CN114491211B - Service providing method based on internet big data - Google Patents
Service providing method based on internet big data Download PDFInfo
- Publication number
- CN114491211B CN114491211B CN202210340004.9A CN202210340004A CN114491211B CN 114491211 B CN114491211 B CN 114491211B CN 202210340004 A CN202210340004 A CN 202210340004A CN 114491211 B CN114491211 B CN 114491211B
- Authority
- CN
- China
- Prior art keywords
- information
- delta
- feedback information
- query
- databases
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- 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
- G06F16/31—Indexing; Data structures therefor; Storage structures
- G06F16/316—Indexing structures
-
- 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
- G06F16/3344—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
Abstract
The invention relates to a service providing method based on internet big data, which comprises the following steps: receiving query information of a user; extracting keywords of the query information, and searching query contents matched with the keywords in a plurality of associated databases based on the keywords; quantitatively screening the inquired content, and selecting the content with the correlation degree higher than the preset correlation degree with the keyword as information to be fed back, wherein the information to be fed back is generated based on the inquired information; acquiring current configuration information of a user, and performing secondary extraction of information from the filtered content according to the configuration information to form secondary feedback information; and after information fusion is carried out on the information to be fed back and the secondary feedback information, an output list is formed, and the information in the output list is sent to a user. The selection of the user based on the output list is improved, the information conversion capability based on the query information of the user is completed, and the conversion efficiency is improved.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a service providing method based on internet big data.
Background
With the development of the internet and information technology, the way in which users acquire information has changed greatly. The information quantity on the internet is increased explosively, and a user has certain difficulty in acquiring information from massive information, so that the information push service is developed at the right moment. The information push can directly push the information required by the user to the hands of the user, and the information overload is relieved. The internet has been developed in different stages, and the method and mode of information push service have changed.
Patent document No. CN111708931A discloses a big data collection method based on mobile internet, which is to perform data processing in a data collection phase based on request information of a user in a push service process provided for the user, and the specific implementation scheme is as follows: after page user behavior information corresponding to an extended page object needing big data acquisition is obtained from an internet access process, determining internet function service information matched with the page user behavior information; generating corresponding data acquisition identification node information according to the internet function service information and the theme zone information corresponding to the internet function service information; associating the data acquisition identification node information to a data acquisition script of a data uploading path of a data crawling flow of the page user behavior information through a big data acquisition control, configuring the data acquisition script according to the data acquisition identification node information, and then executing big data acquisition; and carrying out corresponding data acquisition and identification operation on the mobile internet terminal through the data acquisition script in the big data acquisition process. Obviously, in the process of providing a service based on internet big data, data processing is only performed in the data acquisition stage, which not only reduces the data acquisition amount, but also reduces the actual data obtained by a user after the acquired data is processed for many times in the subsequent transmission and conversion process, thereby easily causing data deviation and failing to meet the actual requirements of the user.
Disclosure of Invention
Therefore, the invention provides a service providing method based on internet big data, which can solve the technical problem that the data quantity is greatly reduced due to the fact that the data quantity is greatly reduced when the data acquisition stage is carried out to the acquisition node in the prior art, so that the data provided for the user has information deviation.
In order to achieve the above object, the present invention provides a service providing method based on internet big data, comprising:
receiving query information of a user;
extracting keywords of the query information, and searching query contents matched with the keywords in a plurality of associated databases based on the keywords;
quantitatively screening the inquired content, and selecting the content with the correlation degree higher than the preset correlation degree with the keyword as information to be fed back, wherein the information to be fed back is generated based on the inquired information;
acquiring current configuration information of a user, and performing secondary extraction of information from the filtered content according to the configuration information to form secondary feedback information;
and after information fusion is carried out on the information to be fed back and the secondary feedback information, an output list is formed, and the information in the output list is sent to a user.
Further, when searching the database for the query content matched with the keyword based on the keyword, counting the number of the obtained query content N1, and if N1 is less than or equal to N0 and N0 represents the reference number, determining the manner of expanding the query content according to the relationship between the difference Δ N between the two and the standard difference Δ N0.
