CN113298525A - Data asset transaction method based on block chain - Google Patents
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Abstract
The invention belongs to the technical field of data transaction, and particularly relates to a data asset transaction method based on a block chain, which comprises the following steps: an uploading step, classifying the data of the holder in a data abstract and actual data mode, storing and chaining the data abstract in a clear text mode, and storing and chaining the actual data in a cipher text mode; receiving, namely receiving a purchase application of a purchaser by a platform, wherein the purchase application comprises a decrypted data type, a decrypted data amount and a holder identity; a data packaging step, after the purchase application is verified by the platform, sending an application decryption transaction and chaining according to the content of the purchase application, encrypting the actual data after the actual data corresponding to the application decryption transaction is obtained, and encrypting the decryption element into a ciphertext which can be decrypted only by a purchaser and then chaining; and a data acquisition step, namely after the block of the purchaser is analyzed to obtain the decryption element, decrypting the ciphertext to obtain the required data. The application can improve the safety of data transaction.
Description
Technical Field
The invention belongs to the technical field of data transaction, and particularly relates to a data asset transaction method based on a block chain.
Background
In the big data era, in order to better analyze own business and competitive product business and further control the market, a plurality of enterprises can purchase a large amount of data required by themselves. Therefore, data sharing and transaction become a current hotspot. However, the data has a large difference compared with the traditional goods, so that the data is easy to lose, copy and need to be kept secret. Thus, there are higher demands on the processing power of the transaction, traceability of the transaction process, integrity of the transaction data and reliability.
However, on the traditional trading platform, the integrity and confidentiality of the trading data are difficult to guarantee; meanwhile, due to the non-transparency of the traditional transaction, the history of the transaction is difficult to trace, and the files in the transaction process are possibly tampered, so that fraud is easy to breed.
Disclosure of Invention
The invention aims to provide a data asset transaction method based on a block chain, which can improve the security of data transaction.
The basic scheme provided by the invention is as follows:
a data asset transaction method based on a blockchain comprises the following steps:
an uploading step, classifying the data of the holder in a data abstract and actual data mode, storing and chaining the data abstract in a clear text mode, and storing and chaining the actual data in a cipher text mode;
receiving, namely receiving a purchase application of a purchaser by a platform, wherein the purchase application comprises a decrypted data type, a decrypted data amount and a holder identity;
a data packaging step, after the purchase application is verified by the platform, sending an application decryption transaction and chaining according to the content of the purchase application, encrypting the actual data after the actual data corresponding to the application decryption transaction is obtained, and encrypting the decryption element into a ciphertext which can be decrypted only by a purchaser and then chaining;
and a data acquisition step, namely after the block of the purchaser is analyzed to obtain the decryption element, decrypting the ciphertext to obtain the required data.
Basic scheme theory of operation and beneficial effect:
when the data is stored, the data abstract is stored in a plaintext mode, and the actual data is stored in a ciphertext mode. The buyer can know the characteristics such as the type, the data quantity and the like of the data provided by the data provider through the data abstract; meanwhile, the situation that data is divulged of actual data can be avoided. In addition, the data of the holder can be uplink after being stored, so that the data can be prevented from being tampered.
When a buyer purchases data, the buyer can know which data are needed by the buyer through the data abstract, and after the data needed by the buyer are determined, the buyer can send the data needed by the buyer to a platform in a decryption application form. After the platform receives the decryption application, the platform carries out identity verification on the decryption application, analyzes the data which the buyer wants to purchase according to the content of the decryption application after the verification is passed, encrypts the analyzed data, and encrypts the decryption elements into the ciphertext which can be decrypted only by the buyer and then carries out cochain. After the purchaser obtains the decryption element through decryption, the purchaser can decrypt the data encrypted by the previous system to obtain the data required by the purchaser. Therefore, the data required by the buyer can be accurately sent to the other side, and the data is prevented from falling into other hands.
Because the whole process of purchasing data by the purchaser carries out the uplink operation, the whole purchasing process can be traced when the data is abnormal, and the behavior that the fraudulent purchaser passes through the data provider can be prevented.
In conclusion, the scheme can improve the safety of data transaction.
