CN111581513A - Website intelligent information aggregation system - Google Patents
Website intelligent information aggregation system Download PDFInfo
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- CN111581513A CN111581513A CN202010384446.4A CN202010384446A CN111581513A CN 111581513 A CN111581513 A CN 111581513A CN 202010384446 A CN202010384446 A CN 202010384446A CN 111581513 A CN111581513 A CN 111581513A
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- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
The invention discloses an intelligent website information aggregation system which comprises a website acquisition module, a website analysis module, a server, a website aggregation module, a website pushing module, a hot search arrangement module and a registration login module, wherein the website acquisition module is used for acquiring website information; the website analysis module is used for retrieving and analyzing website information; the hot search arrangement module is used for arranging search keyword information in a website to be recommended; the website pushing module is used for pushing the hot search arrangement list with a high fitness value with the browsing user to the browsing user, and the website aggregation module is used for calculating the fitness of the browsing website and the browsing user in an intelligent website pushing mode; the websites to be recommended are conveniently aggregated by analyzing and calculating the popularity value of the browsed websites, the aggregated websites are conveniently recommended to the browsed users by analyzing the hot search arrangement value of the keyword information searched by the browsed users in the websites to be recommended, and the website information sharing efficiency is improved.
Description
Technical Field
The invention belongs to the technical field of information processing, relates to a website information aggregation technology, and particularly relates to an intelligent website information aggregation system.
Background
Information aggregation is an innovation of information organization and search mode developed on the basis of corresponding technology and theory by taking the integration of 'scene' factors as a main characteristic under the condition that the current search system does not meet the complex and various information requirements of users.
The comparison document CN110188301A discloses an information aggregation method for websites, and belongs to the field of information aggregation. The method comprises for each of the stored subject words, performing the steps of: searching the special topic words in a search engine to obtain a first amount of resources related to the special topic words and belonging to the website in a search result; acquiring a first quantity of resources ranked according to the latest reply from the resources related to the thematic words in the website; acquiring the first third quantity of resources ranked according to the popularity in the resources related to the thematic words in the website; and obtaining an aggregated page associated with the topic word by using the first quantity of resources, the second quantity of resources, and the third quantity of resources. The method can make the website more friendly to a search engine, thereby improving the page weight and ranking of the website.
At present, the aggregated website cannot be conveniently recommended to the browsing user, so that the sharing efficiency of the website information is reduced.
Disclosure of Invention
The invention aims to provide an intelligent website information aggregation system, which is convenient for aggregating websites to be recommended by analyzing and calculating welcome values of browsed websites, is convenient for recommending the aggregated websites to the browsed users by analyzing hot search arrangement values of keyword information searched by the browsed users in the websites to be recommended, and improves website information sharing efficiency.
The technical problem to be solved by the invention is as follows:
(1): by analyzing and calculating the website intelligent information, the websites browsed by the browsing user can be conveniently aggregated;
(2): how to set an analysis and calculation mode is convenient for recommending the aggregated website to the browsing user, and the website information sharing efficiency is improved;
the purpose of the invention can be realized by the following technical scheme:
a website intelligent information aggregation system comprises a website acquisition module, a website analysis module, a server, a website aggregation module, a website pushing module, a hot search arrangement module and a registration login module;
the website acquisition module is connected with the Internet and acquires website information clicked by a user in a media social website from the network, wherein the website information comprises website click time, refreshing times and creation time; the website acquisition module sends website information to the server, the website analysis module is used for retrieving and analyzing the website information, and the specific processing steps are as follows:
the method comprises the following steps: marking the browsing website as Di, i being 1 … n;
step two: counting the click time of a pre-click page of a user before opening a browsing website, and marking the click time as BDiCounting the browsing time of the user after opening the browsing website, calculating the total time to obtain the browsing time of the browsing website, and marking the browsing time as TDi；
Step three: counting the refreshing times of the browsed websites when being browsed by the user, calculating the total refreshing times to obtain the browsing times of the browsed websites, and marking the browsing times as FDi；
Step four: setting the existing time of the browsing website after being created as CDi；
Step five: using formulas
Obtaining a popularity value SHY of a websiteDiWherein λ is a correction factor, and its value is 0.74584; a1, a2, a3 and a4 are all preset proportionality coefficients;
step six: when the popularity value is larger than a set threshold value, a recommendation instruction is generated, the browsing website is marked as a to-be-recommended website of the browsing user, and the website analysis module sends the recommendation instruction and the to-be-recommended website to the hot search arrangement module;
the hot search arrangement module is used for arranging search keyword information in a website to be recommended, and the specific arrangement steps are as follows;
s1: collecting user registration information of a browsing website through a registration login module, and marking a browsing user as Yh, wherein h is 1 … n;
s2: setting the network age of browsing user as EYhCounting the browsing time of the browsing user for browsing the website as SYh；
S3: marking keyword information searched when a browsing user browses a website as Gx, wherein x is 1 … n, and counting the number of times that the browsing user searches for the keyword information as CGx；
S4: using formulas
Obtaining a hot search arrangement value F for obtaining keyword information searched by browsing users in a website to be recommendedYh(ii) a Wherein a5, a6 and a7 are all preset proportionality coefficients; kYhThe total recommendation score is the total recommendation score of the website to be recommended;
s5: marking the hot search arrangement value of the keyword information searched in the browsing website by the browsing user as FYh1Marking the hot search arrangement value of the corresponding keyword in the website to be recommended of the browsing user as FYh0And comparing, using a formula
Calculating a recommendation total score K of a website to be recommendedYh；
The website pushing module is used for pushing the hot search arrangement list with a high fitness value with the browsing user to the browsing user, and the specific pushing process is as follows:
a: obtaining a popularity value SHY of a website browsed by a browsing userDiAnd the total recommendation score K of the website to be recommendedYhUsing the formula Qh-SHYDi+a8*KYhAcquiring a fitting value of the browsing user and the website to be recommended, wherein a8 is a preset proportionality coefficient;
b: the website aggregation module merges the websites with the highest fitting value Qh with the browsing user, and pushes the websites to be recommended to the browsing user through the website pushing module; and the number of the websites to be recommended of the browsing users is reduced by one.
