CN109634991A - A kind of searching method based on big data - Google Patents
A kind of searching method based on big data Download PDFInfo
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- CN109634991A CN109634991A CN201811519912.4A CN201811519912A CN109634991A CN 109634991 A CN109634991 A CN 109634991A CN 201811519912 A CN201811519912 A CN 201811519912A CN 109634991 A CN109634991 A CN 109634991A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The invention discloses a kind of searching methods based on big data, comprising the following steps: checks the relevant information of user first, and opens corresponding search interface according to the information of user and carry out information inquiry；User proposes the requirement of inquiry, big data analysis user's requirement, and extracts the keyword in user's requirement；The keyword of user query and the information in the historical query net and logout net of previous people's historical query are compared.A kind of searching method based on big data of the present invention, first, the information that new information is searched with previous people is be combined with each other, the message that people can be allowed to grasp is more comprehensive, is secondly directly combined the information collected with event, people are facilitated to analyze, consequently facilitating people hold the core content of information, the degree of safety of user information finally can be improved, while having expanded the resource of information, facilitate people to search for information next time, brings better prospect of the application.
Description
Technical field
The present invention relates to searching method field, in particular to a kind of searching method based on big data.
Background technique
Over time, people enter information-based society, and people increasingly pay attention to information, for various
The comprehensive and agility of information requires higher and higher, and then people have invented the searching method based on big data, but with
Science and technology is developing, and the epoch, requirement of the people to the searching method based on big data was higher and higher in progress, cause it is traditional based on
The searching method of big data can no longer meet the use demand of people；
There are certain drawbacks in the existing searching method based on big data, firstly, existing based on big number when in use
According to searching method be generally only to directly read the content of former people search, meeting compared with the record of previous people search
Leading to the needs of newest message can not be read in a short time, be unsatisfactory for the requirement of modern people, and network is continuous
Development, information constantly accumulates, and the existing searching method based on big data is generally only by the way of single to information
Classification, information will lead to user's short time too much cannot hold the key content of information, finally, existing based on big data
The search record full disclosure of searching method is called, and safety is relatively low, for this purpose, it is proposed that a kind of search based on big data
Method.
Summary of the invention
The main purpose of the present invention is to provide a kind of searching methods based on big data, can effectively solve background technique
The problems in.
To achieve the above object, the technical scheme adopted by the invention is as follows:
A kind of searching method based on big data, comprising the following steps:
(1), the relevant information of user is checked first, and corresponding search interface is opened according to the information of user and carries out information
Inquiry；
(2), user proposes the requirement of inquiry, big data analysis user's requirement, and extracts in user's requirement
Keyword；
It (3), will be in the keyword of user query and the historical query net and logout net of previous people's historical query
Information compares, and extracts the result of previous people's inquiry and requires the relevant information of relevant up-to-date event to user；
(4), information is ranked up according to the clicking rate of the age bracket of user, the issuing time of information and information；
(5), by the information conveyance after sequence to client, and the information searched is recorded and is input to and is gone through
In history inquiry net, the information in historical query net is updated.
Preferably, in the step (1), the relevant information for checking user includes:
1., the identity of user and age；
2., the routine work of user；
3., the event of the daily concern of user and the time for browsing information；
4., user for itself search information privacy degrees.
Preferably, the step 4. in, user for itself search information privacy degrees can be divided into three grades；
I grade of user, do not announce it is all itself information and search record；
II grade of user does not announce the information of itself but announces the search record of itself；
III grade of user, announce it is all itself information and search record.
Preferably, in the step (2), 2-4 keyword is extracted into the requirement of user.
Preferably, in the step (3), the content of historical query net is divided into personal record and all user records, crucial
When word is matched with the relevant information of historical query net, keyword and personal record and other security requirements are second level and three-level
The search information of user is compared.
Preferably, in the step (3), keyword carries out matched with the information in historical query net and logout net
As a result there are three types of situations:
A, the record of keyword and historical query net exactly matches, and is directly ranked up all results；
B, keyword is matched with the record part of historical query net, is arranged after all information searched are combined
Sequence；
C, the record of keyword and historical query net mismatches, and all information inside big data is compared, and
It prompts user to search for the time required for information, then the information searched is ranked up.
Preferably, in the step (4), sort before first according to age bracket and user daily concern event to information into
Row classification, the higher information of user's attention rate in the same age bracket is extracted, then is ranked up to the information of extraction, is arranged
The rule of sequence is first three entitled clicking rate highest information when sequence according to the issuing time of information and the clicking rate of information, after
The sequence in face differs 100,000 or more according to clicking rate and sorts according to clicking rate, clicking rate differ less than 100,000 according to publication when
Between successively be ranked up.