Further, in the uploading step, when the actual data is stored in a ciphertext mode, a random number is generated as a temporary secret key K, the temporary secret key K is used for symmetrically encrypting the actual data to obtain a ciphertext S, the private key of the data holder is used for symmetrically encrypting the temporary secret key K to obtain Ks, the Ks + S are connected in series and stored in txData, then the data holder sends the uploading transaction to the chain, and the uploading transaction is initiated.
The storage mode ensures the safety and the confidentiality of actual data.
Further, in the uploading step, when the data abstract is stored in a plaintext mode, the data abstract is stored in a mark.
The holder can conveniently display the actual data of the holder through the data abstract, and the purchaser can conveniently judge whether the actual data is the required data.
Further, in the uploading step, after the data holder sends the upload transaction to the chain, when the platform synchronizes to the uplink transaction through the block chain node, the remark is analyzed, and the type, the data volume, the holder identity and the transaction hash of the data are stored in the local database and are included in the available data range.
The data abstract is convenient to classify and manage, and meanwhile, a purchaser can search and check the data abstract conveniently.
Further, in the data packaging step, after the platform passes the verification of the purchase application, the platform analyzes the data description required by the purchaser and finds out the data required to be decrypted, and then sends the application for decryption transaction, wherein txData for the application for decryption transaction comprises a hash list required to be decrypted; after the block of the provider is synchronized to the application of decryption transaction, if the Hash list in the application of decryption transaction is sent by the provider, a shipment order is generated in the local system, and the transaction is broadcasted.
The safety and the confidentiality of the data transaction process are ensured, and if a subsequent buyer and a holder compete, the transaction can be traced.
Further, in the data packing step, when the provider generates the shipment order locally, the provider firstly accepts the application of the decryption transaction and finds out the data description of the transaction, then analyzes txData applied for the decryption transaction to take out the cipher text Ks of the temporary key, symmetrically decrypts the cipher text Ks of the temporary key by using the private key of the provider to obtain the key k, then uses the public key of the purchaser to asymmetrically encrypt the key k to obtain the cipher text Ks2, then creates the decryption shipment transaction, stores the application form transaction hash, the transaction hash of the reported data and the cipher key cipher text Ks2 into the txData of the decryption shipment transaction, and broadcasts the transaction.
The method can ensure that the holder can not miss the purchase request initiated to the holder, and simultaneously, the method can also ensure the safety and the confidentiality of the data when the holder sells the data.
Further, in the data packaging step, encrypting the actual data after acquiring the actual data corresponding to the application decryption transaction specifically includes: after the platform synchronizes with the decrypted shipment transaction through the block chain node, whether the platform is a response of applying for the decrypted transaction sent by the platform is judged, if so, a plaintext key k of Ks2 is decrypted through a private key, actual data in the shipment transaction is decrypted through the plaintext key k to obtain a plaintext of the actual data, and then the actual data is encrypted.
Therefore, the data of the holder can be always in a safe state in the data transaction process.
Further, the method also comprises a recording step and a recommending step; recording, namely recording a data abstract viewing record and a purchase application record of a purchaser by a platform; and a recommendation step, wherein the platform checks the record and the purchase application record according to the abstract of the buyer, and performs data recommendation for the buyer after performing behavior analysis on the buyer.
The platform records the operation of checking the abstract and the purchase application of the buyer, analyzes the behavior of the buyer, and carries out data recommendation on the buyer after analyzing the required actual data. Therefore, on one hand, the workload of a purchaser for checking the data abstract one by one can be reduced, on the other hand, the idea of the purchaser can be expanded through data recommendation, a more ideal mode of using a plurality of data in a combined mode is probably thought, the purchased data is more fully used, and the purchaser can conveniently purchase more applicable data.
Further, the abstract checking record comprises checking time, duration of checking the abstract and identification information of the abstract; the purchase requisition record includes a purchase time, a data type, and a data amount for requisition for purchase.
Through the information records, data such as the checking frequency and the like can be counted, the purchasing behavior of the purchaser is comprehensively and accurately analyzed, the purchasing preference of the purchaser is deduced, and the data recommendation of the purchaser is facilitated in a targeted manner.