Preferably, the website aggregation module is used for a website intelligent pushing mode and calculating the engagement degree between a browsing website and a browsing user, and the specific steps are as follows:
the method comprises the following steps: the server acquires the current website to be recommended according to the arrangement sequence of the contract values Qh of the browsing users through the Internet, and marks the website which is ranked n before the contract values Qh of the browsing users as a website set to be recommended;
step two: pushing the website to be recommended with the first fitting value Qh of the browsing user to the browsing user through a website pushing module; reducing the number of the to-be-recommended website sets of the browsing users by one;
step three: and uploading the (n + 1) th website to be recommended with the browsing user matching value Qh ranking to a website set to be recommended for supplementation by the website aggregation module.
Preferably, the popular information of the browsed websites includes posting quantity and comment quantity in the websites, and the website aggregation module processes the browsed websites into a set of websites to be recommended through sharing times among the websites.
Preferably, the registration login module is configured to count registration information of the browsing user, a network age of the browsing user, and a browsing duration of the browsing user when the browsing user browses the website, and send the data to the server for storage, and the server matches the registration information of the browsing user with the browsing information, where the browsing information includes a click time of a pre-click page of the browsing user before the browsing user opens the browsing website and a browsing time after the browsing user opens the browsing website.
The invention has the beneficial effects that:
(1) the website acquisition module is connected with the Internet and acquires website information clicked by a user in a media social website from the network, wherein the website information comprises website click time, refreshing times and creation time; the website acquisition module sends website information to a server, a welcome value of a browsed website is obtained by using a formula, if the welcome value is larger than a set threshold value, a recommendation instruction is generated, the browsed website is marked as a to-be-recommended website of a browsed user, and the website analysis module sends the recommendation instruction and the to-be-recommended website to the hot search arrangement module; obtaining a hot search arrangement value of the keyword information searched by the browsing user in the website to be recommended through the keyword information searched when the browsing user browses the website, comparing the hot search arrangement values of the corresponding keywords in the website to be recommended of the browsing user, and calculating a recommendation total score of the website to be recommended by using a formula; acquiring a fitting value of the browsing user and the website to be recommended by using a formula, and pushing the website to be recommended to the browsing user by using a website pushing module; the website aggregation module merges the websites with the highest fitting value Qh with the browsing users, and the number of the websites to be recommended of the browsing users is reduced by one; the websites to be recommended are conveniently aggregated by analyzing and calculating the popularity value of the browsed websites, the aggregated websites are conveniently recommended to the browsed users by analyzing the hot search arrangement value of the keyword information searched by the browsed users in the websites to be recommended, and the website information sharing efficiency is improved.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
As shown in fig. 1, an intelligent website information aggregation system includes a website acquisition module, a website analysis module, a server, a website aggregation module, a website push module, a hot search configuration module, and a registration module;
the system comprises a website acquisition module, a website display module and a website display module, wherein the website acquisition module is connected with the Internet and acquires website information clicked by a user in a media social website from the network, and the website information comprises website click time, refreshing times and creation time; the website information is sent to the server by the website acquisition module, the website analysis module is used for retrieving and analyzing the website information, and the specific processing steps are as follows:
the method comprises the following steps: marking the browsing website as Di, i being 1 … n;
step two: counting the click time of a pre-click page of a user before opening a browsing website, and marking the click time as BDiCounting the browsing time of the user after opening the browsing website, calculating the total time to obtain the browsing time of the browsing website, and marking the browsing time as TDi；
Step three: counting the refreshing times of the browsed websites when being browsed by the user, calculating the total refreshing times to obtain the browsing times of the browsed websites, and marking the browsing times as FDi；
Step four: setting the existing time of the browsing website after being created as CDi；
Step five: using formulas
Obtaining a popularity value SHY of a websiteDiWherein λ is a correction factor, and its value is 0.74584; a1, a2, a3 and a4 are all preset proportionality coefficients;
step six: when the popularity value is larger than a set threshold value, a recommendation instruction is generated, the browsing website is marked as a to-be-recommended website of the browsing user, and the website analysis module sends the recommendation instruction and the to-be-recommended website to the hot search arrangement module;
the hot search arrangement module is used for arranging search keyword information in a website to be recommended, and the specific arrangement steps are as follows;
s1: collecting user registration information of a browsing website through a registration login module, and marking a browsing user as Yh, wherein h is 1 … n;
s2: setting the network age of browsing user as EYhCounting the browsing time of the browsing user for browsing the website as SYh；
S3: marking keyword information searched when a browsing user browses a website as Gx, wherein x is 1 … n, and counting the number of times that the browsing user searches for the keyword information as CGx；
S4: using formulas
Obtaining a hot search arrangement value F for obtaining keyword information searched by browsing users in a website to be recommendedYh(ii) a Wherein a5, a6 and a7 are all preset proportionality coefficients; kYhThe total recommendation score is the total recommendation score of the website to be recommended;
s5: marking the hot search arrangement value of the keyword information searched in the browsing website by the browsing user as FYh1Marking the hot search arrangement value of the corresponding keyword in the website to be recommended of the browsing user as FYh0And comparing, using a formula
Calculating a recommendation total score K of a website to be recommendedYh；
The website pushing module is used for pushing the hot search arrangement list with a high fitness value with the browsing user to the browsing user, and the specific pushing process is as follows:
a: obtaining a popularity value SHY of a website browsed by a browsing userDiAnd the total recommendation score K of the website to be recommendedYhUsing the formula Qh-SHYDi+a8*KYhAcquiring a fitting value of the browsing user and the website to be recommended, wherein a8 is a preset proportionality coefficient;
b: the website aggregation module merges the websites with the highest fitting value Qh with the browsing user, and pushes the websites to be recommended to the browsing user through the website pushing module; and the number of the websites to be recommended of the browsing users is reduced by one.
Preferably, the website aggregation module is used for a website intelligent pushing mode and calculating the engagement degree between the browsing website and the browsing user, and the specific steps are as follows:
the method comprises the following steps: the server acquires the current website to be recommended according to the arrangement sequence of the contract values Qh of the browsing users through the Internet, and marks the website which is ranked n before the contract values Qh of the browsing users as a website set to be recommended;
step two: pushing the website to be recommended with the first fitting value Qh of the browsing user to the browsing user through a website pushing module; reducing the number of the to-be-recommended website sets of the browsing users by one;
step three: and uploading the (n + 1) th website to be recommended with the browsing user matching value Qh ranking to a website set to be recommended for supplementation by the website aggregation module.
Preferably, the popular information of the browsed websites includes posting quantity and comment quantity in the websites, and the website aggregation module processes the browsed websites into a set of websites to be recommended according to the sharing times among the websites.
Preferably, the registration login module is configured to count registration information of the browsing user, a network age of the browsing user, and a browsing duration of the browsing user when the browsing user browses the website, and send the data to the server for storage, and the server matches the registration information of the browsing user with the browsing information, where the browsing information includes a click time of a pre-click page of the browsing user before the browsing user opens the browsing website and a browsing time after the browsing user opens the browsing website.
