CN109634991B - Searching method based on big data - Google Patents
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- CN109634991B CN109634991B CN201811519912.4A CN201811519912A CN109634991B CN 109634991 B CN109634991 B CN 109634991B CN 201811519912 A CN201811519912 A CN 201811519912A CN 109634991 B CN109634991 B CN 109634991B
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Abstract
The invention discloses a searching method based on big data, which comprises the following steps: firstly, checking relevant information of a user, and opening a corresponding search interface according to the information of the user to perform information query; the user puts forward the query requirement, the big data analyzes the requirement put forward by the user, and the key words in the user requirement are extracted; the keywords inquired by the user are compared with the information in the historical inquiry network and the event record network which are inquired by people historically. According to the searching method based on the big data, firstly, new information and information searched by people in the past are combined with each other, so that the information mastered by people can be more comprehensive, secondly, the collected information is directly combined with events, and the analysis by people is facilitated, so that people can master the core content of the information conveniently, finally, the safety degree of user information can be improved, meanwhile, the information resources are expanded, the information is conveniently searched by people next time, and a better use prospect is brought.
Description
Technical Field
The invention relates to the field of search methods, in particular to a search method based on big data.
Background
With the lapse of time, people enter an information-based society, people pay more and more attention to information, and the requirements on comprehensiveness and rapidness of various information are higher and higher, so that people invent a search method based on big data, but with the development of science and technology and the progress of times, the requirements of people on the search method based on big data are higher and higher, so that the traditional search method based on big data cannot meet the use requirements of people;
the existing searching method based on big data has certain disadvantages when in use, firstly, the existing searching method based on big data only compares with the existing searching records of people, directly reads the contents searched by people before, can cause the latest information to be incapable of being read in a short time, and does not meet the requirements of modern people, and the network is continuously developed, and the information is continuously accumulated.
Disclosure of Invention
The invention mainly aims to provide a searching method based on big data, which can effectively solve the problems in the background technology.
In order to achieve the purpose, the invention adopts the technical scheme that:
a big data-based searching method comprises the following steps:
(1) Firstly, checking relevant information of a user, and opening a corresponding search interface according to the information of the user to perform information query;
(2) The user puts forward a query requirement, the big data analyzes the requirement put forward by the user, and key words in the user requirement are extracted;
(3) Comparing the keywords inquired by the user with the information in the historical inquiry network and the event record network which are inquired by people historically, and extracting the result inquired by people and the related information of the latest event related to the user requirement;
(4) Sorting the information according to the age bracket of the user, the information release time and the information click rate;
(5) And the sorted information is transmitted to the client, the searched information is recorded and input into the historical query network, and the information in the historical query network is updated.
Preferably, in the step (1), the checking the relevant information of the user includes:
(1) identity and age of the user;
(2) daily work of the user;
(3) events of daily interest of the user and the time of browsing information;
(4) and the confidentiality degree of the user for the self-searching information.
Preferably, in the step (4), the user's privacy level for the self-search information can be divided into three levels;
the I-level user unfairly distributes all self information and search records;
the level II user does not publish own information but publishes own search record;
and the III-level user publishes all self information and search records.
Preferably, in the step (2), 2 to 4 keywords are extracted according to the requirement of the user.
Preferably, in the step (3), the content of the historical query web is divided into personal records and all user records, and when the keywords are matched with the related information of the historical query web, the keywords are compared with the personal records and the search information of other users with the security requirements of the second level and the third level.
Preferably, in the step (3), the result of matching the keyword with the information in the historical query network and the event logging network has three conditions:
a. the keywords are completely matched with the records of the historical query network, and all results are directly sorted;
b. matching the keywords with the recorded part of the historical query network, combining all searched information and then sequencing;
c. and the keywords are not matched with the records of the historical query network, all information in the big data is compared, the time required by the user for searching the information is prompted, and then the searched information is sequenced.