Further, in the recommending step, within a preset duration, if the abstracts are viewed and recorded in a preset quantity range and browsed back and forth, the platform performs characteristic analysis on the identification information of the browsed abstracts and searches whether a data abstract containing a plurality of characteristics of the browsed abstracts exists, and if the data abstract exists, the corresponding data abstract is pushed to a purchaser;
within a preset time length, if the number of the browsed data summaries is greater than X and the browsing time lengths of the continuous Y data summaries are all smaller than a first preset time length, whether a purchase application record exists within a second preset time length or not is analyzed; if the purchase application record exists, the platform combines the purchase record and pushes a data abstract corresponding to the data which can be used in combination with the purchased data to the purchaser; if the purchase record does not exist, the platform analyzes the browsing path according to the sequence of the browsed data summaries, the browsing path analysis comprises the field, the area and the data generation time of the data summaries, browsing prediction is carried out according to the browsing path analysis, and the predicted data summaries are pushed to a purchaser; and the second preset time length is greater than the first preset time length.
Has the advantages that:
if the buyer browses back and forth among the abstracts within the preset quantity range within the preset duration, the buyer is in a knotting stage at present, namely the buyer knows which data is needed by the buyer, but the browsed data abstracts can meet part of the requirements of the buyer but cannot directly meet all the requirements of the buyer. At this moment, avoid blind recommendation, otherwise can make buyer more knot, in this scheme, the platform can carry out characteristic analysis to the identifying information of the abstract of browsing to whether look for the data abstract that contains a plurality of browsing abstract characteristics, if there is, then this data abstract is equivalent to the upgrade version that present buyer is browsing the data abstract, can press close to buyer's demand more, consequently, the platform is with the data abstract propelling movement that corresponds for buyer, more accurate, comprehensive satisfaction buyer's actual demand.
If the number of the data abstracts browsed by the buyer is larger than X within the preset time length, and the browsing time lengths of the continuous Y data abstracts are all smaller than the first preset time length, the buyer is only browsing at will and does not have definite buying intention. At this time, the platform end analyzes whether the purchase application record exists within a second preset time. If the purchase record exists, the purchaser is indicated to finish the purchase purpose, at this time, strolling is possible, but the purchase data can also be supplemented, so that the platform pushes a data abstract corresponding to the data which can be used in combination with the purchased data to the purchaser in combination with the purchase record, and thus, the data recommended to the purchaser can be used in combination with the purchased data, the idea is convenient to open for the purchaser, and a better data analysis method is realized. If no purchase record exists, the motivation of the buyer can not be determined at all and data recommendation can only be carried out for the buyer along the thought of the buyer, so that the platform carries out browsing path analysis according to the sequence of the browsed data abstracts, the browsing path analysis comprises the field, the region and the data generation time of the data abstracts, browsing prediction is carried out according to the browsing path analysis, data conforming to the prediction is pushed to the buyer, and the time for manually searching the wanted data abstracts can be reduced for the buyer.
Drawings
FIG. 1 is a flow chart of a first embodiment of the present invention;
fig. 2 is a schematic diagram of a transaction flow according to an embodiment of the invention.
Detailed Description
The following is further detailed by the specific embodiments:
example one
As shown in fig. 1 and 2, the data asset transaction method based on the block chain includes:
and an uploading step, classifying the data of the holder in a data abstract and actual data mode, storing and chaining the data abstract in a clear text mode, and storing and chaining the actual data in a cipher text mode. When the data abstract is stored in a plaintext mode, the data abstract is stored in a mark; in this embodiment, the data digest in the remark is stored in the plaintext in JSON format. When actual data is stored in a ciphertext mode, a random number is generated as a temporary secret key K, the temporary secret key K is used for symmetrically encrypting the actual data to obtain a ciphertext S, a private key of a data holder is used for symmetrically encrypting the temporary secret key K to obtain Ks, the Ks + S are connected in series and stored in txData, then the data holder sends an upload transaction to a chain, and an uplink transaction is initiated. After the data holder sends the upload transaction to the chain, when the platform synchronizes to the upload transaction through the block chain node, the remark is analyzed, and the type, the data volume, the holder identity and the transaction hash of the data are stored in a local database and are included in an available data range. Therefore, the data abstract is convenient to manage and a purchaser can check the data abstract conveniently. The transaction Hash (also called TxHash) is the transaction number, which makes each transaction corresponding to the Hash a unique transaction.
And a receiving step, wherein the platform receives a purchase request of a purchaser, and the purchase request comprises the decrypted data type, the data amount and the holder identity.
