CN111930899B - Keyword processing method and system and keyword searching method - Google Patents
Keyword processing method and system and keyword searching method Download PDFInfo
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- CN111930899B CN111930899B CN202011024683.6A CN202011024683A CN111930899B CN 111930899 B CN111930899 B CN 111930899B CN 202011024683 A CN202011024683 A CN 202011024683A CN 111930899 B CN111930899 B CN 111930899B
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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
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
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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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
- G06F16/2358—Change logging, detection, and notification
Abstract
The invention relates to a keyword processing method and system and a keyword searching method, which comprise the following steps: scanning the keywords in the keyword library according to the priority of the keywords, extracting parts from the scanned keywords and sending the parts to a message queue; the keywords in the keyword library are endowed with mark fields, and an updating state is formed; and sending the keywords in the message queue to a service end for searching to obtain a state result, and returning the state result to a keyword library so as to update the updating state of the keywords. The keyword searching method of the invention forms closed-loop updating of the keywords, realizes complete management and tracking of the keywords in the field of big data searching, avoids search omission and repeated searching, improves the utilization efficiency of data resources, reduces the operation load of a server, saves cost and improves economic benefits.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a keyword processing method and system and a keyword searching method.
Background
With the development of big data technology, the number of keywords is hundreds of millions, and related content can be updated regularly and quantitatively. Each enterprise unit can develop effective business requirements only when meeting a large number of keywords and ensuring that the big data collected by each enterprise unit is the latest data, and then the big data needs to be searched and collected in time.
Because the number of the keywords is very large, the traditional management scheme for the keywords has the problems of repeated searching, invalid searching and the like, and the problems of untimely searching and search omission can be caused, so that the searching or using efficiency of the keywords is reduced. Therefore, how to improve the search efficiency of the keywords is the focus of the present research. The research is funded by national key research and development plans, and the topic is numbered as follows: 2019YFC 0850103.
Disclosure of Invention
The invention aims to solve the problem of low search efficiency caused by repeated search and invalid search in the traditional scheme, and provides a keyword processing method and system and a keyword search method.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
a keyword processing method and system and a keyword searching method comprise the following steps:
scanning the keywords in the keyword library according to the mark fields of the keywords, extracting parts from the scanned keywords and sending the parts to a message queue; the keywords in the keyword library are endowed with mark fields, and an updating state is formed;
and sending the keywords in the message queue to a service end for searching to obtain a state result, and returning the state result to a keyword library so as to update the updating state of the keywords.
According to the scheme, the mark fields are given to the keywords to form the updating state of the keywords, so that a user can search and use the related contents of the keywords according to the mark fields conveniently in the later period; the keywords are scanned according to the mark fields of the keywords, for example, when the updating time in the mark fields is taken as the priority, the keywords can be scanned according to the sequence of the updating time, so that the problem of search omission is avoided when the keywords are scanned, the search efficiency can be improved, and other mark fields can be used as the priority to scan the keywords; after the keywords are searched, the obtained state results are returned to the keyword library for processing equivalent to the marking, repeated searching of the keywords can be avoided, closed-loop updating of the keywords is formed, complete management and tracking of the keywords in the field of big data searching are achieved, searching omission and repeated searching are avoided, utilization efficiency of data resources is improved, operation load of a server is reduced, cost is saved, and economic benefits are improved.
After the keywords in the keyword library are endowed with the mark fields, converting the keywords into structural data; the structural data comprises keyword field names, data types, descriptions and remarks; the formed updating state comprises the storage time, the updating time and the updating failure time of the key words.
According to the scheme, the mark fields given to the keywords and the formed updating state can provide convenience for subsequent users to search or use, the warehousing time, the updating time and the updating failure time in the updating state can also be used as a mark processing for the updating state of the keywords, and whether the keywords are searched or not can be known according to the updating state of the keywords, so that the keywords are not searched repeatedly.
Before the step of assigning a mark field to the keyword in the keyword library, the method further comprises the following steps: acquiring original data, preprocessing the acquired original data, filtering invalid data, and supplementing data of a missing field; and adding the preprocessed data serving as keywords into a keyword library.
