CN116450931B - Hot-search word throwing method, hot-search word throwing device and computer storage medium - Google Patents
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The application discloses a hot search word throwing method, a hot search word throwing device and a computer storage medium, wherein the hot search word throwing method comprises the following steps: acquiring a search record of a user, wherein the search record comprises a history number; obtaining a high-grade number of a number pool; acquiring a first keyword list based on the history number and the high-level number; setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list; setting a search matching degree index for a plurality of keywords in a first keyword list based on a search record of a user; calculating the weights of a plurality of keywords according to the importance index and the search matching degree index; generating a second keyword list according to the weights of the keywords from large to small, and putting the keywords in the second keyword list as hot search words. According to the method and the device, an ordered rule is established through unordered search behaviors of the user, and a series of indexes are extracted to be used for automatically screening proper hot search words and recommending the hot search words to the user.
Description
Technical Field
The present disclosure relates to the field of number delivery technologies, and in particular, to a hot search word delivery method, a hot search word delivery device, and a computer storage medium.
Background
In the business of the carrier industry number card, advertisement delivery is an important revenue source mode. In order to reduce the delivery cost, get the customer cost and improve the user conversion rate, advertisement delivery pages (hereinafter referred to as delivery pages) usually show some popular search keywords. However, since the searching behavior of the user has timeliness and uncertainty, the hot search word and the mobile phone number display of the put page need to be continuously adjusted to ensure the maximized advertising benefit.
The traditional hot search word display mode is usually static, namely a group of hot search keywords are preset in advance and displayed on a put page. This approach suffers from significant drawbacks, such as:
1. the timeliness of the search behavior of the user cannot be guaranteed, so that the displayed hot search word deviates from the actual requirement of the user.
2. The hot search word cannot be updated in time, which may result in the displayed hot search word being outdated or no longer welcome by the user.
Therefore, an algorithm capable of analyzing the search behavior of the user in real time, dynamically adjusting the hot-search word presentation of the put page, and presenting the numbers conforming to the hot-search word preferentially is needed to solve the problems.
Disclosure of Invention
The application provides a hot search word throwing method, a hot search word throwing device and a computer storage medium.
The technical scheme adopted by the application is to provide a hot search word throwing method based on a mobile phone number, wherein the hot search word throwing method comprises the following steps:
obtaining a search record of a user, wherein the search record comprises a history number;
obtaining a high-grade number of a number pool;
acquiring a first keyword list based on the history number and the high-level number;
setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list;
setting a search matching degree index for a plurality of keywords in the first keyword list based on the search record of the user;
calculating the weights of the keywords according to the importance index and the search matching degree index;
generating a second keyword list according to the weights of the keywords from large to small, and putting the keywords in the second keyword list as hot search words.
Wherein the obtaining a first keyword list based on the history number and the high-level number includes:
extracting high-level keywords in the high-level numbers, and calculating the duty ratio of the high-level keywords;
sorting the high-level keywords from high to low according to the duty ratio to obtain a third keyword list;
and extracting the history keywords in the history numbers, putting the history keywords into the third keyword list, and generating the first keyword list.
Wherein the importance index of the history keyword in the first keyword list is set to the highest importance.
The setting a search matching degree index for a plurality of keywords in the first keyword list based on the search record of the user comprises the following steps:
extracting a search keyword based on the search record of the user;
matching the search keyword with a plurality of keywords in the first keyword list;
setting the search matching degree index of the keywords directly matched as the highest search matching degree;
and calculating the similarity between the keywords which cannot be directly matched and the search keywords, and setting search matching degree indexes of the keywords according to the similarity.
The calculating the weights of the keywords according to the importance index and the search matching degree index comprises the following steps:
counting the stock quantity of the keywords in the number pool;
sequencing the keywords from high to low according to the stock quantity corresponding to each keyword, and setting the stock indexes of the keywords according to the sequencing;
and calculating the weights of the keywords according to the importance index, the search matching degree index and the inventory index.
The calculating the weights of the keywords according to the importance index, the search matching degree index and the inventory index comprises the following steps:
and calculating the importance index, the search matching degree index and the inventory index by using an analytic hierarchy process or an order diagram process so as to obtain the weights of the keywords.
