CN113779418B - Tourism message subscription push system - Google Patents
Tourism message subscription push system Download PDFInfo
- Publication number
- CN113779418B CN113779418B CN202111337579.7A CN202111337579A CN113779418B CN 113779418 B CN113779418 B CN 113779418B CN 202111337579 A CN202111337579 A CN 202111337579A CN 113779418 B CN113779418 B CN 113779418B
- Authority
- CN
- China
- Prior art keywords
- travel
- user
- message
- target user
- intention
- 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.)
- Expired - Fee Related
Links
- 238000012795 verification Methods 0.000 claims abstract description 43
- 238000000034 method Methods 0.000 claims description 34
- 238000000605 extraction Methods 0.000 claims description 11
- 230000003827 upregulation Effects 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000003828 downregulation Effects 0.000 claims description 9
- 230000009286 beneficial effect Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010200 validation analysis Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 230000002222 downregulating effect Effects 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 230000037072 sun protection Effects 0.000 description 1
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
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- 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
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a travel message subscription pushing system, which comprises: the target user determining module is used for determining a target user pushed by the travel message; the tourism intention analysis module is used for acquiring information data related to the target user from the big data platform and analyzing the tourism intention of the target user based on the information data; the tourism information acquisition module is used for acquiring tourism information from the big data platform based on the tourism intention; the verification module is used for verifying the tourism message and marking the tourism message passing the verification; and the pushing module is used for pushing the tour message verified by the verification module to the target user. The tourism message subscription pushing system verifies and marks the tourism message before pushing by pushing the tourism message which accords with the tourism intention of the user, and the user can avoid the interference of unreal tourism messages by judging whether the pushed tourism message has the corresponding mark or not.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a travel message subscription pushing system.
Background
With the gradual improvement of the life quality of people, tourism becomes an important form of leisure life of people; at present, the tourism information acquisition ways of people mainly comprise an active mode and a passive mode, active acquisition is realized by searching the tourism information from a network, but the information on the network has a part which is not beneficial to judgment of people, people cannot effectively screen the part, and a large amount of data information which is not beneficial to judgment of people is essential along with the development of big data and the Internet; passive acquisition is pushed by means of advertisements and the like, but often some travel messages which do not accord with the mind of people are pushed.
Disclosure of Invention
One of the objectives of the present invention is to provide a travel message subscription pushing system, which analyzes the relevant information of a user on a big data platform to determine the travel intention, verifies and labels the travel message before pushing by pushing the travel message meeting the travel intention of the user, so that the user can avoid the interference of unreal travel messages by determining whether the pushed travel message has a corresponding label.
The embodiment of the invention provides a travel message subscription pushing system, which comprises:
the target user determining module is used for determining a target user pushed by the travel message;
the tourism intention analysis module is used for acquiring information data related to the target user from the big data platform and analyzing the tourism intention of the target user based on the information data;
the tourism information acquisition module is used for acquiring tourism information from the big data platform based on the tourism intention;
the verification module is used for verifying the tourism message and marking the tourism message passing the verification;
and the pushing module is used for pushing the tour message verified by the verification module to the target user.
Preferably, the tourism intention analysis module acquires information data related to the target user from the big data platform and analyzes the tourism intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data to obtain a travel wish list of the target user;
determining a first time for a travel wishlist to be generated;
analyzing the information data again to obtain the travel history information of the target user from the first time to the current time;
and determining a tourism destination corresponding to the unfinished wish of the tourism wish list of the target user based on the tourism history information, and taking the tourism destination corresponding to the unfinished wish of the tourism wish list of the target user as the tourism intention of the target user.
Preferably, the tourism intention analysis module acquires information data related to the target user from the big data platform and analyzes the tourism intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data, and acquiring the filling information of the latest target user on a preset travel questionnaire;
analyzing the filling information, determining the classification identification of the intention tourist destination of the target user and constructing a first identification set based on all the classification identifications of the intention tourist destination;
determining a second time of generation of the filling information;
analyzing the information data again to obtain the travel history information of the target user from the second time to the current time;
based on the travel history information of the target user from the second time to the current time, determining the classification identification of the travel destination which the target user has traveled and constructing a second identification set based on the classification identifications of all the travel destinations which have traveled;
determining an intention identifier set based on the first identifier set and the second identifier set; and taking the intention identification set as the travel intention of the target user.
Preferably, the tourism intention analysis module acquires information data related to the target user from the big data platform and analyzes the tourism intention of the target user based on the information data; the method comprises the following steps:
extracting the characteristics of the information data based on a preset characteristic extraction template to obtain a plurality of characteristic values;
constructing a target user intention vector based on the plurality of characteristic values;
acquiring a preset travel intention analysis library;
determining the travel intention of the target user based on the target user intention vector and the travel intention analysis library;
wherein, the standard intention vector in the travel intention analysis library is correspondingly associated with the travel intention;
determining the travel intention of the target user based on the target user intention vector and the travel intention analysis library; the method comprises the following steps:
and matching the target user intention vector with each standard intention vector one by one, and determining the tourism intention corresponding to the standard intention vector matched with the target user intention vector.