The working principle of the invention is as follows: a website intelligent information aggregation system is connected with the Internet through a website acquisition module and acquires website information clicked by a user in a media social website from the network, wherein the website information comprises website click time, refreshing times and creation time; the website acquisition module sends website information to the server and utilizes a formula
The method comprises the steps that a welcome value of a browsed website is obtained, if the welcome value is larger than a set threshold value, a recommending instruction is generated, the browsed website is marked as a to-be-recommended website of a browsed user, and a website analysis module sends the recommending instruction and the to-be-recommended website to a hot search arrangement module; obtaining the hot search arrangement value of the keyword information searched by the browsing user in the website to be recommended through the keyword information searched when the browsing user browses the website, comparing the hot search arrangement values of the corresponding keywords in the website to be recommended of the browsing user, and utilizing a formula
Calculating a total recommendation score of a website to be recommended; acquiring a fitting value of the browsing user and the website to be recommended by using a formula, and pushing the website to be recommended to the browsing user by using a website pushing module; the website aggregation module merges the websites with the highest fitting value Qh with the browsing users, and the number of the websites to be recommended of the browsing users is reduced by one; the websites to be recommended are conveniently aggregated by analyzing and calculating the popularity value of the browsed websites, the aggregated websites are conveniently recommended to the browsed users by analyzing the hot search arrangement value of the keyword information searched by the browsed users in the websites to be recommended, and the website information sharing efficiency is improved.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. A website intelligent information aggregation system is characterized by comprising a website acquisition module, a website analysis module, a server, a website aggregation module, a website pushing module, a hot search arrangement module and a registration login module;
the website acquisition module is connected with the Internet and acquires website information clicked by a user in a media social website from the network, wherein the website information comprises website click time, refreshing times and creation time; the website acquisition module sends website information to the server, the website analysis module is used for retrieving and analyzing the website information, and the specific processing steps are as follows:
the method comprises the following steps: marking the browsing website as Di, i being 1 … n;
step two: counting the click time of a pre-click page of a user before opening a browsing website, and marking the click time as BDiCounting the browsing time of the user after opening the browsing website, calculating the total time to obtain the browsing time of the browsing website, and marking the browsing time as TDi；
Step three: counting the refreshing times of the browsed websites when being browsed by the user, calculating the total refreshing times to obtain the browsing times of the browsed websites, and marking the browsing times as FDi；
Step four: setting the existing time of the browsing website after being created as CDi；
Step five: using formulas
Obtaining a popularity value SHY of a websiteDiWherein λ is a correction factor, and its value is 0.74584; a1, a2, a3 and a4 are all preset proportionality coefficients;
step six: when the popularity value is larger than a set threshold value, a recommendation instruction is generated, the browsing website is marked as a to-be-recommended website of the browsing user, and the website analysis module sends the recommendation instruction and the to-be-recommended website to the hot search arrangement module;
the hot search arrangement module is used for arranging search keyword information in a website to be recommended, and the specific arrangement steps are as follows;
s1: collecting user registration information of a browsing website through a registration login module, and marking a browsing user as Yh, wherein h is 1 … n;
s2: setting the network age of browsing user as EYhCounting the browsing time of the browsing user for browsing the website as SYh；
S3: marking keyword information searched when a browsing user browses a website as Gx, wherein x is 1 … n, and counting the number of times that the browsing user searches for the keyword information as CGx；
S4: using formulas
Obtaining a hot search arrangement value F for obtaining keyword information searched by browsing users in a website to be recommendedYh(ii) a Wherein a5, a6 and a7 are all preset proportionality coefficients; kYhThe total recommendation score is the total recommendation score of the website to be recommended;
s5: marking the hot search arrangement value of the keyword information searched in the browsing website by the browsing user as FYh1Marking the hot search arrangement value of the corresponding keyword in the website to be recommended of the browsing user as FYh0And comparing, using a formula
Calculating a recommendation total score K of a website to be recommendedYh；
The website pushing module is used for pushing the hot search arrangement list with a high fitness value with the browsing user to the browsing user, and the specific pushing process is as follows:
a: obtaining a popularity value SHY of a website browsed by a browsing userDiAnd the total recommendation score K of the website to be recommendedYhUsing the formula Qh-SHYDi+a8*KYhAcquiring a fitting value of the browsing user and the website to be recommended, wherein a8 is a preset proportionality coefficient;
b: the website aggregation module merges the websites with the highest fitting value Qh with the browsing user, and pushes the websites to be recommended to the browsing user through the website pushing module; and the number of the websites to be recommended of the browsing users is reduced by one.
2. The system for website intelligent information aggregation according to claim 1, wherein the website aggregation module is used for a website intelligent push manner and calculating a degree of engagement between a browsing website and a browsing user, and specifically comprises the following steps:
the method comprises the following steps: the server acquires the current website to be recommended according to the arrangement sequence of the contract values Qh of the browsing users through the Internet, and marks the website which is ranked n before the contract values Qh of the browsing users as a website set to be recommended;
step two: pushing the website to be recommended with the first fitting value Qh of the browsing user to the browsing user through a website pushing module; reducing the number of the to-be-recommended website sets of the browsing users by one;
step three: and uploading the (n + 1) th website to be recommended with the browsing user matching value Qh ranking to a website set to be recommended for supplementation by the website aggregation module.
3. The system for intelligent information aggregation of websites according to claim 1, wherein the popular information of the browsed websites includes the number of posts and comments in the websites, and the website aggregation module processes the browsed websites into a set of websites to be recommended by sharing times among the websites.
4. The system of claim 1, wherein the registration login module is configured to count registration information of the browsing user, a network age of the browsing user, and a browsing duration of the browsing user when the browsing user browses the website, and send the data to the server for storage, the server matches the registration information of the browsing user with browsing information, and the browsing information includes a click time of a pre-click page of the browsing user before the browsing user opens the browsing website and a browsing time after the browsing user opens the browsing website.
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