The method is a step of establishing a keyword library, and the keywords in the library are preprocessed, so that invalid data are prevented from being searched, and the searching cost is reduced.
The step of sending the keywords in the message queue to the service end for searching to obtain the state result comprises the following steps:
searching the keywords in the message queue at a service end according to the mark fields of the keywords to obtain a normal state search result, an abnormal state search result and an overtime unreturned state result; the search normal state result comprises that the content of the keywords is updated or not updated.
The step of returning the state result to the keyword library to update the update state of the keyword comprises the following steps:
if the state result is that the search is normal, updating the updating state of the keyword in the keyword library, including the updating time of the keyword;
if the state result is abnormal, returning the abnormal state result to the keyword library for abnormal investigation, and updating the updating state of the keyword in the keyword library, including the updating failure time of the keyword;
if the state result is overtime unreturned, the priority of the keywords of the state result which is overtime unreturned is improved, the keywords are searched again, if the state result is still overtime unreturned, the state result is returned to the keyword library for exception checking, the updating state of the keywords in the keyword library is updated, the updating failure time of the keywords is included, and the keywords are not searched any more.
A keyword search method, comprising:
and searching the keywords in the message queue at the service end according to the mark fields of the keywords to obtain a normal state result, an abnormal state result and an overtime unreturned state result, and returning the state result to the keyword library.
A keyword processing system, comprising:
the keyword library is used for storing the keywords, and the mark fields and the updating states corresponding to the keywords;
the word bank server is used for endowing a mark field to the keywords in the keyword bank, forming an updating state of the keywords, scanning the keywords in the keyword bank according to the mark field of the keywords, extracting a part from the scanned keywords and sending the part to the message queue;
the message queue is used for storing keywords scanned by the word stock server;
and the service end is used for searching the keywords in the message list and returning the obtained state result to the keyword library so as to update the updating state of the keywords.
The word stock server is used for endowing a mark field to the keyword and converting the keyword into structural data, wherein the structural data comprises a keyword field name, a data type, a description and a remark; and the formed updating state comprises the storage time, the updating time and the updating failure time of the key words.
The system also comprises a keyword preprocessing module, a keyword library and a database, wherein the keyword preprocessing module is used for acquiring original data, preprocessing the acquired original data and adding the preprocessed original data into the keyword library as a keyword; the preprocessing includes filtering invalid data, supplementing data of missing fields.
The state result obtained after the service terminal searches the keywords in the message list according to the mark fields of the keywords comprises: searching for normal state results, searching for abnormal state results and state results which are not returned after time-out, wherein the normal state results comprise that the content of the key words is updated or the content of the key words is not updated.
If the state result is normal after the business end searches the keyword, returning the state result which is normal to the search to a keyword library, and updating the updating state of the keyword by a word library server, wherein the updating state comprises the updating time of the keyword;
if the state result is abnormal after the business end searches the keyword, returning the abnormal state result to the keyword library, and performing abnormal investigation on the state result of the keyword by the word library server and updating the update state of the keyword, wherein the updated update state comprises the update failure time of the keyword;
if the state result is the overtime unreturned state result after the business side searches the keyword, the overtime unreturned state result is returned to the keyword library, the word library server improves the priority of the keyword, the business side searches the keyword again, if the overtime unreturned state result is still the overtime unreturned state result, the word library server conducts abnormal investigation on the state result of the keyword, the updating state of the keyword in the keyword library is updated, the updating state of the updating comprises the updating failure time of the keyword, and the keyword is not sent to the business side for searching.
Compared with the prior art, the invention has the beneficial effects that:
the keyword searching method of the invention forms closed-loop updating of the keywords, realizes complete management and tracking of the keywords in the field of big data searching, avoids search omission and repeated searching, improves the utilization efficiency of data resources, reduces the operation load of a server, saves cost and improves economic benefits.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flowchart of a method for improving keyword search efficiency according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The invention is realized by the following technical scheme, as shown in figure 1, a keyword processing method comprises the following steps:
step S1: and giving a mark field to the keywords in the keyword library, and forming the updating state of the keywords.