Preferably, the verification module verifies the travel message and marks the travel message passing the verification, including:
determining the identification information of a travel destination corresponding to the travel message; the identification information includes: one or more of name, identification code and position;
acquiring first feedback information of first users playing the tourism destination corresponding to the tourism information in a preset amount within a preset time from the big data platform based on the identification information;
constructing a first key parameter set corresponding to each first user based on first feedback information corresponding to each first user;
constructing a second key parameter set based on the travel message;
determining the popularity of each first user to the travel message based on the first key parameter set and the second key parameter set;
determining the reliability of the travel message based on the approval degree of each first user;
and when the credibility is greater than a preset credibility threshold value, the travel message passes the verification.
Preferably, the determining the popularity of each first user for the travel message based on the first set of key parameters and the second set of key parameters includes:
calculating the similarity of the first key parameter set and the second key parameter set, wherein the similarity calculation formula is as follows:
wherein,
is as follows
The similarity between a first key parameter set and a second key parameter set corresponding to each first user;
is as follows
First key parameter set corresponding to first user
The value of each key parameter;
set forth for the second key parameter
The value of each key parameter;
a total number of key parameters being the first key parameter set or the second key parameter set;
and determining the popularity of the first user corresponding to the first key parameter set to the travel message based on the similarity of the first key parameter set and the second key parameter set and a preset comparison table of the similarity and the popularity.
Preferably, the reliability of the travel message is determined based on the approval degree of each first user; the method comprises the following steps:
acquiring a credit set corresponding to each first user; the credit set includes: the target user gives the first user an indirect credit coefficient for the direct credit coefficient and the big data platform of the first user;
calculating a voting value of the travel message based on the credit set and the approval degree; the calculation formula of the vote value is as follows:
wherein,
a vote value for a travel message;
is as follows
The popularity of the first user to the travel message;
is a direct credit coefficient;
is an indirect credit coefficient;
and determining the reliability of the travel message based on the voting value of the travel message and a preset comparison table of the voting value and the reliability.
Preferably, the travel message subscription pushing system further includes:
the credit adjustment module is used for acquiring second feedback information of the target user on the tourist destination corresponding to the pushed tourist message after the target user selects the tourist destination corresponding to the pushed verified tourist message for playing; adjusting the direct credit coefficient of the first user with the approval degree larger than or equal to a preset approval threshold value in the verification process of the verified travel message based on the second feedback information;
the credit adjustment module adjusts the direct credit coefficient of the first user of which the approval degree is greater than or equal to a preset approval threshold value in the verification process of the verified travel message based on the second feedback information, and the credit adjustment module comprises:
constructing a third key parameter set based on the second feedback information of the target user;
calculating the similarity of the second key parameter set and the third key parameter set;
when the similarity of the second key parameter set and the third key parameter set is greater than or equal to a preset first similarity threshold, performing up-regulation operation on a direct credit coefficient of a first user, of which the approval degree is greater than or equal to the preset approval threshold in the verification process of the approved travel message, by using a preset first upper amplitude modulation value;
when the similarity of the second key parameter set and the third key parameter set is smaller than a preset first similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user, of which the approval degree is greater than or equal to the preset approval threshold in the verification process of the approved travel message, by using a preset first lower amplitude modulation value;
wherein the first upper amplitude modulation value is greater than the first lower amplitude modulation value; when the adjusted direct credit coefficient is larger than a preset maximum direct credit coefficient, taking the maximum direct credit coefficient as a final direct credit coefficient of the first user; and when the adjusted direct credit coefficient is smaller than a preset minimum direct credit coefficient, taking the minimum direct credit coefficient as the final direct credit coefficient of the first user.
Preferably, the credit adjustment module further performs the following operations:
acquiring third feedback information corresponding to a tour destination corresponding to a verified tour message which is selected and pushed by a target user and is authorized by a plurality of second users through official certification of a big data platform;
constructing a fourth key parameter set based on the third feedback information;
calculating the similarity of the second key parameter set and the fourth key parameter set;
when the similarity between the second key parameter set and the fourth key parameter set is greater than or equal to a preset second similarity threshold, performing an up-regulation operation on the indirect credit coefficient of the first user, of which the approval degree is greater than or equal to the preset approval threshold in the verification process of the approved travel message, by using a preset second upper amplitude modulation value;
when the similarity of the second key parameter set and the fourth key parameter set is smaller than a preset similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user with the approval degree larger than or equal to the preset approval threshold in the verification process of the approved travel message by using a preset second down-regulation amplitude value;
wherein the second upper amplitude modulation value is greater than the second lower amplitude modulation value; when the adjusted indirect credit coefficient is larger than a preset maximum indirect credit coefficient, taking the maximum indirect credit coefficient as a final indirect credit coefficient of the first user; and when the adjusted indirect credit coefficient is smaller than a preset minimum indirect credit coefficient, taking the minimum indirect credit coefficient as the final indirect credit coefficient of the first user.
