User management method of service interaction order platform
Technical Field
The invention relates to the technical field of information communication, in particular to a user management method of a business interaction order platform.
Background
With the continuous development and maturity of internet technology, the online shopping mall brings unprecedented convenience for commodity shopping. The existing online shopping malls are not satisfied with the display of physical commodities, and have already been extended to the field of service products. The service product website in the prior art mainly adopts works of a display service party and information of a service party, and then waits for a demand party to search, discover and consult, the butt joint service in the mode needs to spend more energy and time on the demand party to inquire a proper service party to complete self business butt joint, the cost of the time spent on the demand party is higher, the service party searched has certain randomness with the business matching degree of the demand party, the inquiry enthusiasm of the demand party can be struck to a certain degree, the butt joint development of network service products is not facilitated, and the continuous healthy growth of platforms is not facilitated.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a user management method of a business interaction order platform, which can search a designer with higher matching degree with the demand of a demand party according to the classification mark and the keyword mark of the service party, greatly save the time spent by the demand party for inquiring a proper service party, improve the matching accuracy between the demand party and the service party and effectively stimulate the business enthusiasm of the demand party for searching the service party through a network platform.
In order to achieve the purpose, the invention adopts the technical scheme that: a user management method of a service interaction order platform is characterized in that: includes such steps as storing the registered information of both demander and server, classifying the certification data D1 of server, and storing them, the certification data D1 according to age Y, work experience E and work W1、W2、W3……]Geographic location L, adept skill S1、S2、S3……]A demand acceptance number aN [ aN ]1、aN2、aN3……]The number of demand releases bN [ bN ]1、bN2、bN3……]Additional supplementary information I [ I ]1、I2、I3……]Classifying and marking, storing in a marking library, establishing a keyword library, storing keywords in the keyword library, wherein the keywords comprise an adequacy field H, a designer authentication qualification A/B, a designer state K1 and an authentication information integrity T, correspondingly matching the keywords with classification marks of service party authentication data, searching corresponding keywords in the keyword library by search words input by a demand party, finding out service parties conforming to the keywords, and displaying the searched service parties to the demand party after adjusting the arrangement sequence of the service parties according to the matching degree.
Further, in the step (iv), the good field H is correspondingly matched with the classification mark according to the following formula:
{{Snn1,(∑Snn1≡Smm)max},......,{Snnn,(∑Snnn≡Smm)min}}=H2
the designer certification qualification A/B is calculated according to the following formula:
a (authentication qualification): [
B (no certification qualification): [
Wnn e { work passed audit }
The designer state K1 is calculated according to the following formula:
the integrity T of the authentication information is calculated according to the following formula:
t < 1 (incomplete).
Furthermore, the matching degree in the step (C) is arranged according to the matching parameters, the matching parameters comprise a recommendation value V, a comprehensive score P and a user activity degree C, the matching parameters are input by a demand party in a selection frame mode,
the recommended value V is calculated according to the following formula:
L(Wn) Number of liking of work, WnIn order to correspond to the work,
F(aNn) To accept the final completion of the demand, incomplete or non-timed out works do not count or temporarily do not count, t (aN)n) The final time spent for the corresponding work, aNnIn order to correspond to the reception of the demand,
y (E) is the score of the corresponding experience, E is the corresponding year, the score of the corresponding experience below 1 year is 100, the score of the corresponding experience below 1-3 years is 200E, the score of the corresponding experience between 3-5 years is 300E, the score of the corresponding experience between 5-10 years is 2000+ 100E, the score of the corresponding experience above 10 years is 4000,
ipunishthe scores are punishment, reporting and violation;
the comprehensive score P is calculated according to the following formula:
L(Wn) Number of liking of work, WnIn order to correspond to the work,
F(aNn) To accept the final completion of the demand, incomplete or non-timed out works do not count or temporarily do not count, t (aN)n) The final time spent for the corresponding work, aNnIn order to correspond to the reception of the demand,
y (E) is the score of the corresponding experience, E is the corresponding year, the score of the corresponding experience below 1 year is 100, the score of the corresponding experience below 1-3 years is 200E, the score of the corresponding experience between 3-5 years is 300E, the score of the corresponding experience between 5-10 years is 2000+ 100E, the score of the corresponding experience above 10 years is 4000,
ipunishfor punishment, reporting,A score of the violation;
the user activity C is calculated according to the following formula:
C1=T*0.1+I(W0)+I(I0),
C2=I(aN0)+I(bN0),
C3=Iactivity,
C=C1+C2+C3,
i (x) is a time activity algorithm, and x is a work set W0Extra activity information set IactivityAnd logging flow set I0Demand acceptance set aN0Or the requirement issuing set bN0,
I (x) collecting time characteristic values of corresponding behaviors, then carrying out distributed calculation to obtain the reciprocal of the time interval of the average behavior as result feedback;
and fifthly, the service parties searched out in the step five are arranged according to the matching degree of the matching parameters selected by the demand party and then displayed to the demand party.