After the keyword in the second keyword list is put as the hot search word, the hot search word putting method further includes:
searching a hot search number from the number pool according to the launched hot search word, and launching the hot search number to a search interface of a user.
The application adopts another technical scheme that provides a hot search word throwing device, wherein the hot search word throwing device comprises a number module, a list module, an index module, a weight module and a throwing module; wherein,
the number module is used for acquiring a search record of a user, wherein the search record comprises a history number;
the number module is also used for acquiring high-grade numbers of the number pool;
the list module is used for acquiring a first keyword list based on the history number and the high-level number;
the index module is used for setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list;
the index module is further used for setting search matching degree indexes for a plurality of keywords in the first keyword list based on the search records of the user;
the weight module is used for calculating the weights of the keywords according to the importance index and the search matching degree index;
and the putting module is used for generating a second keyword list from large to small according to the weights of the keywords, and putting the keywords in the second keyword list as hot search words.
Another technical scheme adopted by the application is to provide a hot search word throwing device, wherein the hot search word throwing device comprises a memory and a processor coupled with the memory;
the memory is used for storing program data, and the processor is used for executing the program data to realize the hot word searching and putting method.
Another technical solution adopted in the present application is to provide a computer storage medium, where the computer storage medium is used to store program data, where the program data is used to implement the hot search word placement method as described above when the program data is executed by a computer.
The beneficial effects of this application are: the method comprises the steps that a hot search word throwing device obtains search records of a user, wherein the search records comprise history numbers; obtaining a high-grade number of a number pool; acquiring a first keyword list based on the history number and the high-level number; setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list; setting a search matching degree index for a plurality of keywords in a first keyword list based on a search record of a user; calculating the weights of a plurality of keywords according to the importance index and the search matching degree index; generating a second keyword list according to the weights of the keywords from large to small, and putting the keywords in the second keyword list as hot search words. According to the hot search word throwing device, the real-time search behavior of the user is combined with the number information, an ordered rule is established from the unordered search behavior of the user, a series of indexes are extracted, meanwhile, the information contained in the number is deeply mined, multidimensional information is extracted for silk-stripping, indexes are quantized, and a hot search word dynamic list based on the search behavior of the user is extracted. The problems of unhealthy hot search words, invalid hot search words and the like caused by untimely updating are solved, the focus of attention of a current user can be more met, the user is attracted, and the user conversion rate is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an embodiment of a hot word placement method provided in the present application;
FIG. 2 is a schematic diagram of an overall interaction flow of the hot word placement method provided by the application;
FIG. 3 is a schematic diagram of a specific flow of step S16 of the hot word placement method shown in FIG. 1;
FIG. 4 is a schematic diagram of the results of keywords provided in the present application after being ranked according to weights;
FIG. 5 is a schematic structural diagram of an embodiment of a hot word placement device provided in the present application;
FIG. 6 is a schematic structural diagram of another embodiment of a hot word placement device provided in the present application;
fig. 7 is a schematic structural diagram of an embodiment of a computer storage medium provided in the present application.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The application provides a solution for dynamically displaying hot search words and mobile phone numbers of a released page in real time based on user search behaviors. The scheme comprises the following steps:
1. and analyzing keywords searched by the user on the put page in a period of time in real time, and generating a hot search word list according to the search keywords of the user.
2. According to the hot search word list, the hot search word display of the put page is dynamically adjusted, the displayed hot search word is ensured to be consistent with the actual requirement of a user, and the change of the search behavior of the user can be reflected in time.
3. And according to the weight of the hot search word, preferentially displaying the number conforming to the hot search word on the release page.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic flow diagram of an embodiment of a hot word placement method provided in the present application, and fig. 2 is a schematic flow diagram of overall interaction of the hot word placement method provided in the present application.
As shown in FIG. 2, the hot word searching and throwing device specifically comprises a data acquisition module, a hot word searching module and a number pool module.
The data acquisition module is used for acquiring search behaviors of a user on a put page and transmitting the cleaned data to the hot word searching module. The hot search word module analyzes keywords searched by a user, filters, screens, merges, calculates weight after summarization and generates a hot search word list. And displaying the hot search word list on the release page in real time when the user accesses the release page. And the number pool module dynamically adjusts a number query rule according to the weight of the hot search word and the duty ratio of the search quantity, and preferentially displays the numbers which accord with the hot search word and have high grades on the put page.