Firstly, acquiring a large amount of original data, and preprocessing the acquired original data, wherein the preprocessing comprises filtering invalid data, supplementing data of missing fields and the like. For example, the raw data obtained now is shown in table 1:
| company a, 91420 × FJJ90L |
| B Ltd, Hubei, 9142112 |
| C ltd, hubei, 91422 × FJ3Q8Q |
| Zhang three |
TABLE 1
As can be seen from the raw data obtained in Table 1, the first piece of data is missing home, the second piece of data has an error in the organization code, and the fourth piece of data is invalid. Therefore, the acquired raw data is preprocessed, and the preprocessed data is shown in table 2:
| company limited, hubei, 91420 FJJ90L |
| B company, limited, north of lake, |
| c ltd, hubei, 91422 × FJ3Q8Q |
TABLE 2
Preprocessing a large amount of original data, adding the preprocessed data serving as a large amount of keywords into a keyword library, giving a mark field to the keywords, and converting the keywords into structural data. For example, when a keyword having a company name "D labor company, llc" is assigned a tag field, the structural data shown in table 3 is formed:
| name of field | Data of Type (B) | Description of the invention | Remarks for note |
| region_code | integ er | Region codes, such as: 540102 | Distinguish provinces |
| enterprise_ status | byte | Registration status, such as: 1 (storage continuing) | Distinguishing registration status |
| enterprise_ type | short | Types of businesses, such as: 1130 (Limited accountability) Company) | Is distinguished and has type |
| company_name | text | Company names, such as: d limited liability of labor Driver | |
| company_ creditcode | keywo rd | Unifying social credit codes, such as: 91540*******F6CJ4J | |
| company_regno | keywo rd | registration numbers, such as: 542*****00322 | |
| _id | text | Unique ID, tag key uniqueness | |
| enabled | boole an | The keyword uses a flag. True- False: activation/deactivation | |
| seed_from | byte | A source of the keyword. Such as: 9 (CC spreading) | Differentiating sources of keywords |
| seed_crawler | join | Document type | The parent-child document relationship is a one-to-many relationship. One keyword can be divided into a plurality of crawlers In use, multiple subdocuments may therefore be owned. |
| crawler_id | keywo rd | Crawler ID, such as: qyxx _ data __ sichuan | Crawler unique ID, bbd _ table __ bbd _ type |
| create_time | date | Crawler and keyword associated time | |
| lastest_ inqueue_time | date | Keyword fill time | |
| lastest_ update_time | date | Keyword corresponding information update time | |
| lastest_nc_ time | date | Keyword non-search knotFruit time | |
| latest_ dpfail_time | date | Cleaning and losing data corresponding to keywords Time of failure |
TABLE 3
The update state of the keyword can be further formed according to the formed structure data, for example, the update state of the keyword can include the warehousing time (keyword filling time), the update time (keyword corresponding information update time), and the update failure time (keyword no search result time) of the keyword. The user can search or use the content of the keyword according to the marked field or the updated state of the keyword.
Step S2: and scanning the keywords in the keyword library according to the mark fields of the keywords, extracting parts from the scanned keywords and sending the parts to a message queue.
Because the number of the keywords in the keyword library is very large, the service end cannot complete the search of all the keywords at one time, so that the priorities can be set for the keywords, the search can be performed according to the priorities of the keywords, a certain marked field of the keywords can be used as the priority, for example, when the updating time is used as the priority, all the keywords can be scanned in sequence according to the updating time of the keywords, and the keywords cannot be missed.
Assuming that ten thousand keywords can be scanned at a time according to the priority of the keywords, the number of the ten thousand keywords is still huge, and therefore, parts of the scanned ten thousand keywords are extracted and sent to the message queue. The message queue is a functional module belonging to a service end, and because the capacity of the message queue is limited, keywords in a capacity range can be extracted according to setting and then put into the message queue for subsequent searching.