And a data packaging step, namely after the purchase application is verified by the platform, sending an application decryption transaction and chaining according to the content of the purchase application, encrypting the actual data after the actual data corresponding to the application decryption transaction is obtained, and encrypting the decryption element into a ciphertext which can be decrypted only by a purchaser and then chaining. The encrypting the actual data after acquiring the actual data corresponding to the application decryption transaction specifically comprises: after the platform synchronizes with the decrypted shipment transaction through the block chain node, whether the platform is a response of applying for the decrypted transaction sent by the platform is judged, if so, a plaintext key k of Ks2 is decrypted through a private key, actual data in the shipment transaction is decrypted through the plaintext key k to obtain a plaintext of the actual data, and then the actual data is encrypted.
In the data packaging step, after the purchase application is verified by the platform, the data description required by the purchaser is analyzed, the data required to be decrypted is found out, the application decryption transaction is sent, and the txData required to be decrypted comprises a hash list required to be decrypted; after the block of the provider is synchronized to the application of decryption transaction, if the Hash list in the application of decryption transaction is sent by the provider, a shipment order is generated in the local system, and the transaction is broadcasted. When a provider generates a shipment order locally, the provider firstly accepts an application for a decryption transaction and finds out a data description needing transaction, then analyzes txData applying the decryption transaction to take out a cipher text Ks of a temporary key, symmetrically decrypts the cipher text Ks of the temporary key by using a private key of the provider to obtain a key k, then uses a public key of a purchaser to asymmetrically encrypt the key k to obtain a cipher text Ks2, then creates a decryption shipment transaction, stores a request form transaction hash, a transaction hash of reported data and a key cipher text Ks2 in the txData decrypting the shipment transaction, and broadcasts the transaction.
And a data acquisition step, namely after the block of the purchaser is analyzed to obtain the decryption element, decrypting the ciphertext to obtain the required data.
In the method, a purchaser, a platform and a holder respectively have respective blocks. When the method is used for storing the data of the data holder, the data abstract part and the actual data part are stored separately and linked up. The plaintext storage of the data abstract part is convenient for a data purchaser to conveniently check the related introduction of the data, and the actual data is stored in a ciphertext mode to prevent the data leakage. Thus, the data holder can be effectively publicized and displayed while preventing the actual data from being leaked.
When a buyer purchases data, the buyer can know which data are needed by the buyer, for example, the buyer needs to analyze the sports consumption situation of the city A, and can focus on checking research data related to the region of the city A, the field and the sports consumption through the data abstract. And the buyer can find the required data by combining the data volume and the research time.
After the data needed by the buyer is determined, the buyer can send the data needed by the buyer to the platform in a decryption application form. After the platform receives the decryption application, the platform carries out identity verification on the decryption application, analyzes the data which the buyer wants to purchase according to the content of the decryption application after the verification is passed, encrypts the analyzed data, and encrypts the decryption elements into the ciphertext which can be decrypted only by the buyer and then carries out cochain. After the purchaser obtains the decryption element through decryption, the purchaser can decrypt the data encrypted by the previous system to obtain the data required by the purchaser. Therefore, the data required by the buyer can be accurately sent to the other side, and the data is prevented from falling into other hands.
Example two
Different from the first embodiment, the present embodiment further includes:
recording, namely recording a data abstract viewing record and a purchase application record of a purchaser by a platform; the abstract checking record comprises checking time, duration of checking the abstract and identification information of the abstract; the purchase requisition record includes a purchase time, a data type, and a data amount for requisition for purchase.
And a recommendation step, wherein the platform checks the record and the purchase application record according to the abstract of the buyer, and performs data recommendation for the buyer after performing behavior analysis on the buyer.
In the recommending step, within a preset duration, if the abstracts are browsed back and forth among abstracts recorded within a preset quantity range, the platform analyzes the characteristics of the identification information of the browsed abstracts and searches whether a data abstract containing a plurality of characteristics of the browsed abstracts exists, and if the data abstract exists, the corresponding data abstract is pushed to a purchaser. The specific value of the preset number can be specifically set by those skilled in the art according to the type number and the data size of the abstract provided by the system, and the value of the preset number is 7 in this embodiment.
