CN113793199A - Bid inviting information recommendation method, system and storage medium - Google Patents
Bid inviting information recommendation method, system and storage medium Download PDFInfo
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Abstract
The invention relates to an information matching recommendation method, in particular to a bid inviting information recommendation method. Recommending a plurality of bidding text information according to the bidding text information, wherein the method comprises the following steps: extracting characteristic values in the bid-winning text information; traversing the bidding text information file library, and according to the nth characteristic value in the characteristic values, giving an nth preset value to the bidding text information with the same nth characteristic value in the file library, and giving the same default preset value to other bidding text information, wherein n is not less than 2; respectively adding preset values given to the bidding text information in the bidding text information file library to form added values; and taking the top M bits of the sum value of each bidding text information in the order from large to small to form a topM recommendation result, wherein M is not less than 1. Aiming at the specific text structure of bid inviting information, the quality of a recommendation result is optimized; improvement is made for the subpackage situation; the convenience of people in economic and technical activities is improved.
Description
Technical Field
The invention relates to an information matching recommendation method, in particular to a bid inviting information recommendation method, a bid inviting information recommendation system and a storage medium.
Background
The promotion of bid-winning information has great economic benefits, for example, bid-winning information databases are collected by similar websites or small program modes such as bid-winning bars, so that people can conveniently search and read, and the beneficial information of economic and technical activities is provided. However, these methods are all passive information searching methods, which hamper the ability of people to obtain relevant bid-winning information. Text similarity techniques can certainly search for similar information, but require a lot of programmer labor and are costly in this regard. Text feature extraction technology, such as Chinese vocabulary can be extracted by the Chinese character segmentation technology or the newer python technology, and the Chinese vocabulary can be used for semantic analysis and the like; however, these have no application to the utilization of the actual bidding information. Based on the existing bid-winning information, a reasonable quantification mode is adopted for recommending the information, and wide improvement space is provided.
The bidding documents in the full database are associated with each bidding information in the full database of winning bids. When a user browses a bid inviting bidding signal, the user can be considered as having bid bidding requirements, and the user recommends the corresponding bid inviting bidding signal, so that the user can save the time for bidding signal screening and clearly inform the user that the bid inviting bidding signal is completed; or the answer of the beacon is displayed for the user, and the replying announcement helps the user to track the beacon state. The bid-winning information is a specific text type, and in the existing documents such as CN108874771A and CN104915334A, colleges and universities or enterprise organizations have a few ideas and ideas, but cannot achieve the expected bid-winning information recommendation result.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a bid inviting information recommendation method, a system and a storage medium, which try to improve the prior art, such as improving the relevance of recommendation effect, adaptively improving the specificity of bid inviting information and optimizing the technical logic embodied by an algorithm.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, the present invention provides a bid-winning information recommendation method, which recommends a plurality of bid-winning text information according to bid-winning text information, and the method includes:
extracting characteristic values in the bid-winning text information;
traversing a bidding text information file library, and according to the 1 st characteristic value in the characteristic values, giving a 1 st preset value to the bidding text information with the same 1 st characteristic value in the file library, and giving the same default preset value to other bidding text information;
traversing the bidding text information file library, and according to the 2 nd characteristic value in the characteristic values, giving a 2 nd preset value to the bidding text information with the same 2 nd characteristic value in the file library, and giving the same default preset value to other bidding text information;
traversing the bidding text information file library, and according to the nth characteristic value in the characteristic values, giving an nth preset value to the bidding text information with the same nth characteristic value in the file library, and giving the same default preset value to other bidding text information, wherein n is not less than 2;
respectively adding preset values given to the bidding text information in the bidding text information file library to form added values;
and taking the top M bits of the sum value of each bidding text information in the order from large to small to form a topM recommendation result, wherein M is not less than 1.
Preferably, the 1 st preset value is not less than the 2 nd preset value, the 2 nd preset value is not less than the 3 rd preset value, and both are greater than 0, and so on; the importance degree of the 1 st characteristic value is not weaker than that of the 2 nd characteristic value, the importance degree of the 2 nd characteristic value is not weaker than that of the 3 rd characteristic value, and the like; the same default preset value is 0.
