiwang ", the phonetic of name to be measured " poem is prosperous " is Shiwang, and identical with the partials of " death " in relation table, therefore, " poem is prosperous " comprises derogatory sense.

The method that the present embodiment provides, by receiving name to be measured and the test index of user's input, according to test index and default test order, name to be measured is tested, and according to test result, name to be measured is analyzed, ensure that objectivity and the accuracy of analysis.

Embodiment 2

See Fig. 2, present embodiments provide a kind of device analyzing name, comprising:

Receiver module 201, for receiving name to be measured and the test index of user's input;

Test module 202, for according to test index and default test order, tests name to be measured;

Analysis module 203, for analyzing name to be measured according to test result.

Name to be measured comprises: surname to be measured and name to be measured.

(1) test index is the sex degree of conformity of name to be measured;

Test module 202 comprises sex degree of conformity unit 2021, for basis

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{2l}\],$

The male sex calculating name to be measured is inclined to weights W _m;

Wherein, name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency;

According to

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\],$

The women calculating name to be measured is inclined to weights W _f;

Wherein, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus;

According to

$W=g\×log\left(\frac{W_m}{W_f}\right),$

Calculate the sex degree of conformity W of name to be measured;

Wherein, g represents the value that the male sex is other or women is not corresponding that user inputs.

(2) test index is the general degree of name to be measured;

Test module 202 comprises general degree unit 2022, during for being man when the sex of user, according to

$F_m={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\right(i))\×(q\×A_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of name to be measured;

Wherein, F _mrepresent the general degree of the name to be measured of the other user of the male sex, name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, q represents the contribution weight of end to be measured word for the general degree of name;

When the sex of user is female, according to

$F_f={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\right(i))\×(q\×B_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of name to be measured;

Wherein, F _frepresent the general degree of the name to be measured of the other user of women, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

(3) test index is the musical note scoring of name to be measured;

Test module 202 comprises musical note unit 2023, and for determining the number of times of the tone change of name to be measured, number of times is more, and tone scoring is higher;

According to the difference of the initial consonant points of articulation, initial consonant is divided into groups;

According to the difference of simple or compound vowel of a Chinese syllable pronunciation nozzle type, simple or compound vowel of a Chinese syllable is divided into groups;

Determine the initial consonant place initial consonant grouping of two words of arbitrary neighborhood in name to be measured and the type of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable grouping, be that the grouping of initial consonant place initial consonant and the grouping of simple or compound vowel of a Chinese syllable place simple or compound vowel of a Chinese syllable of two words of arbitrary neighborhood all belongs to same group, only has one to belong to same group, all do not belong to the order of same group according to type, phonetic is marked and is increased progressively;

The summation of tone scoring and phonetic scoring is marked as the musical note of name to be measured.

(4) test index is the degree of conformity that name to be measured and user expect;

Test module 202 comprises expects degree of conformity unit 2024, for

According to calculate word frequency tf _ej;

Wherein, tf _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

According to calculate reverse document-frequency idf _e;

Wherein, idf _ethe logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, | d:e ∈ d| represents the number comprising the explanation document d expecting word e;

According to

w(e,j)＝tf _ej×idf _e，

Calculation expectation word e mates weight w (e, j) with the Chinese character j's in name N to be measured;

According to

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∩Dj}{\Σ}w(e,j),$

Calculate the degree of conformity W that name N to be measured and user expect E _e;

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

(5) test index is the cultural connotation of name to be measured;

Test module 202 comprises cultural connotation unit 2025, for the search rate according to well-known phrase in corpus, determines the weight w of the well-known phrase k that name to be measured occurs at corpus _k;

The mean value of number of words of being separated by well-known phrase k according to each word of name to be measured, determines the distance d of name to be measured in well-known phrase k _k(n);

According to

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1},$

Calculate the cultural connotation W of name to be measured _c.

(6) test index is whether name to be measured comprises derogatory sense;

Test module 202 comprises derogatory sense judging unit 2026, for

Set up the relation table of derogatory term and its phonetic or partials;

When the phonetic in relation table or partials comprise the phonetic of name to be measured, name to be measured comprises derogatory sense, otherwise does not comprise derogatory sense.

The device that the present embodiment provides, belongs to same design with embodiment of the method, and its specific implementation process refers to embodiment of the method, repeats no more here.

The device that the present embodiment provides, by receiving name to be measured and the test index of user's input, according to test index and default test order, name to be measured is tested, and according to test result, name to be measured is analyzed, ensure that objectivity and the accuracy of analysis.

All or part of content in the technical scheme that above embodiment provides can be realized by software programming, and its software program is stored in the storage medium that can read, storage medium such as: the hard disk in computing machine, CD or floppy disk.