Within a preset time length, if the number of the browsed data summaries is greater than X and the browsing time lengths of the continuous Y data summaries are all smaller than a first preset time length, whether a purchase application record exists within a second preset time length or not is analyzed; if the purchase application record exists, the platform combines the purchase record and pushes a data abstract corresponding to the data which can be used in combination with the purchased data to the purchaser; if the purchase record does not exist, the platform analyzes the browsing path according to the sequence of the browsed data summaries, the browsing path analysis comprises the field, the area and the data generation time of the data summaries, browsing prediction is carried out according to the browsing path analysis, and the predicted data summaries are pushed to a purchaser; and the second preset time length is greater than the first preset time length. The numerical values of X and Y can be specifically set by those skilled in the art according to the amount of the data summary, in this embodiment, X is 15, and Y is 8.
In the scheme, the platform records the operation of checking the abstract and the purchase application of the buyer, performs behavior analysis on the buyer, and performs data recommendation on the buyer after analyzing the required actual data.
Specifically, if the abstracts are viewed and recorded in the abstracts within the preset quantity range within the preset duration, the abstracts indicate that the purchaser is in a knotting stage at present, that is, the purchaser knows which data the purchaser needs, but the browsed data abstracts can meet part of the requirements, but cannot directly meet all the requirements. For example, the collection time of a certain data summary is relatively new but the data volume is small, the data volume of a certain data summary is relatively large but the geographical range is small, and the geographical range of a certain data summary is relatively large but the collection time is too long. At this point, blind recommendations are avoided, otherwise the purchaser is more concerned. In this scheme, the platform can be after the characteristics of these data summaries of analysis, whether look for have the data summary that acquisition time is newer, the data bulk is bigger and the region scope is bigger, perhaps the three is all just more balanced data summary poor, if there is, then the data summary propelling movement that the platform will look for gives the buyer, this data summary is equivalent to present buyer and is just browsing the upgrade version of data summary, can press close to buyer's demand more, consequently, more accurate, comprehensive satisfies buyer's actual demand.
If the number of the data abstracts browsed by the buyer is larger than X within the preset time length, and the browsing time lengths of the continuous Y data abstracts are all smaller than the first preset time length, the buyer is only browsing at will and does not have definite buying intention. At this time, the platform end analyzes whether the purchase application record exists within a second preset time. If a record of the purchase exists, it indicates that the purchaser has completed the purchase, which may be strolling, but may also be supplementing the data for the purchase. For example, the purchased data covers the data of all cities except city C in the southwest region, and the browsing purpose of the purchased data can be the data which is wanted to supplement city C; in addition, it is also possible that the buyer is looking for data that can be used in combination with the purchased data, for example, the purchased data is research data about the viewing intention of the sports event on site, and then the research data about the sports consumption can be combined and analyzed as the data of the collocation. Therefore, the platform combines the purchase record to push the data abstract corresponding to the data which can be used in combination with the purchased data to the purchaser, so that the data recommended to the purchaser can be used in combination with the purchased data, the purchase desire of the purchaser is enhanced, the data can be conveniently analyzed by combining with other data after the purchaser purchases the data, and the use value of the data is improved.
If the purchaser does not purchase a record within a second predetermined length of time, the purchaser's motivation to view the summary is completely uncertain, perhaps just in knowing which data the platform is capable of providing, and perhaps wanting to purchase data but not yet determining what data should be purchased. At the moment, data recommendation can be carried out only along the thought of the platform, so that the platform carries out browsing path analysis according to the sequence of the browsed data summaries, the browsing path analysis comprises the data generation time of the fields and the regions of the data summaries, browsing prediction is carried out according to the browsing path analysis, and data conforming to the prediction is pushed to a purchaser. Therefore, the time for manually searching the demand data can be reduced for the buyer, and the use experience of the buyer is improved.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The data asset transaction method based on the block chain is characterized by comprising the following steps:
an uploading step, classifying the data of the holder in a data abstract and actual data mode, storing and chaining the data abstract in a clear text mode, and storing and chaining the actual data in a cipher text mode;
receiving, namely receiving a purchase application of a purchaser by a platform, wherein the purchase application comprises a decrypted data type, a decrypted data amount and a holder identity;
a data packaging step, after the purchase application is verified by the platform, sending an application decryption transaction and chaining according to the content of the purchase application, encrypting the actual data after the actual data corresponding to the application decryption transaction is obtained, and encrypting the decryption element into a ciphertext which can be decrypted only by a purchaser and then chaining;
and a data acquisition step, namely after the block of the purchaser is analyzed to obtain the decryption element, decrypting the ciphertext to obtain the required data.