Preferably, in the step (5), first the information of user's search is sorted out, the history of typing individual subscriber is looked into
In the record for asking net, then judge that the security classification of user, the security classification of user are straight when being II grade of user or III grade of user
It connects and updates historical query net, if the security classification of client is I grade of user, and the record of keyword and historical query net is not
Match, will voluntarily the information searched be classified and be reintegrated, and key is reformulated to the content after integration
Then word is again updated the record of historical query net.
Compared with prior art, the invention has the following beneficial effects:
1, it is integrated again after being compared jointly in the requirement of user and historical query net and logout net, historical query net note
Record previous information, the periphery message of all kinds of major issues comprising newest generation and event in logout net, and event
Attention rate it is relatively high, allow previous message to be combined with each other with newest event, thus allow people grasp message it is more complete
Face；
2, directly information is screened and is classified during searching for, and is divided according to the daily focus of user
Class, can better management information, allow user directly contact itself needs information, and by the information collected directly with
Event is combined, consequently facilitating people hold the core content of information, user is avoided to waste time and energy；
3, suitably the relevant information of historical query net is integrated according to the privacy requirements of user itself, it is ensured that visitor
The safety of family information, and can the information inside historical query net constantly be classified and be expanded, so that history
Inquire net record it is more comprehensive and accurate, and convenient for next time extract information, meet modern people it is comprehensive to information and
The requirement of safety, it is more practical.
Detailed description of the invention
Fig. 1 is a kind of overall structure flow chart of the searching method based on big data of the present invention.
Specific embodiment
To be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, below with reference to
Specific embodiment, the present invention is further explained.
Embodiment 1
(1), the relevant information of user is checked first, and corresponding search interface is opened according to the information of user and carries out information
Inquiry, the relevant information for checking user include:
1., the identity of user and age；
2., the routine work of user；
3., the event of the daily concern of user and the time for browsing information；
4., user for itself search information privacy degrees；
User can be divided into three grades for the privacy degrees of itself search information；
I grade of user, do not announce it is all itself information and search record；
II grade of user does not announce the information of itself but announces the search record of itself；
III grade of user, announce it is all itself information and search record.
(2), user proposes the requirement of inquiry, big data analysis user's requirement, and extracts in user's requirement
The requirement of user is extracted 2-4 keyword by keyword；
It (3), will be in the keyword of user query and the historical query net and logout net of previous people's historical query
Information compares, and extracts the result of previous people's inquiry and requires the relevant information of relevant up-to-date event, history to user
The content of inquiry net is divided into personal record and all user records, and keyword is matched with the relevant information of historical query net
When, keyword is compared with personal record and other security requirements for the search information of second level and three-level user；
Information in keyword and historical query net and logout net carries out matched result, and there are three types of situations:
A, the record of keyword and historical query net exactly matches, and all results are directly issued user；
B, keyword is matched with the record part of historical query net, issues use after all information searched are combined
Family；
C, the record of keyword and historical query net mismatches, and all information inside big data is compared, and
It prompts user to search for the time required for information, the information searched is then sent to user.
It is integrated again after being compared jointly in the requirement of user and historical query net and logout net, historical query net record
Previous information, the periphery message of all kinds of major issues and event in logout net comprising newest generation, and event
Attention rate is relatively high, and previous message is allowed to be combined with each other with newest event, so that the message for allowing people to grasp is more comprehensive.
Embodiment 2
(1), the relevant information of user is checked first, and corresponding search interface is opened according to the information of user and carries out information
Inquiry, the relevant information for checking user include:
1., the identity of user and age；
2., the routine work of user；
3., the event of the daily concern of user and the time for browsing information；
4., user for itself search information privacy degrees；
User can be divided into three grades for the privacy degrees of itself search information；
I grade of user, do not announce it is all itself information and search record；
II grade of user does not announce the information of itself but announces the search record of itself；
III grade of user, announce it is all itself information and search record.
(2), user proposes the requirement of inquiry, big data analysis user's requirement, and extracts in user's requirement
The requirement of user is extracted 2-4 keyword by keyword；
It (3), will be in the keyword of user query and the historical query net and logout net of previous people's historical query
Information compares, and extracts the result of previous people's inquiry and requires the relevant information of relevant up-to-date event, history to user
The content of inquiry net is divided into personal record and all user records, and keyword is matched with the relevant information of historical query net
When, keyword is compared with personal record and other security requirements for the search information of second level and three-level user；
Information in keyword and historical query net and logout net carries out matched result, and there are three types of situations:
A, the record of keyword and historical query net exactly matches, and is directly ranked up all results；
B, keyword is matched with the record part of historical query net, is arranged after all information searched are combined
Sequence；
C, the record of keyword and historical query net mismatches, and all information inside big data is compared, and
It prompts user to search for the time required for information, then the information searched is ranked up；
(4), information is ranked up according to the clicking rate of the age bracket of user, the issuing time of information and information, is sorted
Preceding elder generation classifies to information according to the event of the daily concern of age bracket and user, by user's attention rate in the same age bracket
Higher information extracts, then is ranked up to the information of extraction, and the rule of sequence is issuing time and letter according to information
The clicking rate of breath, first three entitled clicking rate highest information when sequence, subsequent sequence differ 100,000 or more according to clicking rate
It sorts according to clicking rate, clicking rate differs less than 100,000 being successively ranked up according to issuing time.
(5), by the information conveyance after sequence to client.
The step of classification and ordination is carried out to the information searched is increased on the basis of embodiment 1, during search
Directly information is screened and is classified, and is classified according to the daily focus of user, can better management information,
It allows user to directly contact the information of itself needs, and the information collected directly is combined with event, consequently facilitating
People hold the core content of information, and user is avoided to waste time and energy.
Embodiment 3
(1), the relevant information of user is checked first, and corresponding search interface is opened according to the information of user and carries out information
Inquiry, the relevant information for checking user include:
1., the identity of user and age；
2., the routine work of user；
3., the event of the daily concern of user and the time for browsing information；
4., user for itself search information privacy degrees；
User can be divided into three grades for the privacy degrees of itself search information；
I grade of user, do not announce it is all itself information and search record；
II grade of user does not announce the information of itself but announces the search record of itself；
III grade of user, announce it is all itself information and search record.
(2), user proposes the requirement of inquiry, big data analysis user's requirement, and extracts in user's requirement
The requirement of user is extracted 2-4 keyword by keyword；
It (3), will be in the keyword of user query and the historical query net and logout net of previous people's historical query
Information compares, and extracts the result of previous people's inquiry and requires the relevant information of relevant up-to-date event, history to user
The content of inquiry net is divided into personal record and all user records, and keyword is matched with the relevant information of historical query net
When, keyword is compared with personal record and other security requirements for the search information of second level and three-level user；
Information in keyword and historical query net and logout net carries out matched result, and there are three types of situations:
A, the record of keyword and historical query net exactly matches, and is directly ranked up all results；
B, keyword is matched with the record part of historical query net, is arranged after all information searched are combined
Sequence；
C, the record of keyword and historical query net mismatches, and all information inside big data is compared, and
It prompts user to search for the time required for information, then the information searched is ranked up.
(4), information is ranked up according to the clicking rate of the age bracket of user, the issuing time of information and information, is sorted
Preceding elder generation classifies to information according to the event of the daily concern of age bracket and user, by user's attention rate in the same age bracket
Higher information extracts, then is ranked up to the information of extraction, and the rule of sequence is issuing time and letter according to information
The clicking rate of breath, first three entitled clicking rate highest information when sequence, subsequent sequence differ 100,000 or more according to clicking rate
It sorts according to clicking rate, clicking rate differs less than 100,000 being successively ranked up according to issuing time.
(5), by the information conveyance after sequence to client, and the information searched is recorded and is input to and is gone through
In history inquiry net, the information in historical query net is updated；First the information of user's search is sorted out, typing user
In the record of the historical query net of people, then judge that the security classification of user, the security classification of user are II grade of user or III
Historical query net is directly updated when grade user, if the security classification of client is I grade of user, and keyword and historical query net
Record mismatch, will voluntarily the information searched be classified and be reintegrated, and to the interior bulk density after integration
It is new to formulate keyword, then the record of historical query net is updated again.
Expansion historical query net user information is put into how is or else invaded in the case that increasing on the basis of embodiment 2,
Suitably the relevant information of historical query net is integrated according to the privacy requirements of user itself, it is ensured that the peace of customer information
Quan Xing, and can the information inside historical query net constantly be classified and be expanded, so that the note of historical query net
It records more comprehensive and accurate, and extracts information convenient for next time, meet that modern people are comprehensive to information and safety is wanted
It asks, it is more practical.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the above embodiments and description only describe this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (8)
1. a kind of searching method based on big data, it is characterised in that: the following steps are included:
(1), the relevant information of user is checked first, and corresponding search interface progress information is opened according to the information of user and is looked into
It askes；
(2), user proposes the requirement of inquiry, big data analysis user's requirement, and extracts the key in user's requirement
Word；
(3), by the information in the keyword of user query and the historical query net and logout net of previous people's historical query
It compares, extract the result of previous people's inquiry and requires the relevant information of relevant up-to-date event to user；
(4), information is ranked up according to the clicking rate of the age bracket of user, the issuing time of information and information；
(5), by the information conveyance after sequence to client, and the information searched is recorded and is input to history and is looked into
It askes in net, the information in historical query net is updated.