Preferably, the big data platform performs the following operations before storing the first feedback information of the first user for the first user who has played the travel destination corresponding to the travel message:
acquiring historical track data of a first user;
acquiring position information of each scenic spot of a tourist destination;
determining a first set of sights played by a first user based on historical track data and location information;
analyzing the first feedback information and determining a second scenic spot set;
when the second sight spot set is a subset of the first sight spot set, receiving and storing first feedback information of the first user for the first user who plays the tour destination corresponding to the tour message; otherwise, it is not stored.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a travel message subscription pushing system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating steps performed by a travel intent analysis module according to an embodiment of the invention;
fig. 3 is a schematic diagram illustrating an execution step of a verification module according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
An embodiment of the present invention provides a travel message subscription pushing system, as shown in fig. 1, including:
the target user determining module 1 is used for determining a target user pushed by the travel message;
the tourism intention analysis module 2 is used for acquiring information data related to the target user from the big data platform and analyzing the tourism intention of the target user based on the information data;
the tourism information acquisition module 3 is used for acquiring tourism information from the big data platform based on the tourism intention;
the verification module 4 is used for verifying the tourism message and marking the tourism message passing the verification;
and the pushing module 5 is used for pushing the tour message verified by the verification module 4 to the target user.
The working principle and the beneficial effects of the technical scheme are as follows:
when the travel message is pushed, firstly, a pushed target, namely a target user needs to be determined; for example: when the user subscribes the function of pushing the tourism message, the subscribing user is the target user; in addition, when the user reserves a hotel, a ticket and a ticket on the network, the user can also be regarded as a target user; when the pushed target is determined, the intention of the target needs to be analyzed, namely information data related to the target user is obtained from a big data platform through a tourism intention analysis module 2, and the tourism intention of the target user is analyzed based on the information data; for example: when the hotel is reserved, the travel intention of the user comprises a travel destination of the position where the hotel is located; when the target user is not a target user in a mode of reserving a hotel or the like, intention analysis may be performed according to information data corresponding to daily behaviors of the user, for example: when a user recently purchases mountaineering supplies, the tourism intention of the user is a tourism destination (such as Huangshan mountain and Taishan mountain) with mountaineering items; accurate pushing is carried out through the tourism intention based on the target user, and the pushing accuracy is improved. In addition, before pushing, the tourism message is required to be verified, and the authenticity and the validity of the tourism message are mainly verified; to exhaust the inducement of purposely exaggerated travel messages to the target user; in order to facilitate the target user to distinguish the verified and unverified travel messages, the pushed travel message is marked by adopting a mode of marking, for example, the preset verification is printed on the upper right corner of the page of the travel message for marking. Further, authentication is divided into official authentication and client authentication, and different authentication stamps may be used for distinction. In addition, a tourism intention receiving module can be arranged and used for receiving the tourism intention input by the user.
The tourism message subscription pushing system analyzes the related information of the user on the big data platform to determine the tourism intention of the user, verifies and marks the tourism message before pushing by pushing the tourism message which accords with the tourism intention of the user, and the user can avoid the interference of unreal tourism messages by judging whether the pushed tourism message has the corresponding mark or not.
In one embodiment, the tourism intention analysis module 2 acquires information data related to the target user from the big data platform and analyzes the tourism intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data to obtain a travel wish list of the target user;
determining a first time for a travel wishlist to be generated;
analyzing the information data again to obtain the travel history information of the target user from the first time to the current time;
and determining a tourism destination corresponding to the unfinished wish of the tourism wish list of the target user based on the tourism history information, and taking the tourism destination corresponding to the unfinished wish of the tourism wish list of the target user as the tourism intention of the target user.
The working principle and the beneficial effects of the technical scheme are as follows:
the user can be guided to make a travel wish list in a red purse delivery mode; and analyzing and identifying the travel wish list of the target user from the information data aiming at the user who has made the travel wish list before, and determining that the travel destination corresponding to the unfinished travel wish on the travel wish list is the travel intention of the target user by analyzing the travel condition of the user after making the travel wish list.
