CN114970891A - Transaction platform system and method for recycling recovered household appliances under big data - Google Patents
Transaction platform system and method for recycling recovered household appliances under big data Download PDFInfo
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Abstract
The invention discloses a transaction platform system and a method for recycling household appliances under big data, relating to the technical field of household appliance recycling, wherein the system comprises a user side for household appliance sale and household appliance purchase and a transaction platform for household appliance transaction; the transaction platform comprises a central control module, an image analysis module and a communication module; the central control module is used for intelligently controlling the whole transaction platform; the image analysis module is used for analyzing the household appliance information uploaded by the sale module to ensure the authenticity of the household appliance information; the communication module is used for communicating the selling module with the purchasing module before transaction, and the image analysis module can analyze and judge the household appliance information uploaded by the user side, so that the user side is prevented from uploading false image information, the benefits of other people are guaranteed, and the household appliance transaction of the transaction platform is more real.
Description
Technical Field
The invention relates to the technical field of household appliance recycling, in particular to a recycling trading platform system and a recycling trading platform method under big data.
Background
With the continuous progress of society and the continuous development of times, environmental protection becomes the problem to be solved urgently, wherein, in the household electrical appliances field, directly eliminate old household electrical appliances, can lead to producing more harmful rubbish, consequently, recycling to old household electrical appliances is one of the important means of avoiding old household electrical appliances to cause environmental pollution, in the prior art, the mode of trading platform is usually adopted to carry out the recycling trade of old household electrical appliances and recycle, when resources are saved, environmental sanitation has been protected, however, the trading platform of prior art has the following problems in the in-service use:
1. for a seller of old household appliances, false image information and character information can be uploaded in order to improve the selling unit price of the old household appliances, and utilization damage can be caused to a purchaser of the old household appliances;
2. because the seller of the old household appliance does not professionally sell the old household appliance, the communication and contact between the buyer and the seller may not be replied in time, which affects the success rate of the transaction;
therefore, a recycling transaction platform system and a recycling transaction method for home appliances under big data are urgently needed to solve the technical problems.
Disclosure of Invention
The invention aims to provide a transaction platform system and a transaction method for recycling household appliances under big data, so as to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: a transaction platform system for recycling household appliances under big data comprises a user side for selling and purchasing the household appliances and a transaction platform for performing household appliance transaction;
the user side is connected with the transaction platform;
the user side comprises a sale module and a purchase module;
the sale module is used for uploading the household appliance information to be sold to the transaction platform, and the purchase module is used for purchasing the household appliances uploaded by the sale module from the transaction platform; the household appliances refer to old household appliances used for a period of time;
the transaction platform comprises a central control module, an image analysis module and a communication module;
the central control module is used for carrying out intelligent control on the whole transaction platform; the image analysis module is used for analyzing the household appliance information uploaded by the sale module, ensuring the authenticity of the household appliance information, avoiding false household appliance information uploaded by a seller for facilitating sale and improving the sale price and ensuring the benefit of a buyer; the communication module is used for communicating the sales module with the acquisition module before transaction, so that the acquisition party can know the performance of the product fully;
the sales module is connected with the image analysis module, the sales module and the acquisition module are connected with the communication module, and the image analysis module and the communication module are connected with the central control module.
According to the technical scheme, the sales module comprises an image acquisition unit, an image uploading unit and a price marking unit;
the image acquisition unit is used for shooting the image information of the household appliances to be sold by the seller, and the image acquisition unit is a shooting camera; the image uploading unit is used for uploading the image information acquired by the image acquiring unit to the transaction platform; the price marking unit is used for marking the price of the household appliance for sale by a seller;
the output end of the image acquisition unit is connected with the input end of the image uploading unit, and the output ends of the account registration unit, the image uploading unit and the price marking unit are connected with the input end of the central control module;
the purchase module comprises an interface display unit, an order confirmation unit, a payment switching unit and a receiving confirmation unit;
the interface display unit is used for displaying household appliance information uploaded to the transaction platform by the sales module, and the household appliance information comprises image information, product information, price information and the like; the order confirmation unit is used for determining an order needing to be placed for purchase; the payment switching unit is used for switching to a third party payment interface to pay money; the goods receiving confirmation unit is used for confirming the goods receiving after receiving the household appliance;
the output end of the central control module is connected with the input end of an interface display unit, the output end of the interface display unit is connected with the input end of an order confirmation unit, the output end of the order confirmation unit is connected with the input end of a payment switching unit, and the output end of the central control module is connected with the input end of a receiving confirmation unit;
the sales module and the acquisition module respectively comprise an account registration unit;
the account registration unit is used for registering a transaction platform account;
the output end of the account registration unit is connected with the input end of the central control module.
According to the technical scheme, the central control module comprises a storage database, a micro-control center and a data calling unit;
the storage database is used for storing and recording various information data; the micro-control center is used for intelligently controlling the transaction platform; the data calling unit is used for calling data from the storage database, and the image analysis module and the communication module can conveniently analyze and compare big data.