Claims (10)

1. analyze a method for name, it is characterized in that, described method comprises:

Receive name to be measured and the test index of user's input;

According to described test index and default test order, described name to be measured is tested;

According to test result, described name to be measured is analyzed;

Wherein, described name to be measured comprises name to be measured;

If described test index is the sex degree of conformity of name, described according to described test index and default test order, described name to be measured is tested, comprise: according to the number of the to be measured middle word of name to be measured, the frequency of occurrences of each middle word to be measured middle word of other name of homogeneity in corpus in name to be measured, the frequency of occurrences of each middle word to be measured other name end word of homogeneity in corpus, the frequency of occurrences of each end to be measured word middle word of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of each end to be measured word other name end word of homogeneity in corpus, calculate other tendency weight of described homogeneity of name to be measured, the sex degree of conformity of name to be measured according to the tendency weight calculation of different sexes,

If described index to be measured is the general degree of name, described according to described test index and default test order, described name to be measured is tested, comprise: according to the number of middle word to be measured in name to be measured, the frequency of each middle word to be measured appearance of word in the middle of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of end word other name end word of homogeneity in corpus in name to be measured, calculate the general degree of name to be measured;

If described index to be measured is the degree of conformity that name and user expect, described according to described test index and default test order, described name to be measured is tested, comprise: calculate each word frequency expecting word and reverse file word frequency, expect word for each, what calculate this expectation word and each word in name to be measured according to the word frequency of this expectation word and reverse file word frequency mates weight; The degree of conformity that weight calculation name to be measured and user expect is mated according to all expectation words and each word in name to be measured;

If described index to be measured is the cultural connotation of name, described according to described test index and default test order, described name to be measured is tested, comprising: according to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that name to be measured occurs at corpus _k; The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n); According to w _kand d _kn () calculates the cultural connotation of name to be measured.

2. the method for claim 1, is characterized in that, if described test index is the sex degree of conformity of described name to be measured,

According to described test index and default test order, described name to be measured is tested, comprising:

According to

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{2l}\],$

The male sex calculating described name to be measured is inclined to weights W _m;

Wherein, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency;

According to

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\],$

The women calculating described name to be measured is inclined to weights W _f;

Wherein, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus;

According to

$W=g\×log\left(\frac{W_m}{W_f}\right),$

Calculate the sex degree of conformity W of described name to be measured;

Wherein, g represents the value that the male sex is other or women is not corresponding that described user inputs.

3. the method for claim 1, is characterized in that, if described test index is the general degree of described name to be measured,

According to described test index and default test order, described name to be measured is tested, comprising:

When the sex of described user is man, according to

$F_m={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\left(i\right)\right)\×(q\×A_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _mrepresent the general degree of the name described to be measured of the other user of the male sex, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, q represents the contribution weight of end to be measured word for the general degree of name;

When the sex of described user is female, according to

$F_f={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\left(i\right)\right)\×(q\×B_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _frepresent the general degree of the name described to be measured of the other user of women, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

4. the method for claim 1, is characterized in that, if described test index is the degree of conformity that described name to be measured and user expect,

According to described test index and default test order, described name to be measured is tested, comprising:

According to calculate word frequency tf _ej;

Wherein, word frequency tf _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

According to calculate reverse document-frequency idf _e;

Wherein, reverse document-frequency idf _ethe logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, | d:e ∈ d| represents the number comprising the explanation document d expecting word e;

According to

w(e,j)＝tf _ej×idf _e，

Calculation expectation word e mates weight w (e, j) with the Chinese character j's in described name N to be measured;

According to

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∩D_j}{\Σ}w(e,j),$

Calculate the degree of conformity W that described name N to be measured and user expect E _e;

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

5. the method for claim 1, is characterized in that, if described test index is the cultural connotation of described name to be measured,

According to described test index and default test order, described name to be measured is tested, comprising:

According to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that described name to be measured occurs at corpus _k;

The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n);

According to

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1},$

Calculate the cultural connotation W of described name to be measured _c.

6. analyze a device for name, it is characterized in that, described device comprises:

Receiver module, for receiving name to be measured and the test index of user's input;

Test module, for according to described test index and default test order, tests described name to be measured;

Analysis module, for analyzing described name to be measured according to test result;

Wherein, described name to be measured comprises name to be measured;

Described test module specifically for,

If described test index is the sex degree of conformity of name, according to the number of the to be measured middle word of name to be measured, the frequency of occurrences of each middle word to be measured middle word of other name of homogeneity in corpus in name to be measured, the frequency of occurrences of each middle word to be measured other name end word of homogeneity in corpus, the frequency of occurrences of each end to be measured word middle word of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of each end to be measured word other name end word of homogeneity in corpus, calculate other tendency weight of described homogeneity of name to be measured, the sex degree of conformity of name to be measured according to the tendency weight calculation of different sexes,

If described index to be measured is the general degree of name, according to the number of middle word to be measured in name to be measured, the frequency of each middle word to be measured appearance of word in the middle of other name of homogeneity in corpus in name to be measured, and the frequency of occurrences of end word other name end word of homogeneity in corpus in name to be measured, calculate the general degree of name to be measured;

If described index to be measured is the degree of conformity that name and user expect, word is expected for each, calculates the frequency tf that this expectation word occurs in the explanation document of each word of name to be measured _ej, and the number of all explanation documents and the logarithm idf of business of number of explanation document comprising this expectation word in Dictionary of Computing _e; According to tf _ejwith institute idf _ewhat calculate this expectation word and each word in name to be measured mates weight; The degree of conformity that weight calculation name to be measured and user expect is mated according to all expectation words and each word in name to be measured;

If described index to be measured is the cultural connotation of name, according to the search rate of well-known phrase in corpus, determine the weight w of the well-known phrase k that name to be measured occurs at corpus _k; The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n); According to w _kand d _kn () calculates the cultural connotation of name to be measured.