2. The blockchain-based data asset transaction method of claim 1, wherein: in the uploading step, when the actual data is stored in a ciphertext mode, a random number is generated as a temporary secret key K, the temporary secret key K is used for symmetrically encrypting the actual data to obtain a ciphertext S, a private key of a data holder is used for symmetrically encrypting the temporary secret key K to obtain Ks, the Ks + S are connected in series and stored in txData, then the data holder sends the uploading transaction to a chain, and the uploading transaction is initiated.
3. The blockchain-based data asset transaction method of claim 2, wherein: in the uploading step, when the data abstract is stored in a plaintext mode, the data abstract is stored in a mark.
4. The blockchain-based data asset transaction method of claim 3, wherein: in the uploading step, after the data holder sends the upload transaction to the chain, when the platform synchronizes to the uplink transaction through the block chain node, the remark is analyzed, and the type, the data volume, the holder identity and the transaction hash of the data are stored in a local database and are included in the available data range.
5. The blockchain-based data asset transaction method of claim 4, wherein: in the data packaging step, after the purchase application is verified by the platform, the data description required by the purchaser is analyzed, the data required to be decrypted is found out, the application decryption transaction is sent, and the txData required to be decrypted comprises a hash list required to be decrypted; after the block of the provider is synchronized to the application of decryption transaction, if the Hash list in the application of decryption transaction is sent by the provider, a shipment order is generated in the local system, and the transaction is broadcasted.
6. The blockchain-based data asset transaction method of claim 5, wherein: in the data packing step, when a provider locally generates a shipment order, the provider firstly accepts an application decryption transaction and finds out a data description needing transaction, then analyzes txData applying the decryption transaction to take out a cipher text Ks of a temporary key, symmetrically decrypts the cipher text Ks of the temporary key by using a private key of the provider to obtain a key k, then uses a public key of a purchaser to asymmetrically encrypt the key k to obtain the cipher text Ks2, then creates a decryption shipment transaction, stores a request form transaction hash, a transaction hash of reported data and a cipher key cipher text Ks2 in the txData decrypting the shipment transaction, and broadcasts the transaction.
7. The blockchain-based data asset transaction method of claim 6, wherein: in the data packaging step, after the actual data corresponding to the application decryption transaction is obtained, encrypting the actual data specifically includes: after the platform synchronizes with the decrypted shipment transaction through the block chain node, whether the platform is a response of applying for the decrypted transaction sent by the platform is judged, if so, a plaintext key k of Ks2 is decrypted through a private key, actual data in the shipment transaction is decrypted through the plaintext key k to obtain a plaintext of the actual data, and then the actual data is encrypted.
8. The blockchain-based data asset transaction method of claim 1, wherein: the method also comprises a recording step and a recommending step; recording, namely recording a data abstract viewing record and a purchase application record of a purchaser by a platform; and a recommendation step, wherein the platform checks the record and the purchase application record according to the abstract of the buyer, and performs data recommendation for the buyer after performing behavior analysis on the buyer.
9. The blockchain-based data asset transaction method of claim 8, wherein: the abstract checking record comprises checking time, duration of checking the abstract and identification information of the abstract; the purchase requisition record includes a purchase time, a data type, and a data amount for requisition for purchase.
10. The blockchain-based data asset transaction method of claim 9, wherein: in the recommendation step, within a preset duration, if the abstracts are viewed and recorded in the abstracts within a preset quantity range and browsed back and forth, the platform carries out feature analysis on the identification information of the browsed abstracts and searches whether a data abstract containing a plurality of characteristics of the browsed abstracts exists, and if the data abstract exists, the corresponding data abstract is pushed to a purchaser;
within a preset time length, if the number of the browsed data summaries is greater than X and the browsing time lengths of the continuous Y data summaries are all smaller than a first preset time length, whether a purchase application record exists within a second preset time length or not is analyzed; if the purchase application record exists, the platform combines the purchase record and pushes a data abstract corresponding to the data which can be used in combination with the purchased data to the purchaser; if the purchase record does not exist, the platform analyzes the browsing path according to the sequence of the browsed data summaries, the browsing path analysis comprises the field, the area and the data generation time of the data summaries, browsing prediction is carried out according to the browsing path analysis, and the predicted data summaries are pushed to a purchaser; and the second preset time length is greater than the first preset time length.
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