In one embodiment, the tourism intention analysis module 2 acquires information data related to the target user from the big data platform and analyzes the tourism intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data, and acquiring the filling information of the latest target user on a preset travel questionnaire;
analyzing the filling information, determining the classification identification of the intention tourist destination of the target user and constructing a first identification set based on all the classification identifications of the intention tourist destination;
determining a second time of generation of the filling information;
analyzing the information data again to obtain the travel history information of the target user from the second time to the current time;
based on the travel history information of the target user from the second time to the current time, determining the classification identification of the travel destination which the target user has traveled and constructing a second identification set based on the classification identifications of all the travel destinations which have traveled;
determining an intention identifier set based on the first identifier set and the second identifier set; and taking the intention identification set as the travel intention of the target user.
The working principle and the beneficial effects of the technical scheme are as follows:
performing questionnaire survey on a target user through a preset travel questionnaire; questionnaires can be conducted when a user logs in for registration; determining an intended tourist destination of the target user through a tourist questionnaire; specific travel destinations can be uncertain, and classification marks of the travel destinations can be determined; the classification identification comprises: cave-dissolving, mountain-climbing, landscape, extreme sports, etc.; for example: in the travel questionnaire, the question "the category of travel destinations you compare to mean" can be set to: 1. dissolving holes; 2. climbing; 3. viewing a scene; 4. extreme motion class "; determining a first identification set of a target user through a questionnaire; then, analyzing a second identification set of travel objectives that the user has completed at the moment of the questionnaire survey; and obtaining the intention identification set of the target user at the current moment by deleting the identifications in the second identification set from the first identification set.
In one embodiment, as shown in FIG. 2, the travel intention analysis module 2 obtains information data related to the target user from a big data platform and analyzes the travel intention of the target user based on the information data; the method comprises the following steps:
step S1: extracting the characteristics of the information data based on a preset characteristic extraction template to obtain a plurality of characteristic values;
step S2: constructing a target user intention vector based on the plurality of characteristic values;
step S3: acquiring a preset travel intention analysis library;
step S4: determining the travel intention of the target user based on the target user intention vector and the travel intention analysis library;
wherein, the standard intention vector in the travel intention analysis library is correspondingly associated with the travel intention;
determining the travel intention of the target user based on the target user intention vector and the travel intention analysis library; the method comprises the following steps:
and matching the target user intention vector with each standard intention vector one by one, and determining the tourism intention corresponding to the standard intention vector matched with the target user intention vector.
The working principle and the beneficial effects of the technical scheme are as follows:
extracting the characteristics of the information data through a preset characteristic extraction template to obtain a plurality of characteristic values; for simplicity of description, the feature extraction items of the feature extraction template are set to be 5, the first feature extraction item corresponds to whether to purchase skiing equipment, the second feature extraction item corresponds to whether to purchase swimwear, the third feature extraction item corresponds to whether to purchase a sun protection product, the fourth feature extraction item corresponds to whether to browse skiing related videos, and the fifth feature extraction item corresponds to whether to purchase mountaineering shoes; definition is 1, or not 0; traversing information data, and constructing target user intention vector
Determining travel intent of the target user based on the target user intent vector and a travel intent analysis library, from the target user intent vector
(ii) a Travel intent of target user can be determinedA travel destination for ski classification. Matching the target user intention vector with each standard intention vector one by one, and calculating the similarity between the target user intention vector and each standard intention vector; cosine similarity calculation formulas can be adopted; when the similarity is greater than the similarity threshold (0.95), a match is determined.
In one embodiment, as shown in FIG. 3, the verification module 4 verifies the travel message and marks the verified travel message, including:
step S11: determining the identification information of a travel destination corresponding to the travel message; the identification information includes: one or more of name, identification code and position; the identification code is unique identification information distributed to each tourist destination by the big data platform; the identification code is divided into two parts, wherein the first part is a position code, for example, the position code corresponding to Hangzhou in Zhejiang of China is 011001; the second part is a registration sequence code of a travel destination; for example: the registration order code of the first registered travel destination in Hangzhou is 01.
Step S12: acquiring first feedback information of first users playing the tourism destination corresponding to the tourism information in a preset amount within a preset time from the big data platform based on the identification information;
step S13: constructing a first key parameter set corresponding to each first user based on first feedback information corresponding to each first user; for example, key parameters may be used to quantify travel destinations, such as poor, general, good, or very good playability ratings; the corresponding quantization values are 0, 1, 2, 3, 4; in addition, the key parameters include: the environment of the tourist destination, whether or not the player feels tired after playing, etc.
Step S14: constructing a second key parameter set based on the travel message;
step S15: determining the popularity of each first user to the travel message based on the first key parameter set and the second key parameter set;
step S16: determining the reliability of the travel message based on the approval degree of each first user;
step S17: and when the credibility is greater than a preset credibility threshold value, the travel message passes the verification.