As shown in fig. 1, the hot word placement method in the embodiment of the present application may specifically include the following steps:
step S11: and obtaining a search record of the user, wherein the search record comprises the history number.
In the embodiment of the application, a hot word searching module in the hot word searching and throwing device acquires a searching record of a user and manages keywords and historical numbers input by the user. The hot search word module counts a plurality of historical keywords with top search quantity of the user.
Step S12: and obtaining the high-grade number of the number pool.
In the embodiment of the application, the number pool module in the hot search word throwing device needs to analyze the numbers one by one through a preset rule, then grade scoring is carried out on the numbers, and keywords in the numbers are extracted. For example: AAAAAA, and a is 6/8, then number rating is 1; aaa+, a is 8, the number class is 13. The smaller the ranking score, the higher the ranking representing the cell phone number.
Step S13: a first keyword list is obtained based on the history number and the high-ranking number.
In the embodiment of the application, a hot search word module in the hot search word throwing device extracts high-level keywords in high-level numbers, and then, the top_n keyword list, namely a third keyword list, is extracted by counting the duty ratio of the high-level number keywords.
The hot word searching module in the hot word searching and throwing device also needs to process the history keywords input by the user. Specifically, historical keywords with TOP search quantity ranking are counted, if the historical keywords are not in the TOP_N keyword list of the number pool, the keywords searched by the user are required to be placed in the TOP_N keyword list, and a final first keyword list is formed.
Step S14: and setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list.
In this embodiment of the present application, the hot search word delivering device sorts the high-level keywords in the top_n keyword list according to the duty ratio from high to low, and assigns importance to the keywords from high to low, for example: the importance is at most 10, and the importance is at least 1. The importance index of the keyword needs to be used in the calculation of the weight of the hot search word.
Further, the hot search word placement device sets the importance index of the history keyword in the first keyword list to the highest importance, namely 10.
Step S15: and setting a search matching degree index for a plurality of keywords in the first keyword list based on the search record of the user.
In the embodiment of the application, the keyword putting device needs to go to the first keyword list for matching every time the user searches keywords, and the matching degree of the search keywords in the list is set. If the search is hit directly, the index of the search matching degree of the corresponding keyword is marked as 10; and the keywords which are not directly hit are assigned according to the similarity, the search matching degree index of the very similar keywords is marked as 9, and the search matching degree index of the keywords with the lowest similarity is marked as 1. Finally, the hot search word throwing device averages the search matching degree indexes calculated by all search records of the user, and then the search matching degree index of each keyword in the first keyword list can be obtained.
Step S16: and calculating the weights of the keywords according to the importance index and the search matching degree index.
In the embodiment of the application, the hot search word throwing device calculates the weight of each keyword in the first keyword list finally according to the importance index and the search matching degree index of the first keyword and combining an AHP (advanced high-performance analysis) hierarchical method and a priority diagram method, and sorts each keyword in the first keyword list again according to the weights to finally generate the hot search word list.
And inquiring the mobile phone numbers displayed by default on the release page of the operator according to the weight of the hot search word, and preferentially displaying the mobile phone numbers with high number grade and high hot search word weight.
Further, the hot search word throwing device can further abstract stock indexes of medium-number keywords, because: in addition to the importance index and the search matching index, a factor of number stock needs to be considered, because if the search keyword cannot search the result, the set hot search word is meaningless.
With continued reference to fig. 3, fig. 3 is a schematic flowchart of step S16 of the hot word placement method shown in fig. 1.
As shown in fig. 3, the hot word placement method in the embodiment of the present application may specifically include the following steps:
step S161: and counting the stock quantity of a plurality of keywords in the number pool.
Step S162: and sequencing the keywords according to the stock quantity corresponding to each keyword from high to low, and setting stock indexes of the keywords according to sequencing.
In the embodiment of the application, the hot search word throwing device performs fuzzy matching on keywords in the first keyword list with numbers in the number pool one by one, respectively calculates the stock quantity corresponding to each keyword, sorts the stock quantity from high to low, and sets the stock quantity to be 10 at most and 0 at the lowest, thereby obtaining the stock index of the first keyword list.