Further, the determining the manner of the query content expansion according to the relationship between the difference Δ N and the standard difference Δ N0 includes:
setting delta N = N0-N1, and if 0.8 multiplied by delta N0 and delta N is less than or equal to delta N0, selecting keywords for fuzzy definition;
if 0.2 xDeltaN 0< DeltaN ≦ 0.8 xDeltaN 0, then the number of databases is selected to be increased;
if 0< Δ N ≦ 0.2 × Δ N0, the key is selected for ambiguity definition and the number of databases is selected to be increased.
Further, when the data volume of the database is increased, a first increment P1, a second increment P2 and a third increment P3 are provided, and the first increment P1< P2< P3 which are integers are provided;
when the delta N is more than 0.2 multiplied by delta N0 and less than or equal to 0.4 multiplied by delta N0, the number of the original databases is increased by adopting a third increment P3;
when the delta N is more than 0.4 multiplied by delta N0 and less than or equal to 0.6 multiplied by delta N0, the number of the original databases is increased by adopting a second increment P2;
when the delta N is more than 0.6 multiplied by delta N0 and less than or equal to 0.8 multiplied by delta N0, the number of the original databases is increased by adopting a first increment P1.
Further, the number of the original databases is increased by using a first increment P1, and the number of the increased databases is D1' = D0+ P1;
increasing the number of the original databases by using a second increment P2, wherein the increased number of the databases is D2' = D0+ P2;
and increasing the number of the original databases by using a third increment P3, wherein the number of the increased databases is D3' = D0+ P3, and D0 is the number of the original databases.
Further, when information fusion is carried out on the information to be fed back and the secondary feedback information, the secondary feedback information is inserted into the sequence of the information to be fed back, and the position of the secondary feedback information in the sequence of the information to be fed back is determined according to the type of the secondary feedback information.
Further, determining the position of the secondary feedback information in the sequence of information to be fed back according to the type of the secondary feedback information comprises:
presetting a first information type, a second information type and a third information type, wherein the first information type is instant information, the second information type is periodic information, the third information type is activation information, and when the secondary feedback information is a first type message, the secondary feedback information is inserted into the first N0/3 position in the feedback information;
if the secondary feedback information is of the second information type, inserting the secondary feedback information into the position of the middle N0/3 in the feedback information;
if the sub-feedback information is of the third information type, the sub-feedback information is inserted into the feedback information at the position of the last N0/3.
Further, in the process of screening the information to be fed back, if the number of keywords or databases is increased and then the requirements cannot be met, the preset correlation degree S0 is adjusted to make the data amount in the output list sufficient.
Further, when the preset correlation degree S0 needs to be adjusted, a first adjustment coefficient k1 and a second adjustment coefficient k2 are preset, wherein 1> k1> k2> 0; selecting an adjusting coefficient according to the size of a data gap of the output list to adjust the preset correlation degree S0, and if the data gap is large, reducing the preset correlation degree S0 by adopting a second adjusting coefficient so that more data can meet the requirement of the correlation degree and enter a data range for screening;
if the data gap is small, the preset correlation degree S0 is decreased by using the first adjustment coefficient.
Further, when the preset correlation degree S0 is adjusted by the first adjustment coefficient k1, the adjusted preset correlation degree S10= S0 × k 1;
when the second adjustment coefficient k2 is used to adjust the preset correlation degree S0, the adjusted preset correlation degree S20= S0 × k 2.
Compared with the prior art, the method has the advantages that the query content is obtained from the associated database through the query information of the user, the screening is carried out according to the correlation degree of the query content, the secondary extraction is carried out from the filtered content according to the configuration information of the user to form the secondary feedback information, and the information to be fed back and the secondary feedback information are fused, so that the output list sent to the user is more in line with the requirements of the user, the selection of the user based on the output list is improved, the information conversion capability based on the query information of the user is completed, and the conversion efficiency is improved.
Particularly, according to the query information of the user, the query information of the user is deeply mined, and the feedback information given to the user is subjected to multiple processing, so that the feedback information based on the query information is embodied, the feedback accuracy of the user for realizing the query information is obtained, and the conversion rate of the user based on the feedback information is improved.
Particularly, the number of the query contents searched in the database based on the keywords is compared with the preset standard number, if the number does not reach the data standard number, the query contents need to be expanded, and at the moment, the number of the query contents is effectively supplemented in various ways, so that the supplementing way has diversity, the feedback speed of the query contents is improved, the feedback speed of the query contents based on the user query information is improved, and the speed of the user for acquiring the information is improved.