According to the technical scheme, the image analysis module comprises a contour extraction unit, a coordinate system establishing unit, an inflection point analysis unit, a vector establishing unit and a similarity analysis unit;
the contour extraction unit is used for extracting contour images from the image information uploaded by the image uploading unit; the coordinate system establishing unit is used for establishing a plane rectangular coordinate system on the outline image and giving a coordinate value to each point on the outline image, so that the image information is conveniently subjected to digital processing, and the result of image analysis is more accurate; the inflection point analysis unit is used for analyzing inflection point coordinate values in the profile image; the vector establishing unit is used for establishing a two-dimensional vector according to the inflection point coordinate value; the similarity analysis unit is used for analyzing the similarity between the two-dimensional vector established by the vector component unit and the two-dimensional vector of the image information stored in the storage database and judging the truth of the image information;
the output end of the contour extraction unit is connected with the input end of the coordinate system establishing unit, the output end of the coordinate system establishing unit is connected with the input end of the inflection point analyzing unit, the output end of the inflection point analyzing unit is connected with the input end of the vector establishing unit, and the output ends of the vector establishing unit and the data calling unit are connected with the input end of the similarity analyzing unit.
According to the technical scheme, the communication exchange module comprises a time recording unit, a keyword extraction unit, a data comparison unit, a reply extraction unit and an automatic reply unit;
the keyword extraction unit is used for extracting keyword information in the problems proposed by the purchasing party, so that the comparison of the keywords is convenient, and the intention of the purchasing party is automatically judged; the data comparison unit is used for comparing and analyzing the extracted keyword information with historical chat record information in a storage database, and aims to search similar problem information so as to search corresponding reply information in historical replies; the time recording unit is used for recording the time point of the inquiry of the acquirer, so that the seller can automatically reply to the acquirer when the seller does not reply to the inquiry of the acquirer beyond the time threshold, and the transaction is facilitated to be completed; the reply extraction unit is used for extracting the matched reply information after the data comparison unit compares the reply information with the data; the automatic reply unit is used for directly sending the extracted reply information to the acquisition module;
the output ends of the keyword extraction unit and the data calling unit are connected with the input end of the data comparison unit, the output end of the data comparison unit is connected with the input end of the reply extraction unit, and the output ends of the time recording unit and the reply extraction unit are connected with the input end of the automatic reply unit.
A transaction platform method for recycling recovered household appliances under big data comprises the following steps:
s1, uploading the home appliance information to be sold to the transaction platform by using the selling module;
s2, analyzing and judging the reality degree of the household appliance information uploaded by the sales module by using the image analysis module;
s3, establishing communication between the seller and the buyer by using the communication module;
and S4, the purchasing party purchases the household appliance from the transaction platform by using the purchasing module.
According to the technical scheme, in S1, the selling module utilizes an image acquisition unit to shoot image information of the household appliances to be sold, utilizes an image uploading unit to upload the image information to a transaction platform, and utilizes a price marking unit to mark the selling price of the uploaded household appliances.
According to the above technical solution, in S2, the method specifically includes the following steps:
s201, carrying out binarization processing on the image data uploaded in the S1;
s202, extracting the outline of the image data by using an outline extraction algorithm, wherein the specific calculation step of the outline extraction algorithm is realized by adopting the prior art, so that excessive explanation is not made;
s203, establishing a plane rectangular coordinate system on the image data after the contour is extracted by using a coordinate system establishing unit, and giving a coordinate value to each contour point;
the establishment of the rectangular coordinate system takes the pixel point at the lower left corner of the image data as an origin;
the coordinate values of all contour points on the image data form a set P ═ { Q ═ Q 1 ,Q 2 ,Q 3 ,…,Q n In which Q n A set of coordinate values representing coordinate points in the nth profile in the image data, a subset Q of the set P 1 ,Q 2 ,Q 3 ,…,Q n The coordinate points are arranged from low to high according to the number of the coordinate points, so that the contour lines in the historical image data can be conveniently called from the storage database at the later stage, wherein,
wherein the content of the first and second substances,
a coordinate value representing the ith contour point on the jth contour line,
coordinate value, Q, representing the nth contour point on the jth contour line j The coordinate values in the figure are arranged in a mode that the contour points on the contour line are sequentially arranged;
s204, analyzing inflection point coordinate values of the contour by using an inflection point analyzing unit;
the analysis of the inflection points of the contour is performed according to the following formula:
wherein the content of the first and second substances,
representing coordinate points
And coordinate point
The slope therebetween;
representing coordinate points
And coordinate point
The slope therebetween;
calculated according to the following formula
And
ratio μ between:
when mu is more than or equal to delta or mu is less than or equal to epsilon, the coordinate point is shown
For one of the corners of the contour, δ and ∈ both represent the set threshold