Step S3: and sending the keywords in the message queue to a service end for searching to obtain a state result, and returning the state result to a keyword library so as to update the updating state of the keywords.
And searching the keywords in the message queue at the service end sequentially or simultaneously according to the mark field priority of the keywords, for example, searching by taking the organization code as the priority, and if the mark field is missing, searching on websites such as encyclopedia or industrial and commercial administrative network by using the company name. The purpose of the search is to know whether the information of the keyword in the keyword library is up-to-date after the search, and to mark an updated keyword, where the mark is an update state of the keyword, such as an update time of the keyword.
After the keyword is searched, three state results of normal search, abnormal search and no return after overtime exist, wherein the state result of normal search is a result returned from the website by the keyword, and whether the result is updated or not is judged whether the result is compared with the historical result or not. For example, when the name of an enterprise a is used as a keyword to perform a search, the service end obtains a search result, the thesaurus server obtains the feedback and then correspondingly updates the update state of the keyword, for example, when the search for the keyword occurs at 21 o ' clock 15 o ' clock 21 o ' clock 6/21/2020, the update time of the keyword is changed to 21 o ' clock 15 o ' clock 21 o ' clock 6/21 o ' clock 2020, so as to mark the updated keyword.
However, when all keywords are searched, corresponding content of the keyword cannot be returned, for example, when a returned result is "error", the result is a state result of abnormal search, and no corresponding content is obtained. At this time, the abnormal state result of the search needs to be returned to the keyword for abnormal investigation, and the updated state of the keyword in the keyword library is updated, for example, when the current search occurs at 16 o 'clock 8/21/2020, the update failure time of the keyword is recorded as 16 o' clock 40 o 'clock 16 o' clock 8/21/2020, so as to achieve the purpose of marking the updated keyword with one mark.
If the searched state result is overtime and is not returned, the priority of the keyword is improved, the keyword is searched again, if the state result is still overtime and is not returned, the keyword is returned to the keyword library for exception checking, the updating state of the keyword in the keyword library is updated, the updating failure time of the keyword is included, and the keyword is not searched any more.
The scheme does not specifically limit and protect what abnormal investigation is carried out on the keywords of which the state results are abnormal searches, and different abnormal investigation modes can be carried out according to the technology of each user.
Based on the processing method, the scheme also provides a keyword searching method, which comprises the following steps: and searching the keywords in the message queue at the service end according to the mark fields of the keywords to obtain a normal state search result, an abnormal state search result and a state overtime unreturned result, wherein the normal state search result comprises the condition that the contents of the keywords are updated or not updated, and returning the state result to a keyword library.
Based on the processing and searching method, the scheme also provides a keyword processing system, which comprises the following steps:
the crawling module is used for acquiring original data, preprocessing the acquired original data and adding the preprocessed original data serving as keywords into a keyword library; the preprocessing comprises filtering invalid data and supplementing data of a missing field;
the keyword library is used for storing the keywords, and the mark fields and the updating states corresponding to the keywords;
the word bank server is used for endowing a mark field to the keywords in the keyword bank, forming an updating state of the keywords, scanning the keywords in the keyword bank according to the mark field of the keywords, extracting a part from the scanned keywords and sending the part to the message queue;
the message queue is used for storing keywords scanned by the word stock server;
and the service end is used for searching the keywords in the message list and returning the obtained state result to the keyword library so as to update the updating state of the keywords.
Furthermore, the word stock server is used for endowing a mark field for the keyword, and converting the keyword into structural data, wherein the structural data comprises a keyword field name, a data type, a description and a remark; and the formed updating state comprises the storage time, the updating time and the updating failure time of the key words.
The state result obtained after the service terminal searches the keywords in the message list according to the mark fields of the keywords comprises: searching for normal state results, searching for abnormal state results and state results which are not returned after time-out, wherein the normal state results comprise that the content of the key words is updated or the content of the key words is not updated.