The method can meet the requirement of efficient supplement of the query content of a user by selecting the expansion mode of the query content, in practical application, if the phase difference is small, fuzzy definition of keywords is adopted, multiple times of retrieval is carried out in an original database, content query supplement is carried out based on the keywords, the expansion speed of the query content is increased, if the phase difference is large, the expansion of the query data is realized by adopting two modes of fuzzy definition of the keywords and increasing the number of the databases, the searched related data can quickly reach the corresponding data volume, and the expansion of the query content is met.
The quantity of the original quantity of databases is increased in different levels, so that the precision operation of the query content is realized, and in practical application, if the databases in the same level are used for query, all data in the traversal database can be greatly increased.
Particularly, the position of the secondary feedback information in the feedback information is selected, so that the type of the secondary feedback information is matched with the position highly, the user can select the secondary feedback information conveniently according to the actual requirement, in the practical application, if the type of the secondary feedback information is instant information, the secondary feedback information needs to be processed by the user immediately, the secondary feedback information is arranged at a position which is relatively front, the user can process the secondary feedback information conveniently, and other types of information can be arranged at a corresponding position which is relatively rear, the information which can be displayed only by the user activation is needed, and the secondary feedback information is arranged at a last position, so that the user can process the corresponding activation information after browsing other information, the attention of the user is prevented from being interfered, and the user can focus on processing the output list more.
By adjusting the preset correlation degree, the expansion of the data content is more efficient, and in practical application, the keywords are set to be optimal, the related terms obtained after semantic blurring can be the best, the database used in the query process may be data query in a local area network, or data query in an external network, which is not limited herein, for the setting of the degree of correlation, different levels can be set, and the optimal example is used for illustration, the degree of correlation can be set as one level with the optimal composition sentence, the degree of correlation can not be set as the second degree of correlation with the optimal composition sentence, therefore, the embodiment of the invention enables more contents to enter the query range by adjusting the relevancy of the keywords, effectively supplements the data volume in the output list, improves the matching degree of the output list and the query information of the user, and provides the conversion efficiency.
Drawings
Fig. 1 is a schematic flowchart of a service providing method based on internet big data according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, a service providing method based on internet big data according to an embodiment of the present invention includes:
step S100: receiving query information of a user;
step S200: extracting keywords of the query information, and searching query contents matched with the keywords in a plurality of associated databases based on the keywords;
step S300: quantitatively screening the inquired content, and selecting the content with the correlation degree higher than the preset correlation degree with the keyword as information to be fed back, wherein the information to be fed back is generated based on the inquired information;
step S400: acquiring current configuration information of a user, and performing secondary extraction of information from the filtered content according to the configuration information to form secondary feedback information;
step S500: and after information fusion is carried out on the information to be fed back and the secondary feedback information, an output list is formed, and the information in the output list is sent to a user.
Specifically, in the application scenario of the embodiment of the present invention, a user proposes a query request, the query request of the user is fed back to a processor in the form of query information, the processor is connected to a plurality of databases, each database includes content related to the query information of the user, for example, each database may be each search database, index information may be set in each search database, and corresponding content in the database may be obtained according to the index information, and a keyword of the embodiment of the present invention may be the index information, or semantic information obtained after fuzzy processing of the keyword, where the semantic information is the index information, and in actual application, the number of content obtained based on the keyword or the semantic information obtained after fuzzy processing of the keyword is large, and at this time, a reference number N0 needs to be set, selecting N0 pieces of content with higher relevance from retrieved data information as information to be fed back, using the N0+1 and subsequent content as standby information, wherein the standby information is obtained based on keywords or semantic information of the keywords but has slightly lower relevance, in the embodiment of the invention, the configuration information of a user is obtained, secondary extraction is carried out from the standby information based on the configuration information of the user, when the secondary extraction is carried out, the configuration information of the user can be age information, gender information or other information, deep processing is carried out on the standby information based on the configuration information of the user, secondary feedback information matched with the depth of the user is obtained, wherein the secondary feedback information can be a depth requirement formed based on user requirement information, namely the depth requirement in the secondary feedback information is firstly needed to be completed when the user wants to complete the query information, when the service information is provided for the user, the information to be fed back and the sub-feedback information can be fed back to the user after being fused, so that the user can conveniently select the feedback result according to needs, the selection or the conversion can be further carried out according to the feedback result, and the conversion efficiency of the feedback information based on the user needs can be improved.