7. device as claimed in claim 6, is characterized in that, if described test index is the sex degree of conformity of described name to be measured,

Described test module comprises sex degree of conformity unit, for basis

$W_m=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αA}}_{1m}\left(i\right)+(1-\mathrm{\α})A_{2m}\left(i\right)\]+\mathrm{\γ}\[(1-\mathrm{\β})A_{1l}+{\mathrm{\βA}}_{2l}\],$

The male sex calculating described name to be measured is inclined to weights W _m;

Wherein, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2mi () represents the frequency of occurrences of i-th middle word to be measured male name end word in corpus, A _1lrepresent the frequency of occurrences of the middle word of end to be measured word male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, α represents middle word to be measured and corpus man's name or the award factor of female's name intermediate character when closing, β represents end to be measured word and corpus man's name or the award factor of female's name end character when closing, and γ represents the decision weight of end to be measured word for gender tendency;

According to

$W_f=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}\[{\mathrm{\αB}}_{1m}\left(i\right)+(1-\mathrm{\α})B_{2m}\left(i\right)\]+\mathrm{\γ}(1-\mathrm{\β})B_{1l}+{\mathrm{\βB}}_{2l}\],$

The women calculating described name to be measured is inclined to weights W _f;

Wherein, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2mi () represents the frequency of occurrences of i-th middle word to be measured female's name end word in corpus, B _1lrepresent the frequency of occurrences of the middle word of end to be measured word female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus;

According to

$W=g\×log\left(\frac{W_m}{W_f}\right),$

Calculate the sex degree of conformity W of described name to be measured;

Wherein, g represents the value that the male sex is other or women is not corresponding that described user inputs.

8. device as claimed in claim 6, is characterized in that, if described test index is the general degree of described name to be measured,

Described test module comprises general degree unit, during for being man when the sex of described user, according to

$F_m={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{A}_{1m}\left(i\right)\right)\×(q\×A_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _mrepresent the general degree of the name described to be measured of the other user of the male sex, described name to be measured comprises: middle word to be measured and end to be measured word, and n represents the number of middle word to be measured, and i represents each middle word to be measured, A _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured male name in corpus, A _2lrepresent the frequency of occurrences of end to be measured word male name end word in corpus, q represents the contribution weight of end to be measured word for the general degree of name;

When the sex of described user is female, according to

$F_f={\[\left(\underset{i=1}{\overset{n-1}{\Π}}{B}_{1m}\left(i\right)\right)\×(q\×B_{2l})\]}^{\frac{1}{n}},$

Calculate the general degree of described name to be measured;

Wherein, F _frepresent the general degree of the name described to be measured of the other user of women, B _1mi () represents the frequency of occurrences of the middle word of i-th middle word to be measured female's name in corpus, B _2lrepresent the frequency of occurrences of end to be measured word female's name end word in corpus.

9. device as claimed in claim 6, is characterized in that, if described test index is the degree of conformity that described name to be measured and user expect,

Described test module comprises expects degree of conformity unit, for

According to calculate word frequency tf _ej;

Wherein, word frequency tf _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe frequency of middle appearance, n _ejrepresent and expect the explanation document d of word e at Chinese character j _jthe number of times of middle appearance, | w ∈ d _j| represent and explain document d _jin the number of all word w;

According to calculate reverse document-frequency idf _e;

Wherein, reverse document-frequency idf _ethe logarithm of the business of the number representing all explanation documents in dictionary and the number comprising the explanation document expecting word e, | D| represents the number of all explanation documents in dictionary, | d:e ∈ d| represents the number comprising the explanation document d expecting word e;

According to

w(e,j)＝tf _ej×idf _e，

Calculation expectation word e mates weight w (e, j) with the Chinese character j's in described name N to be measured;

According to

$W_E=\underset{j\∈N}{\Σ}\underset{e\∈E\∩D_j}{\Σ}w(e,j),$

Calculate the degree of conformity W that described name N to be measured and user expect E _e;

Wherein, E represents that user expects, is the set expecting word e, D _jrepresent the set of w (e, j) >0.

10. device as claimed in claim 8, is characterized in that, if described test index is the cultural connotation of described name to be measured,

Described test module comprises cultural connotation unit, for the search rate according to well-known phrase in corpus, determines the weight w of the well-known phrase k that described name to be measured occurs at corpus _k;

The mean value of number of words of being separated by described well-known phrase k according to each word of described name to be measured, determines the distance d of described name to be measured in described well-known phrase k _k(n);

According to

$W_c=\underset{k}{\Σ}{w}_k\×\frac{1}{d_k\left(n\right)+1},$

Calculate the cultural connotation W of described name to be measured _c.