Determining the popularity of each first user for the travel message based on the first key parameter set and the second key parameter set, wherein the determining comprises:
calculating the similarity of the first key parameter set and the second key parameter set, wherein the similarity calculation formula is as follows:
wherein,
is as follows
The similarity between a first key parameter set and a second key parameter set corresponding to each first user;
is as follows
First key parameter set corresponding to first user
The value of each key parameter;
set forth for the second key parameter
The value of each key parameter;
a total number of key parameters being the first key parameter set or the second key parameter set;
and determining the popularity of the first user corresponding to the first key parameter set to the travel message based on the similarity of the first key parameter set and the second key parameter set and a preset comparison table of the similarity and the popularity.
Determining the reliability of the travel message based on the approval degree of each first user; the method comprises the following steps:
acquiring a credit set corresponding to each first user; the credit set includes: the target user gives the first user an indirect credit coefficient for the direct credit coefficient and the big data platform of the first user; the direct credit coefficient is set for the target user, for example, the target user pays attention to the first user, and the corresponding direct credit coefficient is 2.0; when the direct credit is not set, adopting an initial direct credit coefficient, wherein the initial direct credit coefficient is 0.1; the big data platform gives indirect credit coefficient to the first user; may be assigned by official verification based on the first user's feedback information; that is, when there is every feedback information verified in the big data platform, that is, 0.1 is given, it can be accumulated.
Calculating a voting value of the travel message based on the credit set and the approval degree; the calculation formula of the vote value is as follows:
wherein,
a vote value for a travel message;
is as follows
The popularity of the first user to the travel message;
is a direct credit coefficient;
as an indirect credit systemCounting;
and determining the reliability of the travel message based on the voting value of the travel message and a preset comparison table of the voting value and the reliability.
The working principle and the beneficial effects of the technical scheme are as follows:
analyzing first feedback information of a first user who plays a tour destination corresponding to the tour message, and determining the credibility of the tour message; when the confidence level is greater than a confidence threshold (e.g., 95), the travel message is validated and a validation stamp for the customer validation may be marked.
In one embodiment, the travel message subscription pushing system further includes:
the credit adjustment module is used for acquiring second feedback information of the target user on the tourist destination corresponding to the pushed tourist message after the target user selects the tourist destination corresponding to the pushed verified tourist message for playing; adjusting the direct credit coefficient of the first user with the approval degree being more than or equal to a preset approval threshold (for example: 90) in the process of verifying the approved travel message based on the second feedback information;
the credit adjustment module adjusts the direct credit coefficient of the first user of which the approval degree is greater than or equal to a preset approval threshold value in the verification process of the verified travel message based on the second feedback information, and the credit adjustment module comprises:
constructing a third key parameter set based on the second feedback information of the target user;
calculating the similarity of the second key parameter set and the third key parameter set;
when the similarity of the second key parameter set and the third key parameter set is greater than or equal to a preset first similarity threshold (for example, 0.96), performing an up-regulation operation on a direct credit coefficient of the first user, of which the approval is greater than or equal to the preset approval threshold, by a preset first up-regulation value in the verification process of the approved travel message;
when the similarity of the second key parameter set and the third key parameter set is smaller than a preset first similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user, of which the approval degree is greater than or equal to the preset approval threshold in the verification process of the approved travel message, by using a preset first lower amplitude modulation value;
wherein the first upper amplitude modulation value is greater than the first lower amplitude modulation value; when the adjusted direct credit coefficient is larger than a preset maximum direct credit coefficient, taking the maximum direct credit coefficient as a final direct credit coefficient of the first user; and when the adjusted direct credit coefficient is smaller than a preset minimum direct credit coefficient, taking the minimum direct credit coefficient as the final direct credit coefficient of the first user.
The working principle and the beneficial effects of the technical scheme are as follows:
and the direct credit coefficient of the first user is adjusted up and down through the feedback of the target user, so that the accuracy of next calculation of the credibility is ensured, and the reliability of the verification seal is improved.
In one embodiment, the credit adjustment module further performs the following operations:
acquiring third feedback information corresponding to a tour destination corresponding to a verified tour message which is selected and pushed by a target user and is authorized by a plurality of second users through official certification of a big data platform;
constructing a fourth key parameter set based on the third feedback information;
calculating the similarity of the second key parameter set and the fourth key parameter set;
when the similarity between the second key parameter set and the fourth key parameter set is greater than or equal to a preset second similarity threshold (for example: 0.95), performing an up-regulation operation on the indirect credit coefficient of the first user, of which the approval degree is greater than or equal to the preset approval threshold, in the verification process of the approved travel message by using a preset second up-regulation value;
when the similarity of the second key parameter set and the fourth key parameter set is smaller than a preset similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user with the approval degree larger than or equal to the preset approval threshold in the verification process of the approved travel message by using a preset second down-regulation amplitude value;
wherein the second upper amplitude modulation value is greater than the second lower amplitude modulation value; when the adjusted indirect credit coefficient is larger than a preset maximum indirect credit coefficient, taking the maximum indirect credit coefficient as a final indirect credit coefficient of the first user; and when the adjusted indirect credit coefficient is smaller than a preset minimum indirect credit coefficient, taking the minimum indirect credit coefficient as the final indirect credit coefficient of the first user.
The working principle and the beneficial effects of the technical scheme are as follows:
the feedback of a plurality of second users through official certification of the big data platform is used for up-regulating and down-regulating the indirect credit coefficient of the first user, so that the accuracy of next calculation of the credibility is ensured, and the reliability of the verification seal is improved.
In one embodiment, the big data platform performs the following operations before storing the first feedback information of the first user for the first user who has played the travel destination corresponding to the travel message:
acquiring historical track data of a first user;
acquiring position information of each scenic spot of a tourist destination;
determining a first set of sights played by a first user based on historical track data and location information;
analyzing the first feedback information and determining a second scenic spot set;
when the second sight spot set is a subset of the first sight spot set, receiving and storing first feedback information of the first user for the first user who plays the tour destination corresponding to the tour message; otherwise, it is not stored.
The accuracy and effectiveness of information fed back by the first user are ensured through the historical track data of the first user, namely, the opinion feedback can be carried out only on the items played by the user; in addition, a time threshold determination can be added on the basis of the track, namely feedback of feedback information can be performed only when the stay time of the played item position reaches a preset time threshold, and in the process of establishing the first scenic spot set, the scenic spots in the first scenic spot set can be generated only when the stay time of the corresponding scenic spots in the historical track data reaches the corresponding time threshold.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (7)
1. A travel message subscription pushing system is characterized by comprising:
the target user determining module is used for determining a target user pushed by the travel message;
the tourism intention analysis module is used for acquiring information data related to the target user from a big data platform and analyzing the tourism intention of the target user based on the information data;
the tourism information acquisition module is used for acquiring tourism information from the big data platform based on the tourism intention;
the verification module is used for verifying the tourism message and marking the tourism message passing the verification;
the pushing module is used for pushing the tourism message verified by the verification module to the target user;
wherein, the verification module verifies the tourism message and marks the tourism message passing the verification, including:
determining the identification information of a travel destination corresponding to the travel message; the identification information includes: one or more of name, identification code and position;
acquiring first feedback information of a preset number of first users who have played a tour destination corresponding to the tour message within a preset time from the big data platform based on the identification information;
constructing a first key parameter set corresponding to each first user based on the first feedback information corresponding to each first user;
constructing a second key parameter set based on the travel message;
determining the popularity of each first user for the travel message based on the first set of key parameters and the second set of key parameters;
determining the credibility of the travel message based on the approval degree of each first user;
when the credibility is larger than a preset credibility threshold value, the travel message passes the verification;
wherein the determining the popularity of each of the first users for the travel messages based on the first set of key parameters and the second set of key parameters comprises:
calculating the similarity of the first key parameter set and the second key parameter set, wherein a similarity calculation formula is as follows:
wherein,
is as follows
The similarity between the first key parameter set and the second key parameter set corresponding to the first user;
is as follows
The first key parameter set corresponding to the first user is
The value of each key parameter;
set as the second key parameter
The value of each key parameter;
a total number of key parameters that is the first set of key parameters or the second set of key parameters;
determining the popularity of the first user for the travel message corresponding to the first key parameter set based on the similarity of the first key parameter set and the second key parameter set and a preset comparison table of the similarity and the popularity;
determining the credibility of the travel message based on the approval degree of each first user; the method comprises the following steps:
acquiring a credit set corresponding to each first user; the set of credits comprises: the target user gives the first user a direct credit coefficient and the big data platform an indirect credit coefficient;
calculating a voting value of the travel message based on the credit set and the like; the calculation formula of the vote value is as follows:
wherein,
a vote value for the travel message;
is as follows
(ii) an endorsement by each of the first users for the travel message;
is the direct credit coefficient;
is the indirect credit coefficient;
and determining the reliability of the travel message based on the voting value of the travel message and a preset voting value and reliability comparison table.
2. The travel message subscription pushing system of claim 1, wherein the travel intention analysis module obtains information data related to the target user from a big data platform and analyzes the travel intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data to obtain a travel wish list of the target user;
determining a first time of generation of the travel wishlist;
analyzing the information data again to obtain the travel history information of the target user from the first time to the current time;
and determining a tourism destination corresponding to the unfinished wish of the tourism wish list of the target user based on the tourism history information, and taking the tourism destination corresponding to the unfinished wish of the tourism wish list of the target user as the tourism intention of the target user.
3. The travel message subscription pushing system of claim 1, wherein the travel intention analysis module obtains information data related to the target user from a big data platform and analyzes the travel intention of the target user based on the information data; the method comprises the following steps:
analyzing the information data to obtain the filling information of the target user for a preset travel questionnaire at the latest time;
analyzing the filling information, determining the classification identification of the intention tourist destination of the target user and constructing a first identification set based on all the classification identifications of the intention tourist destination;
determining a second time of generation of the filling information;
analyzing the information data again to obtain the travel history information of the target user from the second time to the current time;
based on the travel history information of the target user from the second time to the current time, determining the classification identification of the travel destination which has traveled by the target user and constructing a second identification set based on the classification identifications of all the travel destinations which have traveled;
determining an intent identifier set based on the first identifier set and the second identifier set; and taking the intention identification set as the travel intention of the target user.
4. The travel message subscription pushing system of claim 1, wherein the travel intention analysis module obtains information data related to the target user from a big data platform and analyzes the travel intention of the target user based on the information data; the method comprises the following steps:
extracting the features of the information data based on a preset feature extraction template to obtain a plurality of feature values;
constructing a target user intention vector based on a plurality of the characteristic values;
acquiring a preset travel intention analysis library;
determining a travel intention of the target user based on the target user intention vector and the travel intention analysis library;
wherein, the standard intention vector in the travel intention analysis library is correspondingly associated with the travel intention;
the travel intention of the target user is determined based on the target user intention vector and the travel intention analysis library; the method comprises the following steps:
and matching the target user intention vector with each standard intention vector one by one, and determining the travel intention corresponding to the standard intention vector matched with the target user intention vector.
5. The travel message subscription pushing system of claim 1, further comprising:
the credit adjustment module is used for acquiring second feedback information of the target user on the tourist destination corresponding to the pushed tourist message after the target user selects the tourist destination corresponding to the pushed tourist message which is pushed and verified to play; adjusting the direct credit coefficient of the first user of which the approval degree is greater than or equal to a preset approval threshold value in the verification process of the verified travel message based on the second feedback information;
wherein the credit adjustment module adjusts, based on the second feedback information, a direct credit coefficient of the first user, in which the approval degree is greater than or equal to a preset approval threshold in the verification process of the verified travel message, and includes:
constructing a third key parameter set based on the second feedback information of the target user;
calculating the similarity of the second key parameter set and the third key parameter set;
when the similarity of the second key parameter set and the third key parameter set is greater than or equal to a preset first similarity threshold, performing an up-regulation operation on a direct credit coefficient of the first user, of which the approval degree is greater than or equal to a preset approval threshold in the verification process of the verified travel message, by using a preset first up-regulation value;
when the similarity of the second key parameter set and the third key parameter set is smaller than a preset first similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user, of which the approval degree is greater than or equal to a preset approval threshold in the verification process of the verified travel message, by a preset first down-modulation value;
wherein the first up-modulation value is greater than the first down-modulation value; when the adjusted direct credit coefficient is larger than a preset maximum direct credit coefficient, taking the maximum direct credit coefficient as a final direct credit coefficient of the first user; and when the adjusted direct credit coefficient is smaller than a preset minimum direct credit coefficient, taking the minimum direct credit coefficient as the final direct credit coefficient of the first user.
6. The travel message subscription pushing system of claim 5, wherein said credit adjustment module further performs the following operations:
acquiring third feedback information corresponding to a tour destination corresponding to the verified tour message selected and pushed by the target user by a plurality of second users which are officially authenticated by the big data platform;
constructing a fourth key parameter set based on the third feedback information;
calculating the similarity of the second key parameter set and the fourth key parameter set;
when the similarity between the second key parameter set and the fourth key parameter set is greater than or equal to a preset second similarity threshold, performing an up-regulation operation on an indirect credit coefficient of the first user, of which the approval degree is greater than or equal to a preset approval threshold in the verification process of the verified travel message, by using a preset second up-regulation value;
when the similarity of the second key parameter set and the fourth key parameter set is smaller than a preset similarity threshold, performing down-regulation operation on the direct credit coefficient of the first user, of which the approval degree is greater than or equal to a preset approval threshold in the verification process of the travel message passing the verification, by a preset second down-regulation amplitude value;
wherein the second up-modulation value is greater than the second down-modulation value; when the adjusted indirect credit coefficient is larger than a preset maximum indirect credit coefficient, taking the maximum indirect credit coefficient as a final indirect credit coefficient of the first user; and when the adjusted indirect credit coefficient is smaller than a preset minimum indirect credit coefficient, taking the minimum indirect credit coefficient as the final indirect credit coefficient of the first user.
7. The travel message subscription pushing system of claim 1, wherein the big data platform performs the following operations before storing the first feedback information of the first user for the first user who has played the travel destination corresponding to the travel message:
acquiring historical track data of the first user;
acquiring the position information of each sight spot of the tourist destination;
determining a first set of sights played by the first user based on the historical track data and the location information;
analyzing the first feedback information and determining a second scenic spot set;
when the second attraction set is a subset of the first attraction set, receiving and storing first feedback information of the first user for a first user who has played a tour destination corresponding to the tour message; otherwise, it is not stored.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111337579.7A CN113779418B (en) | 2021-11-12 | 2021-11-12 | Tourism message subscription push system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111337579.7A CN113779418B (en) | 2021-11-12 | 2021-11-12 | Tourism message subscription push system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113779418A CN113779418A (en) | 2021-12-10 |
| CN113779418B true CN113779418B (en) | 2022-03-11 |
Family
ID=78873889
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111337579.7A Expired - Fee Related CN113779418B (en) | 2021-11-12 | 2021-11-12 | Tourism message subscription push system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113779418B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN207399232U (en) * | 2017-06-07 | 2018-05-22 | 孝感市青谷信息科技有限公司 | A kind of message push server |
| CN109919437A (en) * | 2019-01-29 | 2019-06-21 | 特斯联（北京）科技有限公司 | A kind of smart travel target matching method and system based on big data |
| CN111402085A (en) * | 2020-03-11 | 2020-07-10 | 重庆文理学院 | Big data-based travel customization system |
| CN113420210A (en) * | 2020-11-11 | 2021-09-21 | 喻丹 | Big data-based intelligent tourism analysis decision system |
-
2021
- 2021-11-12 CN CN202111337579.7A patent/CN113779418B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN207399232U (en) * | 2017-06-07 | 2018-05-22 | 孝感市青谷信息科技有限公司 | A kind of message push server |
| CN109919437A (en) * | 2019-01-29 | 2019-06-21 | 特斯联（北京）科技有限公司 | A kind of smart travel target matching method and system based on big data |
| CN111402085A (en) * | 2020-03-11 | 2020-07-10 | 重庆文理学院 | Big data-based travel customization system |
| CN113420210A (en) * | 2020-11-11 | 2021-09-21 | 喻丹 | Big data-based intelligent tourism analysis decision system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113779418A (en) | 2021-12-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10929666B2 (en) | System and method for providing augmented reality interactions over printed media | |
| CN104798041B (en) | User's participation in social networks is improved using confirmation instruction | |
| US20090300101A1 (en) | Augmented reality platform and method using letters, numbers, and/or math symbols recognition | |
| CN105491444B (en) | A kind of data identifying processing method and device | |
| CN106651603A (en) | Risk evaluation method and apparatus based on position service | |
| CN112465276A (en) | Method for automatically generating scenic spot playing recommended route | |
| CN108549806B (en) | Identity authentication method based on user sliding and clicking behaviors | |
| CN101010693A (en) | Search system and search method | |
| CN111445308A (en) | Tourist attraction recommendation method based on user portrait | |
| CN103617230A (en) | Method and system for advertisement recommendation based microblog | |
| US20230086644A1 (en) | Cryptographically Enabling Characteristic Assignment to Identities with Tokens, Token Validity Assessments and State Capture Processes | |
| CN101668176A (en) | Multimedia content-on-demand and sharing method based on social interaction graph | |
| KR102097534B1 (en) | Method and apparatus for providing user’s motion recognition based dance game | |
| CN105095355A (en) | Website recommendation method and apparatus | |
| CN116595398A (en) | Resource intelligent matching method and related device based on meta universe | |
| CN116823535B (en) | Journey planning and intelligent navigation system based on multi-mode large model | |
| CN110851621A (en) | Method, device and storage medium for predicting video wonderful level based on knowledge graph | |
| CN107301464B (en) | Method for booking, accompanying and riding of network rented bicycle | |
| US7131581B2 (en) | System for and method of authenticating items | |
| US20220083910A1 (en) | Learning model applying system, a learning model applying method, and a program | |
| CN113779418B (en) | Tourism message subscription push system | |
| US20210216910A1 (en) | Learning system, learning method, and program | |
| KR102357855B1 (en) | Method, apparatus and program for managing specialist career using structured information generated based on unstructured information | |
| CN103577543B (en) | The ranking fraud detection method and ranking fraud detection system of application program | |
| CN110322288A (en) | Shopping Behaviors analysis method, device, system and storage medium based on shopping cart |
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 | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221012 Address after: No.24 Mazhuang, Wafang Village, Xinwujiang Town, Yingdong District, Fuyang City, Anhui Province 236000 Patentee after: Ma Qingqing Address before: 310000 room 1011, building 1, No. 388, Fengtan Road, Gongshu District, Hangzhou City, Zhejiang Province Patentee before: Hangzhou Mingrong Technology Co.,Ltd. |
|
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20220311 |