Preferably, the 1 st characteristic value is a business name, a telephone number or a purchaser name, and the 2 nd characteristic value is a name or an address; the difference between the 1 st preset value and the 2 nd preset value is larger than 2, so that the importance degree of the matched 1 st characteristic value is not weaker than that of the 2 nd characteristic value.
Preferably, the recommendation result is displayed on a sidebar of a webpage, a page of the mobile terminal or an outdoor multimedia screen.
Preferably, after extracting the feature value in the winning bid text information, the method further includes: judging whether the bid-winning text information is one of y bid-winning text information of a single label corresponding to x label segments, wherein y is not more than x, namely 1 bid-winning text information can comprise not less than 1 label segment; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value.
Besides, a plurality of bid-winning text information can be recommended according to the bid-winning text information, characteristic values are correspondingly extracted from the bid-winning text information, a bid-winning text information file library is traversed, preset values are given to the bid-winning text information, and a recommendation result of the bid-winning text information is formed.
In a second aspect, the present invention provides a bid inviting information recommendation system for executing a bid inviting information recommendation method for recommending a plurality of bid inviting text information according to bid inviting text information, the system having a storage medium, the system comprising:
the characteristic value extraction unit is used for extracting the characteristic values of the bid winning text information, and the types and the number of the characteristic values are a plurality;
the information traversing unit is used for traversing the bidding text information file library, sequentially endowing the bidding text information with the same nth characteristic value in the file library with an nth preset value according to the nth characteristic value in the characteristic values, and endowing other bidding text information with the same default preset value, wherein n is not less than 2;
the statistical sorting unit is used for respectively adding the preset values given to the bidding text information in the bidding text information file library to form added values and sorting all the added values from large to small;
and the recommendation result forming unit is used for taking the first M bits of the summation value of each bidding text information to form a topM recommendation result, wherein M is not less than 1.
Preferably, the system further comprises a sub-packet determining unit, configured to determine whether the bid-winning text information is one of y bid-winning text information of a single beacon corresponding to x bid-winning text information, where y is not greater than x, that is, 1 bid-winning text information may include not less than 1 bid-winning text information; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value.
In a third aspect, the present invention provides a computer storage medium provided in a mobile terminal such as a mobile phone, a desktop computer, or an outdoor multimedia facility, and having a program or a loadable program to execute a bid inviting information recommendation method.
Compared with the prior art, the invention has the advantages that the invention is not limited to the following: aiming at the specific text structure of bid inviting information, the quality of a recommendation result is optimized; improvement is made for the subpackage situation; the convenience of people in economic and technical activities is improved.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of a bid winning information recommendation method of the present invention;
fig. 2 is a schematic diagram of a bid winning information recommendation system of the present invention.
Detailed Description
Example 1
As shown in the flowchart of fig. 1, the bid-winning information recommendation method recommends a plurality of bid-winning text information according to the bid-winning text information, and includes the following steps:
S1extracting characteristic values in the bid-winning text information;
S2traversing the bidding text information file library, endowing 1 st preset value to the bidding text information with the same 1 st characteristic value in the file library according to the 1 st characteristic value in the characteristic values, and endowing other bidding text information with the 1 st preset valueGiving the same default value;
S3traversing the bidding text information file library, and according to the 2 nd characteristic value in the characteristic values, giving a 2 nd preset value to the bidding text information with the same 2 nd characteristic value in the file library, and giving the same default preset value to other bidding text information;
Sntraversing the bidding text information file library, and according to the nth characteristic value in the characteristic values, giving an nth preset value to the bidding text information with the same nth characteristic value in the file library, and giving the same default preset value to other bidding text information, wherein n is not less than 2;
Sn+1respectively adding preset values given to the bidding text information in the bidding text information file library to form added values;
Sn+2and taking the top M bits of the sum value of each bidding text information in the order from large to small to form a topM recommendation result, wherein M is not less than 1.
The 1 st preset value is 5, the 2 nd preset value is 3, and the 3 rd preset value is 1; it can be seen that the 1 st preset value is not less than the 2 nd preset value, the 2 nd preset value is not less than the 3 rd preset value, and both are greater than 0, and so on; the importance degree of the 1 st characteristic value is not weaker than that of the 2 nd characteristic value, the importance degree of the 2 nd characteristic value is not weaker than that of the 3 rd characteristic value, and the like; the same default preset value is 0.
The 1 st characteristic value is a business name, a telephone number or a buyer name, and the 2 nd characteristic value is a name or an address; the difference between the 1 st preset value and the 2 nd preset value is larger than 2, so that the importance degree of the matched 1 st characteristic value is not weaker than that of the 2 nd characteristic value.
The named entities such as the business name, the telephone number or the name of a buyer are the most important characteristics, and when the bidding text information and a certain bidding text information have the same named entity, a preset value 5 is given;
and displaying the recommendation result on a side bar of a webpage, a page of the mobile terminal or an outdoor multimedia screen. Of course other including applet forms are encapsulated within the mobile terminal page.
For the situation of sub-package bidding, after extracting the characteristic value in the winning bid text information, the method further comprises the following steps: judging whether the bid-winning text information is one of y bid-winning text information of a single label corresponding to x label segments, wherein y is not more than x, namely 1 bid-winning text information can comprise not less than 1 label segment; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value. Here, the 0 th preset value can also be 3.
Because the actual difference of the bid-winning text information is not large, a plurality of bid-winning text information can be recommended according to the bid-winning text information, and in addition, a plurality of bid-winning text information can be recommended according to the bid-winning text information, characteristic values are correspondingly extracted from the bid-winning text information, the bid-winning text information file library is traversed, preset values are given to the bid-winning text information, and a recommendation result of the bid-winning text information is formed.
Example 2
A bid-winning information recommendation system for executing a bid-winning information recommendation method as shown in a block diagram of fig. 2 recommends a plurality of bid-winning text information according to the bid-winning text information, the system having a storage medium, the system comprising:
the characteristic value extraction unit A is used for extracting the characteristic values of the bid-winning text information, and the types and the number of the characteristic values are a plurality;
the information traversing unit B is used for traversing the bidding text information file library, sequentially endowing the bidding text information with the same nth characteristic value in the file library with an nth preset value according to the nth characteristic value in the characteristic values, and endowing other bidding text information with the same default preset value, wherein n is not less than 2;
the statistical sorting unit C is used for respectively adding the preset values given to the bidding text information in the bidding text information file library to form added values and sorting all the added values from large to small;
and a recommendation result forming unit D for taking the first M bits of the summation value of each bidding text information to form a topM recommendation result, wherein M is not less than 1.
These elements are related in the data information flow, forming a closed loop operation of the overall system.
For the situation of sub-package bidding, the system further comprises a sub-package judgment unit J in technical logic, which is used for judging whether the bid-winning text information is one of y bid-winning text information of a single beacon corresponding to x bid-winning sections, wherein y is not greater than x, that is, 1 bid-winning text information can include not less than 1 bid-winning text information; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value.
Example 3
A computer storage medium is provided in a mobile terminal such as a mobile phone, a desktop computer, or an outdoor multimedia facility, and has a program or a loadable program to execute a bid bidding information recommendation method. A computer storage medium having a fixed program may be applied to a bidding institution specialized in bidding, but for more general users, in the form of applets such as WeChat or APP, etc., which may be developed by the institution, a program may be temporarily loaded to perform the bid winning information recommendation method.
The flowchart and block diagrams in the figures illustrate the architecture, acts, and operations of possible implementations of embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of a program of instructions. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures.
The above examples are only for illustrating the technical solutions of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A bid-winning information recommending method is characterized in that a plurality of bid-winning text information are recommended according to bid-winning text information, and the method comprises the following steps:
extracting characteristic values in the bid-winning text information;
traversing a bidding text information file library, and according to the 1 st characteristic value in the characteristic values, giving a 1 st preset value to the bidding text information with the same 1 st characteristic value in the file library, and giving the same default preset value to other bidding text information;
traversing the bidding text information file library, and according to the 2 nd characteristic value in the characteristic values, giving a 2 nd preset value to the bidding text information with the same 2 nd characteristic value in the file library, and giving the same default preset value to other bidding text information;
traversing the bidding text information file library, and according to the nth characteristic value in the characteristic values, giving an nth preset value to the bidding text information with the same nth characteristic value in the file library, and giving the same default preset value to other bidding text information, wherein n is not less than 2;
respectively adding preset values given to the bidding text information in the bidding text information file library to form added values;
and taking the top M bits of the sum value of each bidding text information in the order from large to small to form a topM recommendation result, wherein M is not less than 1.
2. The bid inviting and bid winning information recommending method of claim 1, wherein the 1 st preset value is not less than the 2 nd preset value, the 2 nd preset value is not less than the 3 rd preset value, and both are greater than 0, and so on; the importance degree of the 1 st characteristic value is not weaker than that of the 2 nd characteristic value, the importance degree of the 2 nd characteristic value is not weaker than that of the 3 rd characteristic value, and the like; the same default preset value is 0.
3. The bid-winning information recommendation method of claim 2, wherein the 1 st feature value is a business name, a telephone number or a purchaser name, and the 2 nd feature value is a name or an address; the difference between the 1 st preset value and the 2 nd preset value is larger than 2, so that the importance degree of the matched 1 st characteristic value is not weaker than that of the 2 nd characteristic value.
4. The bid-winning information recommendation method of claim 1, wherein the recommendation result is displayed on a sidebar of a web page, a page of a mobile terminal or an outdoor multimedia screen.
5. The bid-winning information recommendation method according to claim 2, further comprising, after extracting the feature values in the bid-winning text information: judging whether the bid-winning text information is one of y bid-winning text information of a single label corresponding to x label segments, wherein y is not more than x, namely 1 bid-winning text information can comprise not less than 1 label segment; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value.
6. The bid-winning information recommendation method of claim 1, wherein "recommend several bid-winning text information according to the bid-winning text information" is replaced with "recommend several bid-winning text information according to the bid-winning text information", characteristic values are extracted from the bid-winning text information accordingly, a bid-winning text information file library is traversed, and preset values are given to the bid-winning text information, so as to form a recommendation result of the bid-winning text information.
7. A bid-winning information recommending system for executing a bid-winning information recommending method according to claim 1, recommending bid-winning text information based on the bid-winning text information, having a storage medium, the system comprising:
the characteristic value extraction unit is used for extracting the characteristic values of the bid winning text information, and the types and the number of the characteristic values are a plurality;
the information traversing unit is used for traversing the bidding text information file library, sequentially endowing the bidding text information with the same nth characteristic value in the file library with an nth preset value according to the nth characteristic value in the characteristic values, and endowing other bidding text information with the same default preset value, wherein n is not less than 2;
the statistical sorting unit is used for respectively adding the preset values given to the bidding text information in the bidding text information file library to form added values and sorting all the added values from large to small;
and the recommendation result forming unit is used for taking the first M bits of the summation value of each bidding text information to form a topM recommendation result, wherein M is not less than 1.
8. The bid-winning information recommendation system according to claim 7, further comprising a sub-package judgment unit for judging whether the bid-winning text information is one of y bid-winning text information of a single beacon corresponding to x bid-winning sections, wherein y is not greater than x, that is, 1 bid-winning text information may include not less than 1 bid-winning section; if so, when traversing the bidding text information file library, giving a 0 th preset value to other bidding text information with the same bidding information in the bidding text information file library, wherein the 0 th preset value is not less than a 2 nd preset value.
9. A computer storage medium provided in a mobile terminal such as a mobile phone, a desktop computer, or an outdoor multimedia facility, and having a program or a loadable program to execute the bid inviting information recommendation method of one of the preceding claims 1 to 6.
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Cited By (1)
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Application publication date: 20211214 |