The inflection point calculation is carried out, so that the number of coordinate points is reduced, meanwhile, the coordinate points selected by analysis are more representative, a good foundation is provided for digital analysis in the later period, and the analysis and judgment results are more accurate;
s205, establishing a two-dimensional vector of adjacent inflection points by using a vector establishing unit;
the inflection point coordinate values in each contour line in the image data form an inflection point coordinate value set
t is less than m, wherein
A coordinate value of a t-th inflection point in a j-th contour line in the image data;
the calculation of the two-dimensional vector is performed according to the following formula:
wherein the content of the first and second substances,
representation set U j A two-dimensional vector is formed between the (s-1) th inflection point and the(s) th inflection point;
composing a set of two-dimensional vectors
Wherein A is j Representing a two-dimensional vector set consisting of inflection point coordinate values of the jth contour line;
s206, analyzing the similarity between the two-dimensional vector in the image data and the two-dimensional vector of the image data stored in the storage database by using a similarity analysis unit;
the data calling unit is used for calling the image data with the same number of contour lines as the number of the contour lines uploaded by the sales module from the storage database;
selecting a contour line set W { (X) with the same number of coordinate points as that of a certain coordinate point in the set P from the retrieved image data 1 ,Y 1 ),(X 2 ,Y 2 ),(X 3 ,Y 3 ),…,(X i ,Y i ),…,(X m ,Y m )}；
Transforming coordinate points in the set W into a set of two-dimensional vectors according to the analysis process of S204-S205
The similarity analysis unit analyzes and calculates the similarity according to the following formula:
wherein the content of the first and second substances,
represents a set A j The similarity between the o-th two-dimensional vector in (a) and the o-th two-dimensional vector in (B),
represents the o-th two-dimensional vector in the j-th contour line in the image data uploaded by the sales module,
represents the o-th two-dimensional vector in the contour line retrieved from the storage database by the data retrieving unit,
to representTwo-dimensional vector
The die of (a) is used,
representing two-dimensional vectors
The die of (2);
when in use
When the number of the image data is larger than or equal to the set threshold value, the similarity is high, and the image data uploaded by the sales module is false image data;
when in use
When the number of the image data is smaller than the set threshold value, the similarity is low, and the image data uploaded by the sales module is real image data.
By the technical scheme, whether the image data uploaded by the sales module is real image data or not can be analyzed and judged, the authenticity of each image data uploaded by the sales module is guaranteed, the situation that other image data are downloaded by the sales module to be uploaded to cause cheating to a buyer is avoided, and the benefits of the buyer can be well guaranteed.
According to the above technical solution, in S3, the method specifically includes the following steps:
s301, extracting keywords in the question words of the buyer by using the keyword extraction unit, and recording the time point T of the question of the buyer by using the time recording unit 1 ；
S302, comparing the keywords extracted in the S301 with the keywords in the historical chat records stored in the storage database by using a data comparison unit;
s303, extracting the historical reply of the sentence which is the same as the question asked by the buyer in return by using a reply extraction unit according to the comparison result of the S302;
S304the time recording duration of the time recording unit is T 2 -T 1 When T is 2 -T 1 When the number of the buyer exceeds T, the seller does not reply to the buyer message within the threshold value set range, T 2 And sending the history reply information extracted by the reply extraction unit to the purchasing party by using the automatic reply unit at the time point which shows that the history reply information is changed all the time.
By the technical scheme, the inquiry sentences of the acquirer can be analyzed in the busy time period of the seller, the seller replies after the inquiry is the same as the inquiry is extracted according to the historical reply information of the seller, and when the seller does not reply after reaching the set time length threshold, the automatic reply of the acquirer message is realized, the communication is effectively promoted, and the generation of the transaction can be promoted to the greatest extent.
According to the above technical solution, in S4, the purchasing side displays the home appliance sales interface using the interface display unit, confirms the order information of the home appliance to be purchased using the order confirmation unit, switches the third party payment interface to pay using the payment switching unit, confirms the receipt using the receipt confirmation unit after receiving the goods, and transfers the transaction money to the seller account by the transaction platform.
Compared with the prior art, the invention has the beneficial effects that:
1. the image analysis module is arranged, the contour extraction unit is used for extracting the contour of the image data uploaded by the sales module, and the inflection point analysis unit and the similarity analysis unit are used for analyzing and processing the image data, so that the image data uploaded by the sales module can be judged, whether the image data is a real shot image or an image downloaded from the internet can be judged, the image data uploaded by the sales module can be more real, and the rights and interests of buyers can be guaranteed.
2. The invention is provided with a communication module, when a seller inquires about the basic information of the household appliance from an acquisition party, if the seller does not reply to the problem of the acquisition party within the specified time, the keyword extraction unit can extract the keyword of the inquiry content of the acquisition party, the inquiry problem similar to the keyword is searched from a storage database through data comparison, the historical reply of the seller is extracted through the reply extraction unit, and when the seller does not reply to the problem within the specified time, the information of the acquisition party can be replied through the automatic reply unit, so that the transaction can be promoted in time.