Specifically, according to the service providing method based on the internet big data provided by the embodiment of the invention, the query content is obtained from the associated database through the query information of the user, the query content is screened according to the correlation degree of the query content, secondary extraction is performed from the filtered content according to the configuration information of the user, the secondary feedback information is formed, and the information to be fed back and the secondary feedback information are fused, so that the output list sent to the user is more in line with the user requirement, the selection of the user based on the output list is improved, the information conversion capability based on the query information of the user is completed, and the conversion efficiency is improved.
Specifically, according to the query information of the user, the query information of the user is deeply mined, and the feedback information given to the user is subjected to multiple processing, so that the feedback information based on the query information is embodied, the feedback accuracy of the user for realizing the query information is obtained, and the conversion rate of the user based on the feedback information is improved.
Specifically, when searching for query content matching with a keyword in a database based on the keyword, the number N1 of the obtained query content is counted, and if N1 is not greater than N0, the manner of expanding the query content is determined according to the relationship between the difference between the two and the standard difference Δ N0.
Specifically, the embodiment of the invention compares the number of the search query contents in the database based on the keywords with the preset standard number, if the number does not reach the data standard number, the query contents need to be expanded, and at the moment, the number of the query contents is effectively supplemented by adopting a plurality of modes, so that the supplementing mode has diversity, the feedback speed of the query contents is convenient to improve, the feedback speed of the information based on the user query is convenient to improve, and the speed of the user for acquiring the information is improved.
Specifically, the determining the manner of expansion for the query content according to the relationship between the difference Δ N and the standard difference Δ N0 includes:
setting delta N = N0-N1, and if 0.8 multiplied by delta N0 and delta N is not more than delta N0, selecting keywords to carry out fuzzy definition;
if 0.2 xDeltaN 0< DeltaN ≦ 0.8 xDeltaN 0, then the number of databases is selected to be increased;
if 0< Δ N ≦ 0.2 × Δ N0, the key is selected for ambiguity definition and the number of databases is selected to be increased.
Specifically, the embodiment of the invention selects the expansion mode of the query content, so that the efficient supplement of the query content of the user can be met, in practical application, if the phase difference is less, the fuzzy definition of the keywords is adopted, so that the repeated retrieval is carried out in the original database, the content query is supplemented based on the keywords, the expansion speed of the query content is increased, and if the phase difference is more, the expansion of the query data is realized by adopting two modes of the fuzzy definition of the keywords and the increase of the number of the databases, so that the searched related data can quickly reach the corresponding data volume, and the expansion of the query content is met.
Specifically, when the data volume of the database is increased, a first increment P1, a second increment P2 and a third increment P3 are provided, and the first increment P1< P2< P3 are integers;
when the delta N is more than 0.2 multiplied by delta N0 and less than or equal to 0.4 multiplied by delta N0, the number of the original databases is increased by adopting a third increment P3;
when the delta N is more than 0.4 multiplied by delta N0 and less than or equal to 0.6 multiplied by delta N0, the number of the original databases is increased by adopting a second increment P2;
when the delta N is more than 0.6 multiplied by delta N0 and less than or equal to 0.8 multiplied by delta N0, the number of the original databases is increased by adopting a first increment P1.
Specifically, the embodiment of the invention increases the number of the original number of databases at different levels to realize the precision operation of the query content, and in practical application, if the database query at the same level is adopted, all data in the traversal database can be greatly increased.
Specifically, the number of the original databases is increased by using a first increment P1, and the number of the increased databases is D1' = D0+ P1;
increasing the number of the original databases by using a second increment P2, wherein the increased number of the databases is D2' = D0+ P2;
and increasing the number of the original databases by using a third increment P3, wherein the number of the increased databases is D3' = D0+ P3, and D0 is the number of the original databases.