If the state result is normal after the business end searches the keyword, returning the state result which is normal to the search to a keyword library, and updating the updating state of the keyword by a word library server, wherein the updating state comprises the updating time of the keyword;
if the state result is abnormal after the business end searches the keyword, returning the abnormal state result to the keyword library, and performing abnormal investigation on the state result of the keyword by the word library server and updating the update state of the keyword, wherein the updated update state comprises the update failure time of the keyword;
if the state result is the overtime unreturned state result after the business side searches the keyword, the overtime unreturned state result is returned to the keyword library, the word library server improves the priority of the keyword, the business side searches the keyword again, if the overtime unreturned state result is still the overtime unreturned state result, the word library server conducts abnormal investigation on the state result of the keyword, the updating state of the keyword in the keyword library is updated, the updating state of the updating comprises the updating failure time of the keyword, and the keyword is not sent to the business side for searching.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A keyword processing method is characterized in that: the method comprises the following steps:
scanning the keywords in the keyword library according to the mark fields of the keywords, extracting parts from the scanned keywords and sending the parts to a message queue; the keywords in the keyword library are endowed with mark fields, and an updating state is formed; the formed updating state comprises the storage time, the updating time and the updating failure time of the key words;
sending the keywords in the message queue to a service end for searching to obtain a state result, and returning the state result to a keyword library to update the updating state of the keywords;
the step of sending the keywords in the message queue to the service end for searching to obtain the state result comprises the following steps:
searching the keywords in the message queue at a service end according to the mark fields of the keywords to obtain a normal state search result, an abnormal state search result and an overtime unreturned state result; the search normal state result comprises that the content of the keyword is updated or not updated;
the step of returning the state result to the keyword library to update the update state of the keyword comprises the following steps:
if the state result is that the search is normal, updating the updating state of the keyword in the keyword library, including the updating time of the keyword;
if the state result is abnormal, returning the abnormal state result to the keyword library for abnormal investigation, and updating the updating state of the keyword in the keyword library, including the updating failure time of the keyword;
if the state result is overtime unreturned, the priority of the keywords of the state result which is overtime unreturned is improved, the keywords are searched again, if the state result is still overtime unreturned, the state result is returned to the keyword library for exception checking, the updating state of the keywords in the keyword library is updated, the updating failure time of the keywords is included, and the keywords are not searched any more.
2. A keyword processing method according to claim 1, characterized in that: after the keywords in the keyword library are endowed with the mark fields, converting the keywords into structural data; the structural data comprises keyword field names, data types, descriptions and remarks.
3. A keyword processing method according to claim 1, characterized in that: before the step of assigning a mark field to the keyword in the keyword library, the method further comprises the following steps: acquiring original data, preprocessing the acquired original data, filtering invalid data, and supplementing data of a missing field; and adding the preprocessed data serving as keywords into a keyword library.
4. A keyword processing system, characterized by: the method comprises the following steps:
the keyword library is used for storing the keywords, and the mark fields and the updating states corresponding to the keywords; the formed updating state comprises the storage time, the updating time and the updating failure time of the key words;
the word bank server is used for endowing a mark field to the keywords in the keyword bank, forming an updating state of the keywords, scanning the keywords in the keyword bank according to the mark field of the keywords, extracting a part from the scanned keywords and sending the part to the message queue;
the message queue is used for storing keywords scanned by the word stock server;
the service end is used for searching the keywords in the message list and returning the obtained state result to the keyword library so as to update the updating state of the keywords;
the state result obtained after the service terminal searches the keywords in the message list according to the mark fields of the keywords comprises: searching a normal state result, an abnormal state result and a state result which is not returned after overtime, wherein the normal state result comprises that the content of the key words is updated or the content of the key words is not updated;
if the state result is normal after the business end searches the keyword, returning the state result which is normal to the search to a keyword library, and updating the updating state of the keyword by a word library server, wherein the updating state comprises the updating time of the keyword;
if the state result is abnormal after the business end searches the keyword, returning the abnormal state result to the keyword library, and performing abnormal investigation on the state result of the keyword by the word library server and updating the update state of the keyword, wherein the updated update state comprises the update failure time of the keyword;
if the state result is the overtime unreturned state result after the business side searches the keyword, the overtime unreturned state result is returned to the keyword library, the word library server improves the priority of the keyword, the business side searches the keyword again, if the overtime unreturned state result is still the overtime unreturned state result, the word library server conducts abnormal investigation on the state result of the keyword, the updating state of the keyword in the keyword library is updated, the updating state of the updating comprises the updating failure time of the keyword, and the keyword is not sent to the business side for searching.
5. A keyword processing system according to claim 4, characterized in that: the word stock server is used for endowing the key words with mark fields and converting the key words into structural data, wherein the structural data comprises key word field names, data types, descriptions and remarks.
6. A keyword processing system according to claim 5, wherein: the system also comprises a crawling module, a keyword library and a searching module, wherein the crawling module is used for acquiring original data, preprocessing the acquired original data and adding the preprocessed original data into the keyword library as keywords; the preprocessing includes filtering invalid data, supplementing data of missing fields.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1498379A (en) * | 2001-03-21 | 2004-05-19 | 因特国风网络软件有限公司 | System and method of personal and business web cards |
| CN101192221A (en) * | 2006-11-27 | 2008-06-04 | 北京三星通信技术研究有限公司 | Yellow page retrieving method and yellow page system |
| CN103064852A (en) * | 2011-10-20 | 2013-04-24 | 阿里巴巴集团控股有限公司 | Website statistical information processing method and website statistical information processing system |
| CN103841123A (en) * | 2012-11-20 | 2014-06-04 | 中国电信股份有限公司 | Number information obtaining method and obtaining system, and cloud number information system |
| CN106021439A (en) * | 2016-05-16 | 2016-10-12 | 腾讯科技（深圳）有限公司 | Communication number processing method and device |
| CN106708821A (en) * | 2015-07-21 | 2017-05-24 | 广州市本真网络科技有限公司 | User personalized shopping behavior-based commodity recommendation method |
| CN107657057A (en) * | 2017-10-19 | 2018-02-02 | 河北省科学院应用数学研究所 | A kind of enterprise's reference information fusion graphic method |
| CN108062326A (en) * | 2016-11-08 | 2018-05-22 | 北京国双科技有限公司 | A kind of update recording method of data message and device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101853308A (en) * | 2010-06-11 | 2010-10-06 | 中兴通讯股份有限公司 | Method and application terminal for personalized meta-search |
| CN107463616B (en) * | 2017-07-03 | 2020-04-10 | 上海凡响网络科技有限公司 | Enterprise information analysis method and system |
| CN107609921A (en) * | 2017-09-30 | 2018-01-19 | 金蝶软件（中国）有限公司 | A kind of data processing method and server |
-
2020
- 2020-09-25 CN CN202011024683.6A patent/CN111930899B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1498379A (en) * | 2001-03-21 | 2004-05-19 | 因特国风网络软件有限公司 | System and method of personal and business web cards |
| CN101192221A (en) * | 2006-11-27 | 2008-06-04 | 北京三星通信技术研究有限公司 | Yellow page retrieving method and yellow page system |
| CN103064852A (en) * | 2011-10-20 | 2013-04-24 | 阿里巴巴集团控股有限公司 | Website statistical information processing method and website statistical information processing system |
| CN103841123A (en) * | 2012-11-20 | 2014-06-04 | 中国电信股份有限公司 | Number information obtaining method and obtaining system, and cloud number information system |
| CN106708821A (en) * | 2015-07-21 | 2017-05-24 | 广州市本真网络科技有限公司 | User personalized shopping behavior-based commodity recommendation method |
| CN106021439A (en) * | 2016-05-16 | 2016-10-12 | 腾讯科技（深圳）有限公司 | Communication number processing method and device |
| CN108062326A (en) * | 2016-11-08 | 2018-05-22 | 北京国双科技有限公司 | A kind of update recording method of data message and device |
| CN107657057A (en) * | 2017-10-19 | 2018-02-02 | 河北省科学院应用数学研究所 | A kind of enterprise's reference information fusion graphic method |
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