Drawings
FIG. 1 is a schematic diagram of a connection relationship of a recycling appliance recycling transaction platform system according to big data in the present invention;
FIG. 2 is a schematic diagram of the components of a big data recycle transaction platform system for recycled home appliances according to the present invention;
fig. 3 is a flowchart of a transaction platform method for recycling household appliances under big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 to 3, the present invention provides a technical solution of a recycled home appliance recycling transaction platform system under big data, which includes a user side for home appliance sales and home appliance acquisition and a transaction platform for home appliance transaction;
the user side is connected with the transaction platform;
the user side comprises a sale module and a purchase module;
the sale module is used for uploading the household appliance information to be sold to the transaction platform, and the purchase module is used for purchasing the household appliances uploaded by the sale module from the transaction platform; the household appliances refer to old household appliances used for a period of time;
the transaction platform comprises a central control module, an image analysis module and a communication module;
the central control module is used for carrying out intelligent control on the whole transaction platform; the image analysis module is used for analyzing the household appliance information uploaded by the sale module, ensuring the authenticity of the household appliance information, avoiding false household appliance information uploaded by a seller for facilitating sale and improving the sale price and ensuring the benefit of a buyer; the communication module is used for communicating the sales module with the acquisition module before transaction, so that the acquisition party can conveniently and fully know the product performance;
the sales module is connected with the image analysis module, the sales module and the acquisition module are connected with the communication module, and the image analysis module and the communication module are connected with the central control module.
The sales module comprises an image acquisition unit, an image uploading unit and a price marking unit;
the image acquisition unit is used for shooting image information of household appliances to be sold by a seller, and the image acquisition unit is a shooting camera; the image uploading unit is used for uploading the image information acquired by the image acquiring unit to the transaction platform; the price marking unit is used for marking the price of the household appliance for sale by a seller;
the output end of the image acquisition unit is connected with the input end of the image uploading unit, and the output ends of the account registration unit, the image uploading unit and the price marking unit are connected with the input end of the central control module;
the purchase module comprises an interface display unit, an order confirmation unit, a payment switching unit and a receiving confirmation unit;
the interface display unit is used for displaying household appliance information uploaded to the transaction platform by the sales module, and the household appliance information comprises image information, product information, price information and the like; the order confirmation unit is used for determining an order needing to be placed for purchase; the payment switching unit is used for switching to a third party payment interface to pay money; the goods receiving confirmation unit is used for confirming the goods receiving after receiving the household appliance;
the output end of the central control module is connected with the input end of an interface display unit, the output end of the interface display unit is connected with the input end of an order confirmation unit, the output end of the order confirmation unit is connected with the input end of a payment switching unit, and the output end of the central control module is connected with the input end of a receiving confirmation unit;
the sales module and the purchase module respectively comprise an account registration unit;
the account registration unit is used for registering a transaction platform account;
and the output end of the account registration unit is connected with the input end of the central control module.
The central control module comprises a storage database, a micro-control center and a data calling unit;
the storage database is used for storing and recording various information data; the micro-control center is used for intelligently controlling the transaction platform; the data calling unit is used for calling data from the storage database, and the image analysis module and the communication module can conveniently analyze and compare big data.
The image analysis module comprises a contour extraction unit, a coordinate system establishment unit, an inflection point analysis unit, a vector establishment unit and a similarity analysis unit;
the contour extraction unit is used for extracting contour images from the image information uploaded by the image uploading unit; the coordinate system establishing unit is used for establishing a plane rectangular coordinate system on the outline image and giving a coordinate value to each point on the outline image, so that the image information is conveniently subjected to digital processing, and the result of image analysis is more accurate; the inflection point analysis unit is used for analyzing inflection point coordinate values in the profile image; the vector establishing unit is used for establishing a two-dimensional vector according to the inflection point coordinate value; the similarity analysis unit is used for analyzing the similarity between the two-dimensional vector established by the vector component unit and the two-dimensional vector of the image information stored in the storage database and judging the truth of the image information;
the output end of the contour extraction unit is connected with the input end of the coordinate system establishing unit, the output end of the coordinate system establishing unit is connected with the input end of the inflection point analyzing unit, the output end of the inflection point analyzing unit is connected with the input end of the vector establishing unit, and the output ends of the vector establishing unit and the data calling unit are connected with the input end of the similarity analyzing unit.
The communication exchange module comprises a time recording unit, a keyword extraction unit, a data comparison unit, a reply extraction unit and an automatic reply unit;
the keyword extraction unit is used for extracting keyword information in the problems proposed by the purchasing party, so that the comparison of the keywords is convenient, and the intention of the purchasing party is automatically judged; the data comparison unit is used for comparing and analyzing the extracted keyword information with historical chat record information in a storage database, and aims to search similar problem information so as to search corresponding reply information in historical replies; the time recording unit is used for recording the time point of the inquiry of the acquirer, so that the seller can automatically reply to the acquirer when the seller does not reply to the inquiry of the acquirer beyond the time threshold, and the transaction is facilitated to be completed; the reply extraction unit is used for extracting the matched reply information after the data comparison unit compares the reply information with the data; the automatic reply unit is used for directly sending the extracted reply information to the acquisition module;
the output ends of the keyword extraction unit and the data retrieval unit are connected with the input end of the data comparison unit, the output end of the data comparison unit is connected with the input end of the reply extraction unit, and the output ends of the time recording unit and the reply extraction unit are connected with the input end of the automatic reply unit.