Specifically, the embodiment of the invention increases the number of the databases by increasing the corresponding increment on the basis of the number of the original databases, so that the data volume of the query content is increased after the number is increased, the improvement of the output list is further realized, and the efficiency of providing service for the user is higher.
Specifically, when information fusion is performed on information to be fed back and secondary feedback information, the secondary feedback information is inserted into a sequence of the information to be fed back, and the position of the secondary feedback information in the sequence of the information to be fed back is determined according to the type of the secondary feedback information.
Specifically, the determining the position of the secondary feedback information in the sequence of the information to be fed back according to the type of the secondary feedback information comprises:
presetting a first information type, a second information type and a third information type, wherein the first information type is instant information, the second information type is periodic information, the third information type is activation information, and when the secondary feedback information is a first type message, the secondary feedback information is inserted into the first N0/3 position in the feedback information;
if the secondary feedback information is of the second information type, inserting the secondary feedback information into the position of the middle N0/3 in the feedback information;
if the sub-feedback information is of the third information type, the sub-feedback information is inserted into the feedback information at the position of the last N0/3.
Specifically, in the embodiment of the present invention, the position of the secondary feedback information in the feedback information is selected, so that the type of the secondary feedback information is highly matched and matched with the position, and the user can conveniently select the secondary feedback information according to actual needs, in actual application, if the type of the secondary feedback information is instant information, the user needs to perform instant processing, and therefore the secondary feedback information is arranged at a position closer to the front so as to facilitate the user to perform instant processing, and other types of information can be arranged at a corresponding position closer to the rear, if the secondary feedback information is activated, the information which can be displayed only by the user needs to be activated, and by being arranged at the last position, the user can conveniently process the corresponding activated information after browsing other information, so that the attention of the user is prevented from being interfered, and the user can more concentrate on the processing of the output list.
Specifically, in the process of screening the information to be fed back, if the number of keywords or databases is increased and then the requirements cannot be met, the preset correlation degree S0 is adjusted so that the amount of data in the output list is sufficient.
Specifically, when the preset correlation degree S0 needs to be adjusted, a first adjustment coefficient k1 and a second adjustment coefficient k2 are preset, wherein 1> k1> k2> 0; selecting an adjusting coefficient according to the size of a data gap of the output list to adjust the preset correlation degree S0, and if the data gap is large, reducing the preset correlation degree S0 by adopting a second adjusting coefficient so that more data can meet the requirement of the correlation degree and enter a data range for screening;
if the data gap is small, the preset correlation degree S0 is reduced by a small amplitude by adopting a first adjusting coefficient.
Specifically, when the preset correlation S0 is adjusted by using the first adjustment coefficient k1, the adjusted preset correlation S10= S0 × k 1;
when the preset correlation degree S0 is adjusted by the second adjustment coefficient k2, the adjusted preset correlation degree S20= S0 × k 2.
Specifically, the embodiment of the present invention adjusts the preset relevancy, so that expansion of data content is more efficient, in practical applications, keywords are set as optimal, related terms obtained after semantic blurring may be the best, a database used in a query process may be data query in a local area network or data query in an external network, without limitation, different hierarchies may be set for setting the relevancy, the optimal case is used for explaining the optimal case, one layer of relevancy can be set as a sentence which is optimally composed, and a second relevancy cannot be set as a sentence which is optimally composed, so that the embodiment of the present invention adjusts the relevancy of the keywords, so that more contents enter a query range, effectively supplements data amount in an output list, and improves matching degree between the output list and query information of a user, providing conversion efficiency.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention; various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A service providing method based on Internet big data is characterized by comprising the following steps:
receiving query information of a user;
extracting keywords of the query information, and searching query contents matched with the keywords in a plurality of associated databases based on the keywords;