In the scheme, the authentication data of the service party are classified and marked according to different categories, the corresponding relation is formed between the keywords and each mark through a formula, the required party searches the required service party by selecting the corresponding keywords, the service party meeting the conditions can be ranked through the matching parameters and displayed to the required party, and the matching parameters are reference data formed based on the history records of the platform user, so that the query time of the required party is saved to a certain extent, and the matching accuracy between the required party and the service party is improved; in addition, the tag library and the keyword library can gradually expand the classification tags and the keywords according to the continuous development of the platform to meet more requirements of a demand side and improve the platform.
The invention is further described below with reference to the accompanying drawings.
Drawings
FIG. 1 is a block diagram of a system according to an embodiment of the present invention.
Detailed Description
Fig. 1 shows a user management system of a business interaction order platform, which includes an input unit, a display unit, a reading unit, an output unit, a memory, and a data processor. The input mode of the user terminal can adopt mouse, keyboard input or voice input or touch screen and other modes to input the search word which the user wants to inquire, the data processor can read the search word by a sensor (such as a sound sensor and a touch sensor) and search corresponding key words or classification marks in the memory, the data processor inquires corresponding service parties by the key words or the classification marks and feeds back the data to the data processor, when the matched words can not be searched in the mark library or the key word library, the data processor feeds back to the user terminal to enable the demand party to re-input the search word, in order to avoid that the wanted inquiry result can not be searched for many times, the input can be carried out by adopting a selection box mode or a mode combining input and selection, when the selection box is adopted for input, the simple search can adopt the read search word to be searched in the key word library and the mark word library at the same time, the accurate search is carried out by searching the read search words in a keyword library or searching in the keyword library in a selection frame mode; after the corresponding keywords or the classification marks are found, the corresponding service parties are matched, then the data processor feeds back the matched service parties to the user side, and the demander can select and input matching parameters to adjust the ranking sequence of the searched service parties and then displays the service parties on a display unit of the user side.
The user management method of the interactive order platform comprises the following steps of firstly storing the registration information input by a demand party and a service party in a user information base, secondly classifying and marking and storing the authentication data D1 of the service party, and finally storing the authentication data D1 according to the age Y, the work experience E and the work W [ W ] W1、W2、W3……]Geographic location L, adept skill S1、S2、S3……]A demand acceptance number aN [ aN ]1、aN2、aN3……]The number of demand releases bN [ bN ]1、bN2、bN3……]Additional supplementary information I [ I ]1、I2、I3……]Carry out classification marking, anStoring the search results in a tag library which can be gradually expanded along with the development of a platform or the storage of search records, establishing a keyword library which stores keywords comprising an adequacy field H, a designer certification qualification A/B, a designer state K1 and a certification information integrity T, and gradually expanding the keyword library, matching the keywords with classification marks of certification data of a service party correspondingly, searching corresponding keywords in the keyword library by the search words input by a demand party, finding out the service party which meets the keywords, naturally searching the search words input by the demand party in the tag library, adopting a simple search mode and an accurate search mode as described above, feeding back the searched service party by a data processor, and adjusting the arrangement sequence of the service party according to the matching degree by the demand party, and then presented to the requesting party. Furthermore, the keyword or the classification mark finally selected or matched by the demander is stored in the user database through the memory, the demander corresponds to the keyword, and the demander can correspond to a plurality of keywords or classification marks. In addition, the search terms which are input by the demand side and are not corresponding to the original tag library or the keyword library can be used as one of the word sources for expanding the tag library.
In the above step, the good field H is correspondingly matched with the classification mark according to the following formula:
{{Snn1,(∑Snn1≡Smm)max},......,{Snnn,(∑Snnn≡Smm)min}}=H2
the designer certification qualification A/B is calculated according to the following formula:
a (authentication qualification):
b (no certification qualification): [
Wnn e { work passed audit }
The designer state K1 is calculated according to the following formula:
the integrity T of the authentication information is calculated according to the following formula:
t < 1 (incomplete).
And sixthly, arranging the matching degrees according to the matching parameters, wherein the matching parameters comprise a recommended value V, a comprehensive score P and a user activity degree C, and enabling a demand party to select and input the matching parameters in a selection frame mode.
The recommended value V is calculated according to the following formula:
L(Wn) Number of liking of work, WnIn order to correspond to the work,
F(aNn) To accept the final completion of the demand, incomplete or non-timed out works do not count or temporarily do not count, t (aN)n) The final time spent for the corresponding work, aNnIn order to correspond to the reception of the demand,
y (E) is the score of the corresponding experience, E is the corresponding year, the score of the corresponding experience below 1 year is 100, the score of the corresponding experience below 1-3 years is 200E, the score of the corresponding experience between 3-5 years is 300E, the score of the corresponding experience between 5-10 years is 2000+ 100E, the score of the corresponding experience above 10 years is 4000,
ipunishthe scores of punishment, reporting and violation.
The comprehensive score P is calculated according to the following formula:
L(Wn) Number of liking of work, WnIn order to correspond to the work,
F(aNn) To accept the final completion of the demand, incomplete or non-timed out works do not count or temporarily do not count, t (aN)n) The final time spent for the corresponding work, aNnIn order to correspond to the reception of the demand,
y (E) is the score of the corresponding experience, E is the corresponding year, the score of the corresponding experience below 1 year is 100, the score of the corresponding experience below 1-3 years is 200E, the score of the corresponding experience between 3-5 years is 300E, the score of the corresponding experience between 5-10 years is 2000+ 100E, the score of the corresponding experience above 10 years is 4000,
ipunishthe scores of punishment, reporting and violation.
The user activity C is calculated according to the following formula:
C1=T*0.1+I(W0)+I(I0),
C2=I(aN0)+I(bN0),
C3=Iactivity,
C=C1+C2+C3,
i (x) is a time activity algorithm, and x is a work set W0Extra activity information set IactivityAnd logging flow set I0Demand acceptance set aN0Or the requirement issuing set bN0,
And I (x) collecting time characteristic values of corresponding behaviors and then carrying out distributed calculation to obtain the reciprocal of the time interval of the average behavior as result feedback.
And fifthly, the searched service parties are arranged according to the matching degree of the matching parameters selected by the demand party and then displayed to the demand party.
The invention manages the registered and authenticated service party through the platform, orderly manages the registered demand party through a mode of classification marking and keyword association, improves the accuracy of the subsequent search service party by matching and storing the registration information with the search history and the order history of the registration information, can provide timely, rapid and accurate matching for the demand party when the demand party searches related service parties, saves the time spent by inquiry for the demand party, and simultaneously has greater initiative in selection and inquiry, thereby having the function of stimulating the demand party to find the service enthusiasm of the service party through the network platform to a certain extent.
The present invention is not limited to the above embodiments, and those skilled in the art can implement the present invention in other embodiments according to the disclosure of the present invention, or make simple changes or modifications on the design structure and idea of the present invention, and fall into the protection scope of the present invention.