A transaction platform method for recycling household appliances under big data comprises the following steps:
s1, uploading the home appliance information to be sold to the transaction platform by using the selling module; the selling module shoots image information of the household appliances to be sold by using the image acquisition unit, uploads the image information to the transaction platform by using the image uploading unit, and marks the selling price of the uploaded household appliances by using the price marking unit;
s2, analyzing and judging the reality degree of the household appliance information uploaded by the sales module by using the image analysis module;
the method specifically comprises the following steps:
s201, carrying out binarization processing on the image data uploaded in the S1;
s202, extracting the outline of the image data by using an outline extraction algorithm, wherein the specific calculation step of the outline extraction algorithm is realized by adopting the prior art, so that excessive explanation is not made;
s203, establishing a plane rectangular coordinate system on the image data after the contour is extracted by using a coordinate system establishing unit, and giving a coordinate value to each contour point;
the establishment of the rectangular coordinate system takes the pixel point at the lower left corner of the image data as an origin;
the coordinate values of all contour points on the image data form a set P ═ { Q ═ Q 1 ,Q 2 ,Q 3 ,…,Q n In which Q n A set of coordinate values representing coordinate points in the nth profile in the image data, a subset Q of the set P 1 ,Q 2 ,Q 3 ,…,Q n The coordinate points are arranged from low to high according to the number of the coordinate points, so that the contour lines in the historical image data can be conveniently called from the storage database at the later stage, wherein,
wherein the content of the first and second substances,
a coordinate value representing the ith contour point on the jth contour line,
coordinate value, Q, representing the nth contour point on the jth contour line j The coordinate values in the figure are arranged in a mode that the contour points on the contour line are sequentially arranged;
s204, analyzing inflection point coordinate values of the contour by using an inflection point analyzing unit;
the analysis of the inflection points of the contour is performed according to the following formula:
wherein the content of the first and second substances,
representing coordinate points
And coordinate point
The slope therebetween;
representing coordinate points
And coordinate point
The slope therebetween;
calculated according to the following formula
And
ratio μ between:
when mu is more than or equal to delta or mu is less than or equal to epsilon, the coordinate point is shown
For one inflection point of the contour line, delta and epsilon both represent set thresholds;
the inflection point calculation is carried out, so that the number of coordinate points is reduced, meanwhile, the coordinate points selected by analysis are more representative, a good foundation is provided for digital analysis in the later period, and the analysis and judgment results are more accurate;
s205, establishing a two-dimensional vector of adjacent inflection points by using a vector establishing unit;
the inflection point coordinate values in each contour line in the image data form an inflection point coordinate value set
t is less than m, wherein
A coordinate value of a t-th inflection point in a j-th contour line in the image data;
the calculation of the two-dimensional vector is performed according to the following formula:
wherein the content of the first and second substances,
representation set U j A two-dimensional vector is formed between the (s-1) th inflection point and the(s) th inflection point;
composing sets of two-dimensional vectors
Wherein, A j Representing a two-dimensional vector set consisting of inflection point coordinate values of the jth contour line;
s206, analyzing the similarity between the two-dimensional vector in the image data and the two-dimensional vector of the image data stored in the storage database by using a similarity analysis unit;
the data calling unit is used for calling the image data with the same number of contour lines as the number of the contour lines uploaded by the sales module from the storage database;
selecting a contour line set W { (X) with the same number of coordinate points as that of a certain coordinate point in the set P from the retrieved image data 1 ,Y 1 ),(X 2 ,Y 2 ),(X 3 ,Y 3 ),…,(X i ,Y i ),…,(X m ,Y m )}；
Transforming coordinate points in the set W into a set of two-dimensional vectors according to the analysis process of S204-S205
The similarity analysis unit analyzes and calculates the similarity according to the following formula:
wherein the content of the first and second substances,
representation set A j The similarity between the o-th two-dimensional vector in (a) and the o-th two-dimensional vector in (B),
represents the o-th two-dimensional vector in the j-th contour line in the image data uploaded by the sales module,
represents the o-th two-dimensional vector in the contour line retrieved from the storage database by the data retrieving unit,
representing two-dimensional vectors
The die of (a) is used,
representing two-dimensional vectors
The mold of (4);
when in use
When the number of the image data is larger than or equal to the set threshold value, the similarity is high, and the image data uploaded by the sales module is false image data;
when in use
When the number of the image data is smaller than the set threshold value, the similarity is low, and the image data uploaded by the sales module is real image data.
By the technical scheme, whether the image data uploaded by the sales module is real image data or not can be analyzed and judged, the authenticity of each image data uploaded by the sales module is guaranteed, the situation that other image data are downloaded by the sales module to be uploaded to cause cheating to a buyer is avoided, and the benefits of the buyer can be well guaranteed.