quantitatively screening the inquired contents, and selecting the contents with the correlation degree higher than a preset correlation degree with the keywords as information to be fed back, wherein the information to be fed back is generated based on the inquired information;
acquiring current configuration information of a user, and performing secondary extraction of information from the filtered content according to the configuration information to form secondary feedback information;
after information fusion is carried out on the information to be fed back and the secondary feedback information, an output list is formed, and information in the output list is sent to a user;
when searching for query contents matched with the keywords in the database based on the keywords, counting the number N1 of the obtained query contents, and if N1 is not more than N0, determining a mode for expanding the query contents according to the relationship between the difference value of the two and a standard difference value delta N0;
when information fusion is carried out on information to be fed back and secondary feedback information, the secondary feedback information is inserted into a sequence of the information to be fed back, and the position of the secondary feedback information in the sequence of the information to be fed back is determined according to the type of the secondary feedback information;
determining the position of the secondary feedback information in the sequence of the information to be fed back according to the type of the secondary feedback information comprises the following steps:
presetting a first information type, a second information type and a third information type, wherein the first information type is instant information, the second information type is periodic information, the third information type is activation information, and when the secondary feedback information is a first type message, the secondary feedback information is inserted into the position of the first N0/3 in the feedback information;
if the secondary feedback information is of the second information type, inserting the secondary feedback information into the position of the middle N0/3 in the feedback information;
if the sub-feedback information is of a third information type, inserting the sub-feedback information into the position of the last N0/3 in the feedback information;
the manner for determining the expansion of the query content according to the relationship between the difference value of the two and the standard difference value Δ N0 comprises the following steps:
setting delta N = N0-N1, and if 0.8 multiplied by delta N0 and delta N is less than or equal to delta N0, selecting keywords for fuzzy definition;
if 0.2 xDeltaN 0< DeltaN ≦ 0.8 xDeltaN 0, then the number of databases is selected to be increased;
if 0< delta N ≦ 0.2 x delta N0, selecting a keyword for fuzzy definition and selecting to increase the number of databases;
when the data volume of the database is increased, a first increment P1, a second increment P2 and a third increment P3 are arranged, and the first increment P1 is more than P2 and more than P3, and the first increment P1 is more than the second increment P2 and more than the third increment P3;
when the delta N is more than 0.2 multiplied by delta N0 and less than or equal to 0.4 multiplied by delta N0, the number of the original databases is increased by adopting a third increment P3;
when the delta N is more than 0.4 multiplied by delta N0 and less than or equal to 0.6 multiplied by delta N0, the number of the original databases is increased by adopting a second increment P2;
when the delta N is more than 0.6 multiplied by delta N0 and less than or equal to 0.8 multiplied by delta N0, the number of the original databases is increased by adopting a first increment P1.
2. The Internet big data-based service providing method according to claim 1,
increasing the number of the original databases by using a first increment P1, wherein the increased number of the databases is D1' = D0+ P1;
increasing the number of the original databases by using a second increment P2, wherein the number of the increased databases is D2' = D0+ P2;
and increasing the number of the original databases by using a third increment P3, wherein the number of the increased databases is D3' = D0+ P3, and D0 is the number of the original databases.
3. The method for providing a service based on internet big data according to claim 1, wherein in the process of screening the information to be fed back, if the requirement cannot be met after the number of keywords or databases is increased, the preset relevancy S0 is adjusted to make the data amount in the output list sufficient.
4. The method for providing a service based on internet big data according to any of claims 1-3, wherein when the preset correlation degree S0 needs to be adjusted, a first adjustment coefficient k1 and a second adjustment coefficient k2 are preset, wherein 1> k1> k2> 0; selecting an adjusting coefficient according to the size of a data gap of the output list to adjust the preset correlation degree S0, and if the data gap is large, reducing the preset correlation degree S0 by adopting a second adjusting coefficient so that more data can meet the requirement of the correlation degree and enter a data range for screening;
if the data gap is small, the preset correlation degree S0 is reduced by adopting a first adjusting coefficient.