2. a kind of searching method based on big data according to claim 1, it is characterised in that: in the step (1), core
Relevant information to user includes:
1., the identity of user and age；
2., the routine work of user；
3., the event of the daily concern of user and the time for browsing information；
4., user for itself search information privacy degrees.
3. a kind of searching method based on big data according to claim 2, it is characterised in that: the step 4. in, use
Family can be divided into three grades for the privacy degrees of itself search information；
I grade of user, do not announce it is all itself information and search record；
II grade of user does not announce the information of itself but announces the search record of itself；
III grade of user, announce it is all itself information and search record.
4. a kind of searching method based on big data according to claim 1, it is characterised in that:, will in the step (2)
2-4 keyword is extracted in the requirement of user.
5. a kind of searching method based on big data according to claim 1, it is characterised in that: in the step (3), go through
The content of history inquiry net is divided into personal record and all user records, and keyword is matched with the relevant information of historical query net
When, keyword is compared with personal record and other security requirements for the search information of second level and three-level user.
6. a kind of searching method based on big data according to claim 1, it is characterised in that: in the step (3), close
Information in keyword and historical query net and logout net carries out matched result, and there are three types of situations:
A, the record of keyword and historical query net exactly matches, and is directly ranked up all results；
B, keyword is matched with the record part of historical query net, is ranked up after all information searched are combined；
C, the record of keyword and historical query net mismatches, and all information inside big data is compared, and prompts
User searches for the time required for information, is then ranked up to the information searched.
7. a kind of searching method based on big data according to claim 1, which is characterized in that in the step (4), row
First classify according to the event of the daily concern of age bracket and user to information before sequence, user in the same age bracket is paid close attention to
Spend higher information to extract, then the information of extraction be ranked up, the rule of sequence be according to information issuing time and
The clicking rate of information, first three entitled clicking rate highest information when sequence, subsequent sequence is according to 100,000 or more clicking rate difference
Sort according to clicking rate, clicking rate differ less than 100,000 according to issuing time successively being ranked up.
8. a kind of searching method based on big data according to claim 1, which is characterized in that in the step (5), first
The information of user's search is sorted out, in the record of the historical query net of typing individual subscriber, then judges the secrecy of user
Grade directly updates historical query net, if the secrecy of client when the security classification of user is II grade of user or III grade of user
Grade is I grade of user, and the record of keyword and historical query net mismatches, and will voluntarily divide the information searched
It class and reintegrates, and keyword is reformulated to the content after integration, then the record of historical query net is carried out again
It updates.
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| CN201811519912.4A CN109634991B (en) | 2018-12-12 | 2018-12-12 | Searching method based on big data |
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| CN201811519912.4A CN109634991B (en) | 2018-12-12 | 2018-12-12 | Searching method based on big data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117688243A (en) * | 2023-12-19 | 2024-03-12 | 广州无限可能数字科技有限公司 | Keyword screening recommendation method and system based on big data |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103577489A (en) * | 2012-08-08 | 2014-02-12 | 百度在线网络技术（北京）有限公司 | Method and device of searching web browsing history |
| WO2015196907A1 (en) * | 2014-06-24 | 2015-12-30 | 北京奇虎科技有限公司 | Search pushing method and device which mine user requirements |
-
2018
- 2018-12-12 CN CN201811519912.4A patent/CN109634991B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103577489A (en) * | 2012-08-08 | 2014-02-12 | 百度在线网络技术（北京）有限公司 | Method and device of searching web browsing history |
| WO2015196907A1 (en) * | 2014-06-24 | 2015-12-30 | 北京奇虎科技有限公司 | Search pushing method and device which mine user requirements |
Non-Patent Citations (1)
| Title |
|---|
| 尤川川等: "一种基于大数据的有效搜索方法", 《计算机科学》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117688243A (en) * | 2023-12-19 | 2024-03-12 | 广州无限可能数字科技有限公司 | Keyword screening recommendation method and system based on big data |
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