Preferably, in the step (4), before sorting, the information is classified according to the age groups and the daily events concerned by the users, the information with higher user concern in the same age group is extracted, then the extracted information is sorted, the sorting rule is that the first three information with the highest click rate are sorted according to the information release time and the click rate of the information, the later sorting is sorted according to the click rate with the difference of more than one hundred thousand, and the sorting is carried out according to the order of the release time with the difference of less than one hundred thousand.
Preferably, in the step (5), the information searched by the user is classified first, the information is recorded into the personal records of the historical query network of the user, then the privacy level of the user is judged, the historical query network is directly updated when the privacy level of the user is a level II user or a level III user, if the privacy level of the user is a level I user and the keyword is not matched with the records of the historical query network, the searched information is automatically classified and reintegrated, the keyword is reformulated for the integrated content, and then the records of the historical query network are updated.
Compared with the prior art, the invention has the following beneficial effects:
1. the requirements of users are compared with the historical query network and the event record network together and then integrated, the historical query network records the prior information, the event record network comprises various newly-occurring major events and peripheral information of the events, the attention of the events is high, the prior information and the latest events are combined with each other, and therefore the information mastered by people is more comprehensive;
2. the information is directly screened and classified in the searching process, and the information is classified according to the daily attention points of the user, so that the information can be better managed, the user can directly contact the information required by the user, and the collected information is directly combined with the event, so that the core content of the information can be conveniently mastered by people, and the waste of time and energy of the user is avoided;
3. the method has the advantages that the relevant information of the historical query network is properly integrated according to the confidential requirements of the user, the safety of the client information can be guaranteed, the information in the historical query network can be continuously classified and expanded, the record of the historical query network is more comprehensive and accurate, the information can be conveniently extracted next time, the requirements of modern people on the comprehensiveness and safety of the information are met, and the method is practical.
Drawings
Fig. 1 is a flowchart of an overall structure of a search method based on big data according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Example 1
(1) Firstly, checking the relevant information of the user, opening a corresponding search interface according to the information of the user for information query, wherein the checking of the relevant information of the user comprises the following steps:
(1) identity and age of the user;
(2) daily work of the user;
(3) events of daily interest of the user and the time of browsing information;
(4) the confidentiality degree of the user for the self-searched information;
the confidentiality degree of the user for the self-searched information can be divided into three levels;
the I-level user unfairly distributes all self information and search records;
the level II user does not publish own information but publishes own search record;
and the level III user publishes all self information and search records.
(2) The user puts forward a query requirement, the big data analyzes the requirement put forward by the user, extracts key words in the user requirement, and extracts 2-4 key words from the user requirement;
(3) Comparing the keywords inquired by the user with information in a historical inquiry network and an event record network which are inquired by people historically, extracting the inquired results of people and the related information of the latest event related to the user requirement, wherein the content of the historical inquiry network is divided into personal records and all user records, and when the keywords are matched with the related information of the historical inquiry network, the keywords are compared with the personal records and other search information of users with the security requirements of second level and third level;
the result of matching the keywords with the information in the historical query network and the event logging network has three conditions:
a. the keywords are completely matched with the records of the historical query network, and all results are directly sent to the user;
b. matching the keywords with the recorded part of the historical query network, combining all searched information and sending the combined information to the user;
c. and the keyword is not matched with the record of the historical query network, all information in the big data is compared, the time required by the user for searching the information is prompted, and the searched information is sent to the user.
The method comprises the steps of comparing the requirements of users with a history inquiry network and an event recording network together and then integrating the requirements, wherein the history inquiry network records past information, the event recording network comprises various newly-occurring major events and peripheral information of the events, the attention degree of the events is high, the past information and the latest events are combined with each other, and therefore the information mastered by people is more comprehensive.
Example 2
(1) Firstly, checking the relevant information of the user, opening a corresponding search interface according to the information of the user for information query, wherein the checking of the relevant information of the user comprises the following steps:
(1) identity and age of the user;
(2) daily work of the user;
(3) events of daily interest of the user and the time of browsing information;
(4) the confidentiality degree of the user for the self-searched information;
the confidentiality degree of the user for the self-searched information can be divided into three levels;
the I-level user unfairly distributes all self information and search records;
the level II user does not publish own information but publishes own search record;
and the level III user publishes all self information and search records.