5. The Internet big data-based service providing method according to claim 4,
when the preset correlation degree S0 is adjusted by using the first adjustment coefficient k1, the adjusted preset correlation degree S10= S0 × k 1;
when the preset correlation degree S0 is adjusted by the second adjustment coefficient k2, the adjusted preset correlation degree S20= S0 × k 2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210340004.9A CN114491211B (en) | 2022-04-02 | 2022-04-02 | Service providing method based on internet big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210340004.9A CN114491211B (en) | 2022-04-02 | 2022-04-02 | Service providing method based on internet big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114491211A CN114491211A (en) | 2022-05-13 |
| CN114491211B true CN114491211B (en) | 2022-07-19 |
Family
ID=81488637
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210340004.9A Active CN114491211B (en) | 2022-04-02 | 2022-04-02 | Service providing method based on internet big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114491211B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116542251B (en) * | 2023-07-06 | 2023-12-01 | 广州宏途数字科技有限公司 | Network supervision method and system based on intelligent campus |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006009366A1 (en) * | 2004-07-16 | 2006-01-26 | Eui Sin Jeong | Target advertising method and system using secondary keywords having relation to first internet searching keywords, and method and system for providing a list of the secondary keywords |
| WO2019120540A1 (en) * | 2017-12-21 | 2019-06-27 | Arcelik Anonim Sirketi | System and method for compiling suggestions from electronic program guide based on keywords and setting alarms |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5376625B2 (en) * | 2008-08-05 | 2013-12-25 | 学校法人東京電機大学 | Iterative fusion search method in search system |
| US10817549B2 (en) * | 2016-12-09 | 2020-10-27 | Salesforce.Com, Inc. | Augmenting match indices |
| CN109101630B (en) * | 2018-08-14 | 2021-12-17 | 广东小天才科技有限公司 | Method, device and equipment for generating search result of application program |
| US11487823B2 (en) * | 2018-11-28 | 2022-11-01 | Sap Se | Relevance of search results |
| TWI753267B (en) * | 2019-06-14 | 2022-01-21 | 劉國良 | System and implementation method thereof for optimizing consumption recommendation information and purchasing decisions |
| CN112035732A (en) * | 2020-08-25 | 2020-12-04 | 深圳乐信软件技术有限公司 | Method, system, equipment and storage medium for expanding search results |
-
2022
- 2022-04-02 CN CN202210340004.9A patent/CN114491211B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006009366A1 (en) * | 2004-07-16 | 2006-01-26 | Eui Sin Jeong | Target advertising method and system using secondary keywords having relation to first internet searching keywords, and method and system for providing a list of the secondary keywords |
| WO2019120540A1 (en) * | 2017-12-21 | 2019-06-27 | Arcelik Anonim Sirketi | System and method for compiling suggestions from electronic program guide based on keywords and setting alarms |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114491211A (en) | 2022-05-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sahami et al. | Sonia: A service for organizing networked information autonomously | |
| US6732088B1 (en) | Collaborative searching by query induction | |
| RU2435213C2 (en) | Search results time ranking | |
| US20190108276A1 (en) | Methods and system for semantic search in large databases | |
| EP0949571A2 (en) | Document re-authoring systems and methods for providing device-independent access to the world wide web | |
| US20060167896A1 (en) | Systems and methods for managing and using multiple concept networks for assisted search processing | |
| US20080005102A1 (en) | Techniques for Targeting Information to Users | |
| US20170212899A1 (en) | Method for searching related entities through entity co-occurrence | |
| WO2002091216A1 (en) | Very-large-scale automatic categorizer for web content | |
| EP1362298A2 (en) | Method and system for personalisation of digital information | |
| US7203673B2 (en) | Document collection apparatus and method for specific use, and storage medium storing program used to direct computer to collect documents | |
| CN114491211B (en) | Service providing method based on internet big data | |
| CN115563313A (en) | Knowledge graph-based document book semantic retrieval system | |
| EP1524611A2 (en) | System and method for providing information to a user | |
| EP2017752A1 (en) | Information processing apparatus, information processing method and program | |
| JP5349032B2 (en) | Information sorting device | |
| WO2008130501A1 (en) | Unstructured and semistructured document processing and searching and generation of value-based information | |
| Colace et al. | A query expansion method based on a weighted word pairs approach | |
| Benitez et al. | Multimedia knowledge integration, summarization and evaluation | |
| CN116795968A (en) | Knowledge extension and QA system based on Chat LLM technology | |
| Shafi et al. | [WiP] Web Services Classification Using an Improved Text Mining Technique | |
| CN112287218A (en) | Knowledge graph-based non-coal mine literature association recommendation method | |
| EP2083364A1 (en) | Method for retrieving a document, a computer-readable medium, a computer program product, and a system that facilitates retrieving a document | |
| Harakawa et al. | An efficient extraction method of hierarchical structure of web communities for web video retrieval | |
| Yahyaoui et al. | Measuring semantic similarity between services using hypergraphs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |