CN111209388A - Data processing method and device for keyword promotion page and computer equipment - Google Patents

Data processing method and device for keyword promotion page and computer equipment Download PDF

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Publication number
CN111209388A
CN111209388A CN201911359972.9A CN201911359972A CN111209388A CN 111209388 A CN111209388 A CN 111209388A CN 201911359972 A CN201911359972 A CN 201911359972A CN 111209388 A CN111209388 A CN 111209388A
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page
target
promotion
keyword
time
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CN111209388B (en
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陈旋
王冲
郝大松
李龙龙
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Jiangsu Aijia Household Products Co Ltd
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Jiangsu Aijia Household Products Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/34—Browsing; Visualisation therefor
    • G06F16/345—Summarisation for human users
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/957—Browsing optimisation, e.g. caching or content distillation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0277—Online advertisement

Abstract

The invention discloses a data processing method, a device, computer equipment and a storage medium for a keyword promotion page, wherein the data processing method comprises the steps of determining the grade of each keyword, extracting selected keywords, respectively calling a data generation interface of the keyword promotion page, assembling the promotion page of each selected keyword, storing summary information of each promotion page, sequencing the selected keywords, generating promotion market navigation, obtaining target keywords, entering the target promotion page, inquiring the target summary information, rendering page data of the target promotion page according to the last update time, the current time and the first set update time, and calculating the last update time distance according to the last update timeThe time difference between the current times, the page access density according to the target promotion page and the time difference
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And refreshing the target promotion page to improve the generation efficiency of the corresponding promotion page.

Description

Data processing method and device for keyword promotion page and computer equipment
Technical Field
The invention relates to the technical field of information processing, in particular to a data processing method and device for a keyword popularization page, computer equipment and a storage medium.
Background
With the development of the network era, various internet platforms emerge endlessly, and corresponding network popularization is more and more important, such as an ariibaba, a chinese manufacturing network, a smart network, and the like. The platform website has the advantages that the hundred-degree flow rate is important, and the drainage is one of the most important modes. In order to have better ranking in the hundred degree search, the search keywords play an important role in the richness and freshness of the searched resource content in the platform website. In order to better promote the website effect, keyword promotion is an important method, and in order to make the content of the result page searched by the keyword in the website richer and have higher value, each platform often selects to generate various promotion pages for the keyword in advance so as to improve the promotion effect.
At present, the generation of the keyword promotion page has the following pain points: firstly, page data is basically based on an in-site search engine, high-quality resources are extracted through various ranking algorithms and filtering processing, if page modules are more and business rules are various, the fact that searching processing needs to be adjusted for multiple times is meant, and therefore a performance problem exists, the more abundant the pages are, the larger the searching times which need to be called and the more resources consumed by later-stage data filtering processing are, and the general response time is more than 6 seconds; secondly, because the first pain point is a cache page or cache page data, if the first pain point is the cache page or cache page data, the second pain point exists, the number of search keywords is close to a million scale in the current large-scale platform website, if various promotion pages are provided for the first pain point and the second pain point, the total amount of final pages is millions or more, and the updating of page data becomes a huge burden. Therefore, the traditional keyword promotion page often has the problem of low generation efficiency.
Disclosure of Invention
In view of the above problems, the present invention provides a data processing method, a computer device, and a storage medium for a keyword promotion page.
In order to achieve the purpose of the invention, the invention provides a data processing method for a keyword promotion page, which comprises the following steps:
s10, determining scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling data generation interfaces of the keyword promotion pages aiming at all the selected keywords respectively, assembling the promotion pages of all the selected keywords, and storing summary information of all the promotion pages;
s20, sorting the selected keywords from high scores to low scores according to the scores of the selected keywords, and generating the promotion market navigation according to the sorting result;
s30, obtaining a target keyword clicked by a user in the promotion market navigation, entering a promotion page corresponding to the target keyword to obtain a target promotion page, inquiring target summary information of the target promotion page, and updating the last update time _ time, the current time system _ time and the first set update time N stored in the target summary information1Rendering page data of the target promotion page;
s40, according to the last update time of the target promotion page, calculating the time difference T between the last update time and the current timeDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2Refreshing the target promotion page; wherein N is2Indicating a second set update time.
In one embodiment, according to the last updating time of the target promotion page, the distance between the last updating time and the current time is calculatedTime difference TDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2After the target promotion page is refreshed, the method further includes:
acquiring page access density of each promotion page;
calculating the residual updating duration T of the target promotion pageS；
Calculating the updating urgency degree E of each promotion page according to the page access density of each promotion page and the updating remaining time of each promotion page;
and sequencing the updating urgency degree E from large to small, and refreshing each promotion page according to a sequencing result.
In one embodiment, the remaining duration T is updatedSThe calculation process of (2) includes:
TS＝TV-TD，
TVrepresenting page access density, TDRepresenting the time difference between the last update time and the current time.
In one embodiment, the calculation of the page access density includes:
TV＝n/P，
TVand P represents the visit amount of the promotion page in n days.
In one embodiment, the last update time update _ time, the current time system _ time and the first set update time N stored in the target summary information are used1Rendering the page data of the target promotion page includes:
if system _ time-update _ time>N1If so, putting the target keywords into an updating scheduling queue to wait for data updating, inquiring target page data according to a json data text address stored in the summary information of the target promotion page, returning to a front-end page, and rendering and displaying according to the target page data;
if system _ time-update _ time<N1Then, the target page is inquired according to the json data text address stored in the summary information of the target promotion pageAnd returning the surface data to the front-end page, and rendering and displaying according to the target page data.
In one embodiment, determining the score for each keyword in the keyword database comprises:
and acquiring the product number m and the company number n corresponding to each keyword in the keyword database, and calculating the score of each keyword by weighted average of the product number m and the company number n corresponding to each keyword.
As an embodiment, the determination process of the score of the keyword includes:
s＝m*β+(1-β)*n，
in the formula, s represents the score of the keyword, and β represents the first set weight.
A data processing apparatus for a keyword promotional page, comprising:
the determining module is used for determining scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling a data generating interface of a keyword promotion page aiming at all the selected keywords respectively, assembling the promotion pages of all the selected keywords, and storing summary information of all the promotion pages;
the sorting module is used for sorting the selected keywords from high scores to low scores according to the scores of the selected keywords and generating the promotion market navigation according to a sorting result;
an obtaining module, configured to obtain a target keyword clicked by a user in the promoted market navigation, enter a promotion page corresponding to the target keyword to obtain a target promotion page, query target summary information of the target promotion page, and update time update _ time, current time system _ time, and first set update time N stored in the target summary information according to the last update time update _ time, current time system _ time, and first set update time N1Rendering page data of the target promotion page;
a calculating module, configured to calculate a time difference T between a last update time and a current time according to the last update time of the target promotion pageDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2Refreshing the target promotion page; wherein，N2Indicating a second set update time.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the data processing method for a keyword promotion page of any of the above embodiments when executing the computer program.
A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the data processing method for a keyword promotion page of any of the above embodiments.
The data processing method, the data processing device, the computer equipment and the storage medium for the keyword popularization page have the advantages that by determining the scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling a data generation interface of a keyword promotion page respectively aiming at each selected keyword, assembling the promotion pages of each selected keyword, storing the summary information of each promotion page, the selected keywords are ranked from high to low scores according to their scores, generating a promoted market navigation according to the sequencing result, acquiring a target keyword clicked by a user in the promoted market navigation, entering a promoted page corresponding to the target keyword to obtain a target promoted page, inquiring target summary information of the target promoted page, according to the last update time update _ time, the current time system _ time and the first set update time N stored in the target summary information.1Rendering the page data of the target promotion page, and calculating the time difference T between the last update time and the current time according to the last update time of the target promotion pageDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2And refreshing the target promotion page to improve the generation efficiency of the corresponding promotion page, so that the target promotion page can be updated efficiently.
Drawings
FIG. 1 is a flow diagram of a data processing method for a keyword promotional page of an embodiment;
FIG. 2 is a schematic diagram of summary information of a promotion page of one embodiment;
FIG. 3 is a schematic diagram of an update process for database summary information, according to one embodiment;
FIG. 4 is a flow diagram of a priority update of an embodiment;
FIG. 5 is a block diagram of a data processing apparatus for a keyword promotion page according to an embodiment;
FIG. 6 is a schematic diagram of a computer device of an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In one embodiment, as shown in fig. 1, a data processing method for a keyword promotion page is provided, which includes the following steps:
s10, determining scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling data generation interfaces of the keyword promotion pages aiming at all the selected keywords respectively, assembling the promotion pages of all the selected keywords, and storing summary information of all the promotion pages.
The keywords are input by the user when using the search engine, and can maximally summarize the information content searched by the user. Keywords that are spoken in the search engine optimization SEO industry often refer to the core and main content of a web page. For a search engine, a web page is mainly about what aspect is, and that aspect can be attributed a keyword. For example, we search for a tractor in hundred degrees, the user will input "tractor" in the hundred degree input box, and will search for all items related to the tractor, and the three words of "tractor" are a search keyword. The keyword database can record massive keywords related to the user in daily life.
Specifically, the keywords with certain quality and meeting the requirements can be selected in the steps for popularization. The specific selection method comprises the following steps: all the keywords stored in the database are subjected to word segmentation by calling an internal search engine one by one to inquire out corresponding products and the number of manufacturers; and calculating the scores of the keywords according to the products and the number of manufacturers corresponding to the keywords so as to select the keywords with certain values as the selected keywords. Respectively calling keyword promotion page data to generate interfaces aiming at the selected keywords, calling an in-site search engine and filtering processing data by an interface program, assembling promotion page data json of the keywords, storing the json data to a text server, and simultaneously storing summary information tb _ profile of the promotion page data in a database; so as to complete the initialization of the keyword promotion page data. In one example, the summary information tb _ profile of the promotion page can be as shown with reference to FIG. 2.
In one embodiment, determining the score for each keyword in the keyword database comprises:
and acquiring the product number m and the company number n corresponding to each keyword in the keyword database, and calculating the score of each keyword by weighted average of the product number m and the company number n corresponding to each keyword.
As an embodiment, the determination process of the score of the keyword includes:
s＝m*β+(1-β)*n，
in the formula, s represents the score of the keyword, and β represents the first set weight.
Specifically, the first setting weight β may be in a range of 0 < β < 1, for example, β may be equal to 0.5.
And S20, sorting the selected keywords from high scores to low scores according to the scores of the selected keywords, and generating the promotion market navigation according to the sorting result.
The promotion market navigation can record each selected keyword, arrange the selected keywords with high scores in front of the selected keywords with low scores in the back of the selected keywords with low scores, and associate each selected keyword with the corresponding promotion page and summary information of the promotion page.
S30, obtaining a target keyword clicked by a user in the promotion market navigation, entering a promotion page corresponding to the target keyword to obtain a target promotion page, inquiring target summary information of the target promotion page, and rendering page data of the target promotion page according to last update time update _ time and first set update time stored in the target summary information.
In one embodiment, the last update time update _ time, the current time system _ time and the first set update time N stored in the target summary information are used1Rendering the page data of the target promotion page includes:
if system _ time-update _ time>N1If so, putting the target keywords into an updating scheduling queue to wait for data updating, inquiring target page data according to a json data text address stored in the summary information of the target promotion page, returning to a front-end page, and rendering and displaying according to the target page data;
if system _ time-update _ time<N1And inquiring target page data according to the json data text address stored in the summary information of the target popularization page, returning to the front-end page, and rendering and displaying according to the target page data.
Specifically, the above steps may determine that the optimal update time of the page data is N according to the website data update period rule, the search engine update frequency, and other factors1(first set update time); a user clicks a target keyword in the promotion market navigation and accesses a target keyword promotion page; at the moment, the corresponding browser sends an http request and calls a background popularization page data query interface; the program of the background promotion page data query interface firstly according to the targetThe keywords are searched in the database for the summary information tb _ profile of the promotion page, and the last update time update _ time stored in the summary information tb _ profile and the optimal update time of the corresponding page data are N1Comparing the current time system _ time minus update _ time with N1Judging whether the data needs to be updated or not; if system _ time-update _ time>N1If the data needs to be updated, putting the keywords into an update scheduling queue to wait for data update; meanwhile, page data is inquired according to the json data text address stored in the summary information, and a front-end page is returned for rendering and displaying; if system _ time-update _ time<N1That is, updating is not needed, only the page data is inquired according to the json data text address in the summary information, and the front-end rendering is returned.
S40, according to the last update time of the target promotion page, calculating the time difference T between the last update time and the current timeDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2Refreshing the target promotion page; wherein N is2Indicating a second set update time.
The promotion page data is updated passively through user access, so that the freshness of the pages with very high heat can be maintained by ensuring that the pages are frequently accessed. However, in practical situations, most pages cannot guarantee the access heat, and meanwhile, certain freshness needs to be guaranteed, so an active updating strategy needs to be provided, and at this time, it can be determined that the page must be updated for N time according to the update cycle rule of website data, the update frequency of a search engine and other factors2(second set update time), according to the keyword promotion page, the average T of the page is calculated according to the visit P in the latest period of timeV(page visit density) once a day; according to the last update time stored in the corresponding keyword promotion page summary information tb _ profile table, the last update time is calculated to be T from the current time differenceD(ii) a According to page access density TVAnd a time difference TDCalculating that a page must be updatedIs left for a time period TS＝TV-TD(ii) a If T is judgedD<N2Then no data update (refresh) is required; if TD>N2Then an update is required.
The data processing method for the keyword promotion page determines the scores of all the keywords in the keyword database, extracting selected keywords according to the scores, calling a data generation interface of a keyword promotion page respectively aiming at each selected keyword, assembling the promotion pages of each selected keyword, storing the summary information of each promotion page, the selected keywords are ranked from high to low scores according to their scores, generating a promoted market navigation according to the sequencing result, acquiring a target keyword clicked by a user in the promoted market navigation, entering a promoted page corresponding to the target keyword to obtain a target promoted page, inquiring target summary information of the target promoted page, according to the last update time update _ time, the current time system _ time and the first set update time N stored in the target summary information.1Rendering the page data of the target promotion page, and calculating the time difference T between the last update time and the current time according to the last update time of the target promotion pageDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2And refreshing the target promotion page to improve the generation efficiency of the corresponding promotion page, so that the target promotion page can be updated efficiently.
In one embodiment, according to the last updating time of the target promotion page, the time difference T between the last updating time and the current time is calculatedDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2After the target promotion page is refreshed, the method further includes:
acquiring page access density of each promotion page;
calculating the residual updating duration T of the target promotion pageS；
Calculating the updating urgency degree E of each promotion page according to the page access density of each promotion page and the updating remaining time of each promotion page;
and sequencing the updating urgency degree E from large to small, and refreshing each promotion page according to a sequencing result.
In one example, the page access density TVAnd updating the remaining duration TSThe data can be unified by a normalization method, and then the final update urgency degree E is calculated according to the weighted average.
E.g. E- α TS’+(1-α)TV’，TS' represents a normalized remaining time (updated remaining duration) which must be updated, TVSpecifically, α represents the second set weight, α may range from 0 < α < 1, such as α may be 0.5, etc. in one example, since T is the value of TSThe index is more important, so the value of α should be as large as possible, several groups of values can be taken and brought into the actual scene for comparison, and the best value of α is selected, and the access P data has certain stability, so the T value is more importantVThe calculation period of (2) can be determined according to actual conditions, and frequent calculation is not needed.
Preferably, prior to normalization, T is preferably alignedVAnd TSThe abnormal values of (2) are filtered, and the influence caused by the individual abnormal data which are too large or too small is reduced as much as possible. Here, the max-min method was chosen for normalization, but because of TSThe smaller the emergency, the higher the urgency, so TSThe normalization of (c) requires changing the following equation:
TV＝(TV-min)/(max-min)，
TS′＝(max-TS)/(max-min)，
the present embodiment is based on TVAnd TSCalculating the urgency E of updating the promotion page data; and (4) inquiring the keyword promotion page data which needs to be updated most according to the updating urgency degree E in a sequencing mode, and updating in sequence to finish active updating.
The data processing method for the keyword promotion page has the following technical effects: (1) a set of keyword promotion page generation method and an updating strategy are provided; (2) the problem of access performance of the promotion page is solved; (3) by using the technologies of task scheduling, thread pool and the like, the performance problem of passive updating of a large batch of pages is solved; (4) the problem that on the premise of limited resources, a large amount of page number updating tasks are faced, and the pages which need to be updated are updated to the maximum extent is solved.
In one embodiment, the remaining duration T is updatedSThe calculation process of (2) includes:
TS＝TV-TD，
TVrepresenting page access density, TDRepresenting the time difference between the last update time and the current time.
The embodiment may update the remaining duration TSAnd carrying out accurate calculation.
In one embodiment, the calculation of the page access density includes:
TV＝n/P，
TVand P represents the visit amount of the promotion page in n days.
The embodiment can access page access density T of each promotion pageVAnd carrying out accurate calculation.
In an embodiment, the data processing method for the keyword promotion page may be further characterized by the following processes:
(1) initializing keyword promotion page data:
most of the platform keywords come from user search, so the quality is high, the quality is low, the quantity is large, and the keywords with certain popularization value can be selected by a certain method. The method comprises the following steps: and calling all the keywords stored in the database one by internal search engines to inquire the corresponding products and the number of manufacturers, calculating the scores of the keywords according to the products and the number of manufacturers, and selecting the keywords with popularization values according to the scores.
According to the keyword scoring, keywords with popularization value are inquired, keyword popularization page data generation interfaces are respectively called, an interface program calls an in-site search engine and filtering processing data according to business rules, popularization page json data of the keywords are assembled, the json data are stored in a text server or a database (a MongoDB database or cloud storage can be selected, and the like), here, a self-researched large text cloud storage FFS in a company is selected, meanwhile, keyword information, data updating time and an FFS text address are stored in the database, and here, an Oracle database tb _ profile table (as shown in figure 2) used by the current company is selected.
(2) Website portal keyword promotion market generation:
the popularization form of the keyword or the display mode is various, the purpose is to provide a most common navigation mode for better popularization effect. And inquiring keywords with a popularization page, and generating keyword popularization market navigation through keyword classification and keyword grading sequencing.
(3) And (3) passively updating the page data:
the passive updating of the promotion page is mainly triggered by user access. Two indexes are firstly determined, namely the optimal updating time of the promotion page is determined to be N through experience and observation according to the updating period and the updating amount of the website data (the updating amount: the ratio of the number of the product updates to the total product number) and the data updating frequency of a website search engine1(typically ranging essentially from a few minutes to several hours), the time must be updated to N2(typically the basic range is within one to several days), N1<N2Since, first of all, it is known from the general knowledge that the optimum refresh period will be smaller than the necessary refresh period; secondly, according to the statistical rule, even if the pages with very high heat degree cannot be updated within the optimal updating time occasionally, the probability of the pages with very high heat degree can keep enough updating frequency, namely page freshness, so that the later active updating program can take more care of the pages with relatively low heat degree;
the user accesses the keyword promotion page through the keyword market,sending a data query request to a backend API (application programming interface), querying general data information tb _ profile of a promotion page of the database by a background interface program according to keywords, and directly calling an in-site search engine and returning a search result rendering page if the general information does not exist; if the summary information exists, the last update time update _ time stored in the summary information and the optimal update time of the page data are N1Comparing the current time system _ time minus update _ time with N1If the system _ time-update _ time is the same as the system _ time-update _ time, judging whether the promotion page data needs to be updated or not<N1If the updating is not needed, inquiring promotion page data according to ffs _ url in the summary information, and returning to the front-end rendering; if system _ time-update _ time>N1And if the data needs to be updated, the keywords need to be put into an update scheduling queue to wait for data update, and meanwhile, the promotion page data is inquired according to ffs _ url in the summary information and returned to the front-end rendering. At the moment, the Task scheduling queue receives the update Task for consumption, the Task is distributed to different thread pools according to the type of the keyword to perform data update operation, data assembly is completed and uploaded to the FFS, and database summary information is updated at the same time; in one example, the update process of database summary information may be as described with reference to FIG. 3.
The Task scheduling Task is a production consumer model, and is asynchronously distributed to different thread pool tasks T by judging the type of the keywords, such as mechanical words or food wordsA1、TA2……，TAAnd then, according to the page modules generated as required, the thread pool tasks T of different modules are parallelly and asynchronously calledB1、TB2… …, last TAAccording to each module task TBThe generated data are summarized into final json data to be stored in the FFS, and summary information of the promotion page of the database is updated.
Note that: the thread pool can share resources and can be isolated, and the thread pool is determined according to actual conditions and machine conditions. And meanwhile, locking is required, and repeated tasks of the key words K can not be received before the key words K are put into the scheduling platform and the complete processing is finished.
(4) And actively updating the program by the promotion page data:
the passive updating of page data is mainly completed by the access of a user, so that the pages with very high heat can be ensured to be frequently accessed to keep the freshness of the pages. However, in practice, most pages cannot guarantee such access heat, and at the same time, certain freshness needs to be guaranteed, so that a policy of active update needs to be provided:
a timed task may be initiated below to actively update the promotional page data. For millions of pages of data, if the processing time of a single page is more than 6 seconds on average, the resources and time consumed are huge and almost impossible to complete if the whole amount of data is updated. Preferably, in a practical situation, the page data are not required to be updated at the same time, so that only the page data most required to be updated need to be selected and updated preferentially, and in an example, the flow of preferential updating is as shown in fig. 4.
The update urgency level E may be used here to represent the priority of the update of the data. Firstly, the access density T of each keyword page is calculated according to the access amount P and the time period of the keyword promotion page in the latest period of timeV(average T)VTime is accessed once), and then the difference from the current time is calculated to be T according to the last updating time of the data of each keyword promotion pageDTo calculate the remaining time T that must be updatedS＝TV-TDUpdating the period N as necessary2Therefore, the following steps are carried out:
if TD<N2Then no update is needed;
if TD>N2If so, updating is needed, and the promotion page data needing to be updated is updated according to TSAnd the access density T of the pageVAnd comprehensively calculating the urgency degree E of the page, and inquiring the promotion page data sequence which needs to be updated most according to the ranking of the urgency degree E.
Here TVAnd TSThe data needs to be unified by a normalization method, and then the final update urgency degree E- α T is calculated according to the weighted averageS’+(1-α)TV’(TS' represents the remaining time after normalization, T, which must be updatedV' represents the heat and importance of the normalized page, so the weighted average calculates how urgent the page data must be updated). Before normalization, T is preferably alignedVAnd TSThe abnormal values of (2) are filtered, and the influence caused by the individual abnormal data which are too large or too small is reduced as much as possible. Here, the max-min method was chosen for normalization, but because of TSThe smaller the emergency, the higher the urgency, so TSThe normalization of (c) requires changing the following equation:
TV’＝(TV-min)/(max-min)，
TS’＝(max-TS)/(max-min)，
description of the drawings:
1. due to TSIndexes are more important, so the value of α should be as large as possible, a plurality of groups of values can be taken and brought into an actual scene for comparison, and the best value α is selected;
2. t since the access P data has certain stabilityVThe calculation period of the method can be determined according to the actual situation, and frequent calculation is not needed;
finally we are based on TD＞N2And (4) sorting the conditions and the urgency degree E, inquiring keyword promotion page data needing to be updated, putting the keyword promotion page data into an update scheduling task queue (the scheduling task is preferably isolated from the scheduling task needing to be updated passively due to user access so as not to influence each other), and actively updating.
The embodiment provides a set of keyword promotion page generation method and an update strategy, and the biggest highlight is to use factors such as page access amount and data update time to calculate the update urgency degree, and to update the page data which needs to be updated most under the condition of limited resources.
In one embodiment, referring to fig. 5, there is provided a data processing apparatus for a keyword promotion page, including:
the determining module 10 is configured to determine scores of the keywords in the keyword database, extract selected keywords according to the scores, call a data generating interface of a keyword promotion page for each selected keyword, assemble the promotion page for each selected keyword, and store summary information of each promotion page;
the sorting module 20 is used for sorting the selected keywords from high scores to low scores according to the scores of the selected keywords and generating the promotion market navigation according to a sorting result;
an obtaining module 30, configured to obtain a target keyword clicked by a user in the promoted market navigation, enter a promotion page corresponding to the target keyword to obtain a target promotion page, query target summary information of the target promotion page, and update time update _ time, current time system _ time, and first set update time N stored in the target summary information according to the last update time update _ time, the current time system _ time, and the first set update time N1Rendering page data of the target promotion page;
a calculating module 40, configured to calculate a time difference T between the last update time and the current time according to the last update time of the target promotion pageDAccording to the page access density and the time difference T of the target promotion pageDCalculating the residual time T of updating the target promotion pageSIf T isS>N2Refreshing the target promotion page; wherein N is2Indicating a second set update time.
For specific limitations of the data processing apparatus for the keyword promotion page, reference may be made to the above limitations on the data processing method for the keyword promotion page, and details are not repeated here. All or part of the modules in the data processing device for the keyword promotion page can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a data processing method for a keyword promotion page. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Based on the examples described above, in one embodiment, a computer device is further provided, and the computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement any one of the data processing methods for the keyword promotion page in the embodiments described above.
It will be understood by those skilled in the art that all or part of the processes in the methods of the embodiments described above may be implemented by a computer program to instruct related hardware, where the program may be stored in a non-volatile computer-readable storage medium, and as in the embodiments of the present invention, the program may be stored in the storage medium of a computer system and executed by at least one processor in the computer system, so as to implement the processes of the embodiments including the data processing method for the keyword promotion page described above. The storage medium may be a magnetic disk, an optical disk, a Read-only Memory (ROM), a Random Access Memory (RAM), or the like.
Accordingly, in an embodiment, a computer storage medium and a computer readable storage medium are also provided, on which a computer program is stored, wherein the program, when executed by a processor, implements any one of the data processing methods for a keyword promotion page as in the above embodiments.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It should be noted that the terms "first \ second \ third" referred to in the embodiments of the present application merely distinguish similar objects, and do not represent a specific ordering for the objects, and it should be understood that "first \ second \ third" may exchange a specific order or sequence when allowed. It should be understood that "first \ second \ third" distinct objects may be interchanged under appropriate circumstances such that the embodiments of the application described herein may be implemented in an order other than those illustrated or described herein.
The terms "comprising" and "having" and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device that comprises a list of steps or modules is not limited to the listed steps or modules but may alternatively include other steps or modules not listed or inherent to such process, method, product, or device.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A data processing method for a keyword promotion page is characterized by comprising the following steps:
s10, determining scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling data generation interfaces of the keyword promotion pages aiming at all the selected keywords respectively, assembling the promotion pages of all the selected keywords, and storing summary information of all the promotion pages;
s20, sorting the selected keywords from high scores to low scores according to the scores of the selected keywords, and generating the promotion market navigation according to the sorting result;
s30, obtaining a target keyword clicked by a user in the promotion market navigation, entering a promotion page corresponding to the target keyword to obtain a target promotion page, inquiring target summary information of the target promotion page, and updating the last update time _ time, the current time system _ time and the first set update time N stored in the target summary information1Rendering page data of the target promotion page;
s40, according to the last update time of the target promotion page, calculating the time difference T between the last update time and the current timeDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2Refreshing the target promotion page; wherein N is2Indicating a second set update time.
2. The data processing method for the keyword promotion page according to claim 1, wherein in one embodiment, the time difference T between the last update time and the current time is calculated according to the last update time of the target promotion pageDAccording to the target popularization pagePage access density of a surface and time difference TDIf T isD>N2After the target promotion page is refreshed, the method further includes:
acquiring page access density of each promotion page;
calculating the residual updating duration T of the target promotion pageS；
Calculating the updating urgency degree E of each promotion page according to the page access density of each promotion page and the updating remaining time of each promotion page;
and sequencing the updating urgency degree E from large to small, and refreshing each promotion page according to a sequencing result.
3. The data processing method for the keyword promotion page of claim 2, wherein in one embodiment, the remaining duration T is updatedSThe calculation process of (2) includes:
TS＝TV-TD，
TVrepresenting page access density, TDRepresenting the time difference between the last update time and the current time.
4. The data processing method for the keyword promotion page according to claim 1, wherein in one embodiment, the calculation process of the page access density comprises:
TV＝n/P，
TVand P represents the visit amount of the promotion page in n days.
5. The data processing method for the keyword promotion page according to claim 1, wherein in one embodiment, the last update time, the current time, the system time and the first set update time N are stored in the target summary information1Rendering the page data of the target promotion page includes:
if system _ time-update _ time>N1Put the target keywordEntering an updating scheduling queue to wait for data updating, inquiring target page data according to a json data text address stored in the summary information of the target promotion page, returning to a front end page, and rendering and displaying according to the target page data;
if system _ time-update _ time<N1And inquiring target page data according to the json data text address stored in the summary information of the target popularization page, returning to the front-end page, and rendering and displaying according to the target page data.
6. The data processing method for a keyword promotional page according to claim 1 characterized in that in one embodiment, determining the score of each keyword in the keyword database comprises:
and acquiring the product number m and the company number n corresponding to each keyword in the keyword database, and calculating the score of each keyword by weighted average of the product number m and the company number n corresponding to each keyword.
7. The data processing method for the keyword promotion page of claim 6, wherein in one embodiment, the determining process of the score of the keyword comprises:
s＝m*β+(1-β)*n，
in the formula, s represents the score of the keyword, and β represents the first set weight.
8. A data processing apparatus for a keyword promotion page, comprising:
the determining module is used for determining scores of all keywords in the keyword database, extracting selected keywords according to the scores, calling a data generating interface of a keyword promotion page aiming at all the selected keywords respectively, assembling the promotion pages of all the selected keywords, and storing summary information of all the promotion pages;
the sorting module is used for sorting the selected keywords from high scores to low scores according to the scores of the selected keywords and generating the promotion market navigation according to a sorting result;
an obtaining module, configured to obtain a target keyword clicked by a user in the promoted market navigation, enter a promotion page corresponding to the target keyword to obtain a target promotion page, query target summary information of the target promotion page, and update time update _ time, current time system _ time, and first set update time N stored in the target summary information according to the last update time update _ time, current time system _ time, and first set update time N1Rendering page data of the target promotion page;
a calculating module, configured to calculate a time difference T between a last update time and a current time according to the last update time of the target promotion pageDAccording to the page access density and the time difference T of the target promotion pageDIf T isD>N2Refreshing the target promotion page; wherein N is2Indicating a second set update time.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the data processing method for a keyword promotion page of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the data processing method for a keyword promotion page of claims 1 to 7.
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