For example, one number in the number pool is 17666039988. Fuzzy search by key 666 is possible. Fuzzy searches by keyword 88 are also possible. At this point 666 keywords and 88 keywords are both calculated for inventory.
Step S163: and calculating the weights of the keywords according to the importance index, the search matching degree index and the inventory index.
In this embodiment, the number key and the values corresponding to the three indexes are shown in the following table 1:
table 1 number key and value corresponding to three indices
Keywords 66, 233, 88, 123, 668, 876, 333, 886, 8877, 999 in the above table are TOP_10 extracted from high-ranking numbers, keywords 520, 1314 are counted according to the user search amount, and since they are during the episode, the searched keywords will also have holiday characteristics.
After merging, the keyword list contains 12 keywords. And respectively calculating an importance index, a search matching degree index and an inventory index according to rules formulated by the system.
The weight of each keyword in the keyword list is calculated by using the AHP hierarchy method as an example:
in the calculation of weights by AHP analysis, a judgment matrix is first constructed as shown in tables 2 and 3 below.
First: the construction mode of the judgment matrix is as follows: and calculating the average value of each analysis item, and dividing the average value by the average value to obtain a judgment matrix.
Second,: a larger average value means a higher importance and a higher weight.
Third,: AHP analysis is generally applicable to scoring the importance of an index by an expert.
Table 2AHP analytic hierarchy process judgment matrix
TABLE 3AHP analytic hierarchy process results
AHP analytic hierarchy process was used for research expert scoring weight calculation:
first: AHP hierarchies are used to calculate weights and require consistency checks.
Second,: and describing the weight conditions obtained by each index one by one.
Third,: AHP analytic hierarchy process studies were performed using the sum-product calculation method.
As can be seen from table 3, the AHP hierarchical study was performed for a total of 12 construction order judgment matrices 66, 233, 88, 123, 668, 876, 333, 886, 8877, 999, 520, 1314, with the following calculation methods: and the product method, the analysis results in a feature vector (1.813,1.250,1.688,1.188,1.188,0.562,0.688,0.688,0.438,0.500,1.250,0.750), and the weight values corresponding to the total 12 items are respectively: 15.104%,10.417%,14.062%,9.896%,9.896%,4.688%,5.729%,5.729%,3.646%,4.167%,10.417%,6.250%.
In addition, a maximum feature root (12.000) can be calculated in combination with the feature vector, and then a CI value (0.000) [ ci= (maximum feature root-n)/(n-1) ] is calculated using the maximum feature root value, and the CI value is used for the consistency check described below.
When the AHP analytic hierarchy process is used for weight calculation, consistency check analysis is needed;
first: the consistency check requires the use of two index values to CI and RI;
second,: CI values have been calculated and RI values can be found by querying Table 4 below.
Table 4 random consensus RI table
The embodiment of the application constructs a 12-order judgment matrix, and the random consistency RI value of 1.540 can be obtained by inquiring the corresponding table, and the RI value is used for the consistency check calculation.
| Maximum feature root | CI value | RI value | CR value | Consistency test results |
| 12.000 | 0.000 | 1.540 | 0.000 | By passing through |
TABLE 5 summary of consistency check results
When weight calculation is performed by using the AHP hierarchical analysis method, a consistency check analysis is required for researching a consistency check result of evaluating the weight calculation result, that is, calculating a consistency index CR value (cr=ci/RI).
First: the CI value [ ci= (maximum feature root-n)/(n-1) ] calculated above is described first.
Second,: and combining the judgment matrix order to obtain the RI value.
Third,: the CR value is calculated and a consistency determination is made.
The smaller the CR value is under the normal condition, the better the consistency of the judgment matrix is, and the smaller the CR value is under the normal condition, the judgment matrix meets the consistency test; if the CR value is greater than 0.1, it indicates that there is no consistency, and analysis should be performed again after appropriate adjustment of the judgment matrix. The CI value is calculated to be 0.000 for the 12-order judgment matrix, and the RI value is calculated to be 1.540, so that the CR value is calculated to be 0.000<0.1, which means that the judgment matrix in the research meets consistency test, and the calculated weights have consistency.
In other embodiments, the weights of the keywords in the keyword list may be calculated by using a priority diagram method, which is not described herein.