S3, establishing communication between the seller and the buyer by using the communication module;
the method specifically comprises the following steps:
s301, extracting keywords in the question words of the buyer by using the keyword extraction unit, and recording the time point T of the question of the buyer by using the time recording unit 1 ；
S302, comparing the keywords extracted in the S301 with the keywords in the historical chat records stored in the storage database by using a data comparison unit;
s303, extracting the historical reply of the sentence which is the same as the question asked by the buyer in return by using a reply extraction unit according to the comparison result of the S302;
s304, the time recording duration of the time recording unit is T 2 -T 1 When T is 2 -T 1 When the value is more than or equal to T, the seller does not reply to the buyer message within the threshold value setting range, T 2 And sending the history reply information extracted by the reply extraction unit to the purchasing party by using the automatic reply unit at the time point which shows that the history reply information is changed all the time.
By the technical scheme, the inquiry sentences of the acquirer can be analyzed in the busy time period of the seller, the seller replies after the inquiry is the same as the inquiry is extracted according to the historical reply information of the seller, and when the seller does not reply after reaching the set time length threshold, the automatic reply of the acquirer message is realized, the communication is effectively promoted, and the generation of the transaction can be promoted to the greatest extent.
S4, the purchasing party purchases the household appliance from the transaction platform by using the purchasing module;
the purchasing side displays the household appliance selling interface by using the interface display unit, confirms the order information of the household appliance needing to be purchased by using the order confirmation unit, switches the third-party payment interface to pay by using the payment switching unit, confirms the receipt by using the receipt confirmation unit after receiving the commodity, and transfers the transaction money to the account of the selling side by using the transaction platform.
The first embodiment is as follows:
s1, uploading the home appliance information to be sold to the transaction platform by using the selling module; the selling module shoots image information of the household appliances to be sold by using the image acquisition unit, uploads the image information to the transaction platform by using the image uploading unit, and marks the selling price of the uploaded household appliances by using the price marking unit;
s2, analyzing and judging the reality degree of the household appliance information uploaded by the sales module by using the image analysis module;
the method specifically comprises the following steps:
s201, carrying out binarization processing on the image data uploaded in the S1;
s202, extracting the outline of the image data by utilizing an outline extraction algorithm;
s203, establishing a plane rectangular coordinate system on the image data after the contour is extracted by using a coordinate system establishing unit, and giving a coordinate value to each contour point;
the establishment of the rectangular coordinate system takes the pixel point at the lower left corner of the image data as an origin;
the coordinate values of all contour points on the image data form a set P ═ { Q ═ Q 1 ,Q 2 ,Q 3 ,…,Q 10 In which Q 10 Representing a coordinate point in the 10 th contour in the image dataThe formed set of coordinate values, subset Q of the set P 1 ,Q 2 ,Q 3 ,…,Q 10 The coordinate points are arranged from low to high according to the number of the coordinate points contained in the coordinate points, wherein,
wherein the content of the first and second substances,
coordinate values representing the ith contour point on the 2 nd contour line,
coordinate value, Q, representing the 30 th contour point on the 2 nd contour line 2j The coordinate values in the figure are arranged in a mode that contour points on the contour line are sequentially arranged;
s204, analyzing inflection point coordinate values of the contour by using an inflection point analyzing unit;
the analysis of the inflection points of the contour is performed according to the following formula:
calculated according to the following formula
And
ratio μ between:
when mu is less than or equal to epsilon equal to 0, the coordinate point is indicated
One inflection point of the contour line;
the analysis of the inflection points of the contour line is performed according to the following formula:
calculated according to the following formula
And
ratio μ between:
when mu is less than or equal to epsilon equal to 0, the coordinate point is indicated
One inflection point of the contour line;
the analysis of the inflection points of the contour is performed according to the following formula:
calculated according to the following formula
And
ratio μ between:
when mu is less than or equal to epsilon equal to 0, the coordinate point is indicated
Is one inflection point of the contour line;
s205, establishing a two-dimensional vector of adjacent inflection points by using a vector establishing unit;
the inflection point coordinate values in each contour line in the image data form an inflection point coordinate value set
Wherein
A 3 rd inflection point coordinate value in a 2 nd contour line in the image data;
the calculation of the two-dimensional vector is performed according to the following formula:
composing a set of two-dimensional vectors
Wherein A is 2 A two-dimensional vector set consisting of inflection point coordinate values representing the 2 nd contour line;
s206, analyzing the similarity between the two-dimensional vector in the image data and the two-dimensional vector of the image data stored in the storage database by using a similarity analysis unit;
the data calling unit is used for calling the image data with the same number of contour lines as the number of the contour lines uploaded by the sales module from the storage database;
selecting a contour line set W { (X) with the same number of coordinate points as that of a certain coordinate point in the set P from the retrieved image data 1 ,Y 1 ),(X 2 ,Y 2 ),(X 3 ,Y 3 ),…,(X i ,Y i ),…,(X m ,Y m )}；
Transforming coordinate points in the set W into a set of two-dimensional vectors according to the analysis process of S204-S205
The similarity analysis unit analyzes and calculates the similarity according to the following formula:
and the trading platform downloads the image data uploaded by the selling module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A transaction platform system is recycled to recovery household electrical appliances under big data, its characterized in that: the system comprises a user side for selling and purchasing the household appliances and a transaction platform for performing household appliance transaction;
the user side is connected with the transaction platform;
the user side comprises a sale module and a purchase module;
the sale module is used for uploading the household appliance information to be sold to the transaction platform, and the purchase module is used for purchasing the household appliances uploaded by the sale module from the transaction platform;
the transaction platform comprises a central control module, an image analysis module and a communication module;
the central control module is used for carrying out intelligent control on the whole transaction platform; the image analysis module is used for analyzing the household appliance information uploaded by the sale module to ensure the authenticity of the household appliance information; the communication module is used for communicating the selling module with the purchasing module before transaction;
the sales module is connected with the image analysis module, the sales module and the acquisition module are connected with the communication module, and the image analysis module and the communication module are connected with the central control module.
2. The big data recycling transaction platform system for household appliances according to claim 1, wherein the big data recycling transaction platform system comprises: the sales module comprises an image acquisition unit, an image uploading unit and a price marking unit;
the image acquisition unit is used for shooting the image information of the household appliances to be sold by the seller; the image uploading unit is used for uploading the image information acquired by the image acquiring unit to the transaction platform;
the output end of the image acquisition unit is connected with the input end of the image uploading unit, and the output ends of the account registration unit, the image uploading unit and the price marking unit are connected with the input end of the central control module;
the purchase module comprises an interface display unit, an order confirmation unit, a payment switching unit and a receiving confirmation unit;
the interface display unit is used for displaying the household appliance information uploaded to the transaction platform by the sales module; the order confirmation unit is used for determining an order needing to be placed for purchase; the payment switching unit is used for switching to a third party payment interface to pay money; the goods receiving confirmation unit is used for confirming the goods receiving after receiving the household appliance;
the output end of the central control module is connected with the input end of an interface display unit, the output end of the interface display unit is connected with the input end of an order confirmation unit, the output end of the order confirmation unit is connected with the input end of a payment switching unit, and the output end of the central control module is connected with the input end of a receiving confirmation unit;
the sales module and the purchase module respectively comprise an account registration unit;
the account registration unit is used for registering a transaction platform account;
the output end of the account registration unit is connected with the input end of the central control module.
3. The big data recycling transaction platform system according to claim 2, wherein: the central control module comprises a storage database, a micro-control center and a data calling unit;
the storage database is used for storing and recording various information data; the micro-control center is used for carrying out intelligent control on the transaction platform; the data calling unit is used for calling data from a storage database.
4. The big data recycling transaction platform system according to claim 3, wherein: the image analysis module comprises a contour extraction unit, a coordinate system establishment unit, an inflection point analysis unit, a vector establishment unit and a similarity analysis unit;
the contour extraction unit is used for extracting contour images from the image information uploaded by the image uploading unit; the coordinate system establishing unit is used for establishing a plane rectangular coordinate system on the outline image and giving a coordinate value to each point on the outline image; the inflection point analysis unit is used for analyzing inflection point coordinate values in the profile image; the vector establishing unit is used for establishing a two-dimensional vector according to the inflection point coordinate value; the similarity analysis unit is used for analyzing the similarity between the two-dimensional vector established by the vector component unit and the two-dimensional vector of the image information stored in the storage database and judging the truth of the image information;
the output end of the contour extraction unit is connected with the input end of the coordinate system establishing unit, the output end of the coordinate system establishing unit is connected with the input end of the inflection point analyzing unit, the output end of the inflection point analyzing unit is connected with the input end of the vector establishing unit, and the output ends of the vector establishing unit and the data calling unit are connected with the input end of the similarity analyzing unit.
5. The big data recycling transaction platform system according to claim 4, wherein: the communication exchange module comprises a time recording unit, a keyword extraction unit, a data comparison unit, a reply extraction unit and an automatic reply unit;
the keyword extraction unit is used for extracting keyword information in the questions proposed by the purchasing party; the data comparison unit is used for comparing and analyzing the extracted keyword information with historical chat record information in a storage database; the time recording unit is used for recording the time point of the inquiry of the acquirer; the reply extraction unit is used for extracting the matched reply information after the data comparison unit compares the reply information with the data; the automatic reply unit is used for directly sending the extracted reply information to the acquisition module;
the output ends of the keyword extraction unit and the data calling unit are connected with the input end of the data comparison unit, the output end of the data comparison unit is connected with the input end of the reply extraction unit, and the output ends of the time recording unit and the reply extraction unit are connected with the input end of the automatic reply unit.
6. A transaction platform method for recycling household appliances under big data is characterized in that: the method comprises the following steps:
s1, uploading the home appliance information to be sold to the transaction platform by using the selling module;
s2, analyzing and judging the reality degree of the household appliance information uploaded by the sales module by using the image analysis module;
s3, establishing communication between the seller and the buyer by using the communication module;
and S4, the purchasing party purchases the household appliance from the transaction platform by using the purchasing module.
7. The big data recycling transaction platform method of claim 6, wherein the big data recycling transaction platform method comprises the following steps: in S1, the selling module captures image information of the home appliance to be sold by using the image acquiring unit, uploads the image information to the transaction platform by using the image uploading unit, and labels the selling price of the uploaded home appliance by using the price labeling unit.