(2) The user puts forward a query requirement, the big data analyzes the requirement put forward by the user, extracts key words in the user requirement, and extracts 2-4 key words from the user requirement;
(3) Comparing the keywords inquired by the user with information in a historical inquiry network and an event record network which are inquired by people historically, extracting the inquired results of people and the related information of the latest event related to the user requirement, wherein the content of the historical inquiry network is divided into personal records and all user records, and when the keywords are matched with the related information of the historical inquiry network, the keywords are compared with the personal records and other search information of users with the security requirements of second level and third level;
the result of matching the keywords with the information in the historical query network and the event logging network has three conditions:
a. the keywords are completely matched with the records of the historical query network, and all results are directly sorted;
b. matching the keywords with the recorded part of the historical query network, combining all searched information and then sequencing;
c. the keywords are not matched with records of a historical query network, all information in the big data is compared, a user is prompted about the time required for searching the information, and then the searched information is sequenced;
(4) The information is sorted according to the age group of the user, the information release time and the information click rate, the information is classified according to the age group and daily attention events of the user before sorting, the information with higher user attention in the same age group is extracted, the extracted information is sorted, the sorting rule is that the information is sorted according to the information release time and the information click rate, the first three information are sorted according to the information with the highest click rate, the later information is sorted according to the click rate with the difference of more than one hundred thousand, and the information is sorted according to the order of the release time with the difference of less than one hundred thousand.
(5) And transmitting the sorted information to the client.
The step of sorting the searched information is added on the basis of the embodiment 1, the information is directly screened and classified in the searching process, the information is classified according to the daily attention points of the user, the information can be better managed, the user can directly contact the information needed by the user, and the collected information is directly combined with the event, so that the core content of the information can be conveniently mastered by the user, and the waste of time and energy of the user is avoided.
Example 3
(1) Firstly, relevant information of a user is checked, a corresponding search interface is opened according to the information of the user for information query, and the checking of the relevant information of the user comprises the following steps:
(1) identity and age of the user;
(2) daily work of the user;
(3) events of daily interest of the user and time of browsing information;
(4) the confidentiality degree of the user for the self-searched information;
the confidentiality degree of the user for the self-searched information can be divided into three levels;
the I-level user unfairly distributes all self information and search records;
the level II user does not publish own information but publishes own search record;
and the III-level user publishes all self information and search records.
(2) The user puts forward a query requirement, the big data analyzes the requirement put forward by the user, extracts key words in the user requirement, and extracts 2-4 key words from the user requirement;
(3) Comparing the keywords inquired by the user with information in a historical inquiry network and an event record network which are inquired by people historically, extracting the inquired results of people and the related information of the latest event related to the user requirement, wherein the content of the historical inquiry network is divided into personal records and all user records, and when the keywords are matched with the related information of the historical inquiry network, the keywords are compared with the personal records and other search information of users with the security requirements of second level and third level;
the result of matching the keywords with the information in the historical query network and the event logging network has three conditions:
a. the keywords are completely matched with the records of the historical query network, and all results are directly sorted;
b. matching the keywords with the recorded part of the historical query network, combining all searched information and then sequencing;
c. and comparing all the information in the big data when the keyword is not matched with the record of the historical query network, prompting the user of the time required for searching the information, and sequencing the searched information.
(4) The information is sorted according to the age group of the user, the information release time and the information click rate, the information is classified according to the age group and daily concerned events of the user before sorting, the information with high user attention in the same age group is extracted, then the extracted information is sorted, the sorting rule is that the information is released according to the information and the information click rate, the first three information are the information with the highest click rate during sorting, the later information is sorted according to the click rate with the difference of more than one hundred thousand according to the click rate, and the information is sorted according to the order of the release time with the difference of less than one hundred thousand according to the click rate with the difference of less than one hundred thousand.