Step S17: generating a second keyword list according to the weights of the keywords from large to small, and putting the keywords in the second keyword list as hot search words.
In this embodiment of the present application, after the calculation in step S16, the keyword is ranked according to the weight, as shown in fig. 4. The put page generally displays 5 keywords as hot search words, so the keyword weight value TOP_5 is taken, and the final hot search word list is as follows: 66, 88, 233, 520, 123.
Further, the hot search word throwing device can search the hot search number from the number pool according to the thrown hot search word, and throw the hot search number to a search interface of a user for the user to directly select.
In the embodiment of the application, a hot search word throwing device acquires a search record of a user, wherein the search record comprises a history number; obtaining a high-grade number of a number pool; acquiring a first keyword list based on the history number and the high-level number; setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list; setting a search matching degree index for a plurality of keywords in a first keyword list based on a search record of a user; calculating the weights of a plurality of keywords according to the importance index and the search matching degree index; generating a second keyword list according to the weights of the keywords from large to small, and putting the keywords in the second keyword list as hot search words.
The method combines the real-time searching behavior of the user with the number information, establishes an ordered rule from the unordered searching behavior of the user, extracts a series of indexes, simultaneously deeply mines the information contained in the number, and silk-strips and cocoon-peels multidimensional information to quantify the indexes; based on the data, continuously adjusting accumulation, combining with algorithms such as an AHP hierarchical method, a priority diagram method and the like, and refining a hot search word dynamic list based on user search behaviors; the problems of unhealthy hot search words, invalid hot search words and the like caused by untimely updating are solved; and meanwhile, the number displayed by the page is displayed by default according to the hot search word, so that the method can be more in line with the focus of attention of the current user, thereby attracting the user and improving the conversion rate of the user.
The above embodiments are only one common case of the present application, and do not limit the technical scope of the present application, so any minor modifications, equivalent changes or modifications made to the above matters according to the scheme of the present application still fall within the scope of the technical scheme of the present application.
With continued reference to fig. 5, fig. 5 is a schematic structural diagram of an embodiment of a hot word placement device provided in the present application. The hot search word throwing device 30 includes a number module 31, a list module 32, an index module 33, a weight module 34, and a throwing module 35.
The number module 31 is configured to obtain a search record of a user, where the search record includes a history number.
The number module 31 is further configured to obtain a high-level number of the number pool.
The list module 32 is configured to obtain a first keyword list based on the history number and the high-level number.
The index module 33 is configured to set an importance index for a plurality of keywords in the first keyword list according to the order of the first keyword list.
The index module 33 is further configured to set a search matching index for a number of keywords in the first keyword list based on the search record of the user.
The weight module 34 is configured to calculate weights of the keywords according to the importance index and the search matching index.
And the putting module is used for generating a second keyword list from large to small according to the weights of the keywords, and putting the keywords in the second keyword list as hot search words.
With continued reference to fig. 6, fig. 6 is a schematic structural diagram of another embodiment of the hot word placement device provided in the present application. The hot word placement device 500 in the embodiment of the present application includes a processor 51, a memory 52, an input/output device 53, and a bus 54.
The processor 51, the memory 52, and the input/output device 53 are respectively connected to the bus 54, where the memory 52 stores program data, and the processor 51 is configured to execute the program data to implement the hot word placement method according to any of the foregoing embodiments.
In the present embodiment, the processor 51 may also be referred to as a CPU (Central Processing Unit ). The processor 51 may be an integrated circuit chip with signal processing capabilities. Processor 51 may also be a general purpose processor, a digital signal processor (DSP, digital Signal Process), an application specific integrated circuit (ASIC, application Specific Integrated Circuit), a field programmable gate array (FPGA, field Programmable Gate Array) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The general purpose processor may be a microprocessor or the processor 51 may be any conventional processor or the like.
With continued reference to fig. 7, fig. 7 is a schematic structural diagram of an embodiment of the computer storage medium provided in the present application, in which program data 61 is stored in the computer storage medium 600, and the program data 61 is used to implement the hot word placement method according to any of the above embodiments when executed by a processor.
Embodiments of the present application are implemented in the form of software functional units and sold or used as a stand-alone product, which may be stored on a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution, in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely an embodiment of the present application, and the patent scope of the present application is not limited thereto, but the equivalent structures or equivalent flow changes made in the present application and the contents of the drawings are utilized, or directly or indirectly applied to other related technical fields, which are all included in the patent protection scope of the present application.
Claims (7)
1. The hot search word throwing method based on the mobile phone number is characterized by comprising the following steps of:
obtaining a search record of a user, wherein the search record comprises a history number;
obtaining a high-grade number of a number pool;
acquiring a first keyword list based on the history number and the high-level number;
setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list;
setting a search matching degree index for a plurality of keywords in the first keyword list based on the search record of the user;
calculating the weights of the keywords according to the importance index and the search matching degree index;
generating a second keyword list from large to small according to the weights of the keywords, and putting the keywords in the second keyword list as hot search words;
the step of obtaining a first keyword list based on the history number and the high-level number includes:
extracting high-level keywords in the high-level numbers, and calculating the duty ratio of the high-level keywords;
sorting the high-level keywords from high to low according to the duty ratio to obtain a third keyword list;
extracting a history keyword in the history number, and putting the history keyword into the third keyword list to generate the first keyword list;
the calculating the weights of the keywords according to the importance index and the search matching degree index comprises the following steps:
counting the stock quantity of the keywords in the number pool, wherein the stock quantity is the occurrence frequency of the keywords in the number pool;
sequencing the keywords from high to low according to the stock quantity corresponding to each keyword, and setting the stock indexes of the keywords according to the sequencing;
and calculating the importance index, the search matching degree index and the inventory index by using an analytic hierarchy process or an order diagram process so as to obtain the weights of the keywords.
2. The hot-search word placement method according to claim 1, characterized in that,
the importance index of the history keyword in the first keyword list is set to the highest importance.
3. The hot-search word placement method according to claim 1, characterized in that,
the setting a search matching degree index for a plurality of keywords in the first keyword list based on the search record of the user comprises the following steps:
extracting a search keyword based on the search record of the user;
matching the search keyword with a plurality of keywords in the first keyword list;
setting the search matching degree index of the keywords directly matched as the highest search matching degree;
and calculating the similarity between the keywords which cannot be directly matched and the search keywords, and setting search matching degree indexes of the keywords according to the similarity.
4. The hot-search word placement method according to claim 1, characterized in that,
after the keyword in the second keyword list is put as the hot search word, the hot search word putting method further includes:
searching a hot search number from the number pool according to the launched hot search word, and launching the hot search number to a search interface of a user.
5. The hot search word throwing device is characterized by comprising a number module, a list module, an index module, a weight module and a throwing module; wherein,
the number module is used for acquiring a search record of a user, wherein the search record comprises a history number;
the number module is also used for acquiring high-grade numbers of the number pool;
the list module is used for acquiring a first keyword list based on the history number and the high-level number;
the index module is used for setting importance indexes for a plurality of keywords in the first keyword list according to the sequence of the first keyword list;
the index module is further used for setting search matching degree indexes for a plurality of keywords in the first keyword list based on the search records of the user;
the weight module is used for calculating the weights of the keywords according to the importance index and the search matching degree index;
the putting module is used for generating a second keyword list from large to small according to the weights of the keywords, and putting the keywords in the second keyword list as hot search words;
the list module is also used for extracting high-level keywords in the high-level numbers and calculating the duty ratio of the high-level keywords; sorting the high-level keywords from high to low according to the duty ratio to obtain a third keyword list; extracting a history keyword in the history number, and putting the history keyword into the third keyword list to generate the first keyword list;
the weight module is further used for counting the stock quantity of the keywords in the number pool, wherein the stock quantity is the occurrence frequency of the keywords in the number pool; sequencing the keywords from high to low according to the stock quantity corresponding to each keyword, and setting the stock indexes of the keywords according to the sequencing; and calculating the importance index, the search matching degree index and the inventory index by using an analytic hierarchy process or an order diagram process so as to obtain the weights of the keywords.
6. The hot word searching and throwing device is characterized by comprising a memory and a processor coupled with the memory;
wherein the memory is configured to store program data, and the processor is configured to execute the program data to implement the hot word placement method according to any one of claims 1 to 4.
7. A computer storage medium for storing program data which, when executed by a computer, is adapted to carry out the hot word placement method according to any one of claims 1 to 4.
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