8. The big data recycling transaction platform method of claim 7, wherein the big data recycling transaction platform method comprises the following steps: in S2, the method specifically includes the following steps:
s201, carrying out binarization processing on the image data uploaded in the S1;
s202, extracting the outline of the image data by utilizing an outline extraction algorithm;
s203, establishing a plane rectangular coordinate system on the image data after the contour is extracted by using a coordinate system establishing unit, and giving a coordinate value to each contour point;
the establishment of the rectangular coordinate system takes pixel points at the lower left corner of the image data as an origin;
coordinate values of all contour points on the image dataComposition set P ═ { Q ═ Q 1 ,Q 2 ,Q 3 ,…,Q n In which Q n A set of coordinate values representing coordinate points in the nth profile in the image data, a subset Q of the set P 1 ,Q 2 ,Q 3 ,…,Q n The coordinate points are arranged from low to high according to the number of the coordinate points contained in the coordinate points, wherein,
wherein the content of the first and second substances,
coordinate values indicating the ith contour point on the jth contour line,
coordinate value, Q, representing the nth contour point on the jth contour line j The coordinate values in the figure are arranged in a mode that contour points on the contour line are sequentially arranged;
s204, analyzing inflection point coordinate values of the contour by using an inflection point analyzing unit;
the analysis of the inflection points of the contour is performed according to the following formula:
wherein the content of the first and second substances,
representing coordinate points
And coordinate point
A slope therebetween;
representing coordinate points
And coordinate point
The slope therebetween;
calculated according to the following formula
And
ratio μ between:
when mu is more than or equal to delta or mu is less than or equal to epsilon, the coordinate point is shown
For one inflection point of the contour line, delta and epsilon both represent set thresholds;
s205, establishing a two-dimensional vector of adjacent inflection points by using a vector establishing unit;
inflection point coordinate values in each contour line in image data form an inflection point coordinate value set
t is less than m, wherein
A coordinate value of a t-th inflection point in a j-th contour line in the image data;
the calculation of the two-dimensional vector is performed according to the following formula:
wherein the content of the first and second substances,
representation set U j A two-dimensional vector is formed between the (s-1) th inflection point and the(s) th inflection point;
composing a set of two-dimensional vectors
Wherein A is j Representing a two-dimensional vector set consisting of inflection point coordinate values of the jth contour line;
s206, analyzing the similarity between the two-dimensional vector in the image data and the two-dimensional vector of the image data stored in the storage database by using a similarity analysis unit;
the data calling unit is used for calling the image data with the same number of contour lines as the number of the contour lines uploaded by the sales module from the storage database;
selecting a contour line set W { (X) with the same number of coordinate points as that of a certain coordinate point in the set P from the retrieved image data 1 ,Y 1 ),(X 2 ,Y 2 ),(X 3 ,Y 3 ),…,(X i ,Y i ),…,(X m ,Y m )}；
Transforming coordinate points in the set W into a set of two-dimensional vectors according to the analysis process of S204-S205
The similarity analysis unit analyzes and calculates the similarity according to the following formula:
wherein the content of the first and second substances,
representation set A j The similarity between the o-th two-dimensional vector in (a) and the o-th two-dimensional vector in the set B,
represents the o-th two-dimensional vector in the j-th contour line in the image data uploaded by the sales module,
represents the o-th two-dimensional vector in the contour line retrieved from the storage database by the data retrieving unit,
representing two-dimensional vectors
The die of (a) is used,
representing two-dimensional vectors
The mold of (4);
when in use
When the number of the image data is larger than or equal to the set threshold value, the similarity is high, and the image data uploaded by the sales module is false image data;
when in use
When the number of the image data is smaller than the set threshold value, the similarity is low, and the image data uploaded by the sales module is real image data.
9. The big data recycling transaction platform method for the household appliances under the condition of claim 8, wherein the method comprises the following steps: in S3, the method specifically includes the following steps:
s301, extracting keywords in the question words of the buyer by using the keyword extraction unit, and recording the time point T of the question of the buyer by using the time recording unit 1 ；
S302, comparing the keywords extracted in the S301 with the keywords in the historical chat records stored in the storage database by using a data comparison unit;
s303, extracting the historical reply of the sentence which is the same as the question asked by the buyer in return by using a reply extraction unit according to the comparison result of the S302;
s304, the time recording duration of the time recording unit is T 2 -T 1 When T is 2 -T 1 When the value is more than or equal to T, the seller does not reply to the buyer message within the threshold value setting range, T 2 And sending the history reply information extracted by the reply extraction unit to the purchasing party by using the automatic reply unit at the time point which shows that the history reply information is changed all the time.
10. The big data recycling transaction platform method of claim 9, wherein: in S4, the purchasing side displays the home appliance sales interface using the interface display unit, confirms the order information of the home appliance to be purchased using the order confirmation unit, switches the third party payment interface to pay using the payment switching unit, confirms the receipt using the receipt confirmation unit after receiving the goods, and transfers the transaction money to the seller account by the transaction platform.
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