(5) The sorted information is transmitted to a client, the searched information is recorded and input into a historical query network, and the information in the historical query network is updated; classifying information searched by a user, inputting the information into records of a personal historical query network of the user, then judging the privacy level of the user, directly updating the historical query network when the privacy level of the user is a level II user or a level III user, automatically classifying and re-integrating the searched information if the privacy level of the user is a level I user and the keyword is not matched with the records of the historical query network, re-formulating the keyword for the integrated content, and then updating the records of the historical query network.
How to expand the historical query network under the condition of putting user information into the historical query network is increased on the basis of the embodiment 2, relevant information of the historical query network is properly integrated according to the confidential requirements of the user, the safety of the customer information can be ensured, and the information in the historical query network can be continuously classified and expanded, so that the record of the historical query network is more comprehensive and accurate, the information can be conveniently extracted next time, the requirements of modern people on the comprehensiveness and safety of the information are met, and the method is practical.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A search method based on big data is characterized in that: the method comprises the following steps:
(1) Firstly, checking relevant information of a user, and opening a corresponding search interface according to the information of the user to perform information query;
the checking of the relevant information of the user includes:
(1) identity and age of the user;
(2) daily work of the user;
(3) events of daily interest of the user and the time of browsing information;
(4) the confidentiality degree of the user for the self-searched information;
(2) The user puts forward a query requirement, the big data analyzes the requirement put forward by the user, and key words in the user requirement are extracted;
(3) Comparing the keywords inquired by the user with the information in the historical inquiry network and the event record network which are inquired by people historically, and extracting the result inquired by people and the related information of the latest event related to the user requirement;
the content of the historical query network is divided into personal records and all user records, and when the keywords are matched with the related information of the historical query network, the keywords are compared with the personal records and other search information of the second-level user and the third-level user with security requirements;
(4) Sorting the information according to the age bracket of the user, the information release time and the information click rate;
(5) And the sorted information is transmitted to the client, the searched information is recorded and input into the historical query network, and the information in the historical query network is updated.
2. The big data-based search method according to claim 1, wherein: in the step (4), the secrecy degree of the user for the self-searched information can be divided into three grades;
the I-level user unfairly distributes all self information and search records;
the level II user does not publish own information but publishes own search record;
and the level III user publishes all self information and search records.
3. The big data-based search method according to claim 1, wherein: in the step (2), 2-4 keywords are extracted according to the requirements of the user.
4. The big data based searching method according to claim 1, wherein: in the step (3), the result of matching the keywords with the information in the historical query network and the event logging network has three conditions:
a. the keywords are completely matched with the records of the historical query network, and all results are directly sorted;
b. matching the keywords with the recorded part of the historical query network, combining all searched information and then sequencing;
c. and comparing all the information in the big data when the keyword is not matched with the record of the historical query network, prompting the user of the time required for searching the information, and sequencing the searched information.
5. The big data-based search method according to claim 1, wherein in the step (4), before sorting, the information is classified according to the age group and the daily events of interest of the user, the information with higher user interest in the same age group is extracted, and then the extracted information is sorted, the sorting rule is that the first three information with the highest click rate are sorted according to the information release time and the click rate of the information, the later sorting is sorted according to the click rate with a difference of more than one hundred thousand, and the sorting is performed according to the order of the release time with a difference of less than one hundred thousand.
6. The big data-based searching method according to claim 1, wherein in the step (5), the information searched by the user is classified and recorded in the personal history query network record of the user, then the privacy level of the user is judged, the history query network is directly updated when the privacy level of the user is a level II user or a level III user, if the privacy level of the user is a level I user and the keyword is not matched with the history query network record, the searched information is classified and re-integrated, the keyword is re-formulated for the integrated content, and then the history query network record is updated.
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| 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 |
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| 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 |
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| Title |
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| 一种基于大数据的有效搜索方法;尤川川等;《计算机科学》;20130615(第06期);全文 * |
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